Changeset 35bae526


Ignore:
Timestamp:
Nov 30, 2017, 12:41:59 PM (4 years ago)
Author:
Thierry Delisle <tdelisle@…>
Branches:
aaron-thesis, arm-eh, cleanup-dtors, deferred_resn, demangler, jacob/cs343-translation, jenkins-sandbox, master, new-ast, new-ast-unique-expr, new-env, no_list, persistent-indexer, resolv-new, with_gc
Children:
c2b9f21
Parents:
875a72f (diff), 389528b0 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.
Message:

Merge branch 'master' of plg.uwaterloo.ca:software/cfa/cfa-cc

Files:
1 added
1 deleted
20 edited

Legend:

Unmodified
Added
Removed
  • doc/proposals/concurrency/.gitignore

    r875a72f r35bae526  
    1313build/*.ind
    1414build/*.ist
     15build/*.lof
    1516build/*.log
     17build/*.lol
     18build/*.lot
    1619build/*.out
    1720build/*.ps
  • doc/proposals/concurrency/Makefile

    r875a72f r35bae526  
    1212style/cfa-format \
    1313annex/glossary \
     14text/frontpgs \
    1415text/intro \
    1516text/basics \
  • doc/proposals/concurrency/annex/glossary.tex

    r875a72f r35bae526  
    44{name={callsite-locking}}
    55{
    6 Locking done by the calling routine. With this technique, a routine calling a monitor routine will aquire the monitor \emph{before} making the call to the actuall routine.
     6Locking done by the calling routine. With this technique, a routine calling a monitor routine aquires the monitor \emph{before} making the call to the actuall routine.
    77}
    88
     
    1010{name={entry-point-locking}}
    1111{
    12 Locking done by the called routine. With this technique, a monitor routine called by another routine will aquire the monitor \emph{after} entering the routine body but prior to any other code.
     12Locking done by the called routine. With this technique, a monitor routine called by another routine aquires the monitor \emph{after} entering the routine body but prior to any other code.
    1313}
    1414
     
    2222{name={multiple-acquisition}}
    2323{
    24 Any locking technique which allow any single thread to acquire a lock multiple times.
     24Any locking technique that allows a single thread to acquire the same lock multiple times.
    2525}
    2626
     
    3535{name={user-level thread}}
    3636{
    37 Threads created and managed inside user-space. Each thread has its own stack and its own thread of execution. User-level threads are insisible to the underlying operating system.
     37Threads created and managed inside user-space. Each thread has its own stack and its own thread of execution. User-level threads are invisible to the underlying operating system.
    3838
    3939\textit{Synonyms : User threads, Lightweight threads, Green threads, Virtual threads, Tasks.}
     
    5151{name={fiber}}
    5252{
    53 Fibers are non-preemptive user-level threads. They share most of the caracteristics of user-level threads except that they cannot be preempted by an other fiber.
     53Fibers are non-preemptive user-level threads. They share most of the caracteristics of user-level threads except that they cannot be preempted by another fiber.
    5454
    5555\textit{Synonyms : Tasks.}
     
    5959{name={job}}
    6060{
    61 Unit of work, often send to a thread pool or worker pool to be executed. Has neither its own stack or its own thread of execution.
     61Unit of work, often sent to a thread pool or worker pool to be executed. Has neither its own stack nor its own thread of execution.
    6262
    6363\textit{Synonyms : Tasks.}
     
    7575{name={cluster}}
    7676{
    77 TBD...
    78 
    79 \textit{Synonyms : None.}
    80 }
    81 
    82 \longnewglossaryentry{cfacpu}
    83 {name={processor}}
    84 {
    85 TBD...
     77A group of \gls{kthread} executed in isolation.
    8678
    8779\textit{Synonyms : None.}
     
    9183{name={thread}}
    9284{
    93 TBD...
     85User level threads that are the default in \CFA. Generally declared using the \code{thread} keyword.
    9486
    9587\textit{Synonyms : None.}
     
    9991{name={preemption}}
    10092{
    101 TBD...
     93Involuntary context switch imposed on threads at a specified rate.
    10294
    10395\textit{Synonyms : None.}
  • doc/proposals/concurrency/annex/local.bib

    r875a72f r35bae526  
    3838        keywords        = {Intel, TBB},
    3939        title   = {Intel Thread Building Blocks},
     40        note            = "\url{https://www.threadingbuildingblocks.org/}"
    4041}
    4142
     
    7475        title   = {TwoHardThings},
    7576        author  = {Martin Fowler},
    76         address = {https://martinfowler.com/bliki/TwoHardThings.html},
     77        howpublished= "\url{https://martinfowler.com/bliki/TwoHardThings.html}",
    7778        year            = 2009
    7879}
     
    8889}
    8990
    90 @misc{affinityLinux,
     91@book{Herlihy93,
     92        title={Transactional memory: Architectural support for lock-free data structures},
     93        author={Herlihy, Maurice and Moss, J Eliot B},
     94        volume={21},
     95        number={2},
     96        year={1993},
     97        publisher={ACM}
     98}
     99
     100@manual{affinityLinux,
    91101        title           = "{Linux man page - sched\_setaffinity(2)}"
    92102}
    93103
    94 @misc{affinityWindows,
     104@manual{affinityWindows,
    95105        title           = "{Windows (vs.85) - SetThreadAffinityMask function}"
    96106}
    97107
    98 @misc{affinityFreebsd,
     108@manual{switchToWindows,
     109        title           = "{Windows (vs.85) - SwitchToFiber function}"
     110}
     111
     112@manual{affinityFreebsd,
    99113        title           = "{FreeBSD General Commands Manual - CPUSET(1)}"
    100114}
    101115
    102 @misc{affinityNetbsd,
     116@manual{affinityNetbsd,
    103117        title           = "{NetBSD Library Functions Manual - AFFINITY(3)}"
    104118}
    105119
    106 @misc{affinityMacosx,
     120@manual{affinityMacosx,
    107121        title           = "{Affinity API Release Notes for OS X v10.5}"
    108122}
     123
     124
     125@misc{NodeJs,
     126        title           = "{Node.js}",
     127        howpublished= "\url{https://nodejs.org/en/}",
     128}
     129
     130@misc{SpringMVC,
     131        title           = "{Spring Web MVC}",
     132        howpublished= "\url{https://docs.spring.io/spring/docs/current/spring-framework-reference/web.html}",
     133}
     134
     135@misc{Django,
     136        title           = "{Django}",
     137        howpublished= "\url{https://www.djangoproject.com/}",
     138}
  • doc/proposals/concurrency/figures/ext_monitor.fig

    r875a72f r35bae526  
    6969         5250 3150 5250 2400
    70702 1 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 5
    71          3150 3150 3750 3150 3750 2850 5850 2850 5850 1650
     71         3150 3150 3750 3150 3750 2850 5700 2850 5700 1650
    72722 1 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 2
    73          5850 2850 6150 3000
     73         5700 2850 6150 3000
    74742 2 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 5
    7575         5100 1800 5400 1800 5400 2400 5100 2400 5100 1800
     
    91914 1 -1 0 0 0 12 0.0000 2 135 735 5100 3975 variables\001
    92924 0 0 50 -1 0 11 0.0000 2 165 855 4275 3150 Acceptables\001
     934 0 0 50 -1 0 11 0.0000 2 120 165 5775 2700 W\001
     944 0 0 50 -1 0 11 0.0000 2 120 135 5775 2400 X\001
     954 0 0 50 -1 0 11 0.0000 2 120 105 5775 2100 Z\001
     964 0 0 50 -1 0 11 0.0000 2 120 135 5775 1800 Y\001
  • doc/proposals/concurrency/figures/int_monitor.fig

    r875a72f r35bae526  
    47471 3 0 1 0 7 50 -1 -1 0.000 1 0.0000 1200 2850 125 125 1200 2850 1082 2809
    48481 3 0 1 0 7 50 -1 -1 0.000 1 0.0000 900 2850 125 125 900 2850 782 2809
    49 1 3 0 1 -1 -1 0 0 4 0.000 1 0.0000 6225 4650 105 105 6225 4650 6330 4755
    50 1 3 0 1 -1 -1 0 0 20 0.000 1 0.0000 3150 4650 80 80 3150 4650 3230 4730
    51 1 3 0 1 -1 -1 0 0 -1 0.000 1 0.0000 4575 4650 105 105 4575 4650 4680 4755
     491 3 0 1 -1 -1 0 0 -1 0.000 1 0.0000 6000 4650 105 105 6000 4650 6105 4755
     501 3 0 1 -1 -1 0 0 20 0.000 1 0.0000 3900 4650 80 80 3900 4650 3980 4730
    52512 1 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 2
    5352         3900 1950 4200 2100
     
    1071064 1 -1 0 0 0 12 0.0000 2 165 420 4050 1050 entry\001
    1081074 0 0 50 -1 0 11 0.0000 2 120 705 600 2325 Condition\001
    109 4 0 -1 0 0 0 12 0.0000 2 180 930 6450 4725 routine ptrs\001
    110 4 0 -1 0 0 0 12 0.0000 2 135 1050 3300 4725 active thread\001
    111 4 0 -1 0 0 0 12 0.0000 2 135 1215 4725 4725 blocked thread\001
     1084 0 -1 0 0 0 12 0.0000 2 135 1215 6150 4725 blocked thread\001
     1094 0 -1 0 0 0 12 0.0000 2 135 1050 4050 4725 active thread\001
  • doc/proposals/concurrency/style/cfa-format.tex

    r875a72f r35bae526  
    178178    language = C,
    179179    style=defaultStyle,
     180    captionpos=b,
    180181    #1
    181182  }
     
    186187    language = CFA,
    187188    style=cfaStyle,
     189    captionpos=b,
    188190    #1
    189191  }
     
    194196    language = pseudo,
    195197    style=pseudoStyle,
     198    captionpos=b,
    196199    #1
    197200  }
     
    202205    language = c++,
    203206    style=defaultStyle,
     207    captionpos=b,
    204208    #1
    205209  }
     
    210214    language = c++,
    211215    style=defaultStyle,
     216    captionpos=b,
    212217    #1
    213218  }
     
    218223    language = java,
    219224    style=defaultStyle,
     225    captionpos=b,
    220226    #1
    221227  }
     
    226232    language = scala,
    227233    style=defaultStyle,
     234    captionpos=b,
    228235    #1
    229236  }
     
    234241    language = sml,
    235242    style=defaultStyle,
     243    captionpos=b,
    236244    #1
    237245  }
     
    242250    language = D,
    243251    style=defaultStyle,
     252    captionpos=b,
    244253    #1
    245254  }
     
    250259    language = rust,
    251260    style=defaultStyle,
     261    captionpos=b,
    252262    #1
    253263  }
     
    258268    language = Golang,
    259269    style=defaultStyle,
     270    captionpos=b,
    260271    #1
    261272  }
  • doc/proposals/concurrency/text/basics.tex

    r875a72f r35bae526  
    1111Execution with a single thread and multiple stacks where the thread is self-scheduling deterministically across the stacks is called coroutining. Execution with a single and multiple stacks but where the thread is scheduled by an oracle (non-deterministic from the thread perspective) across the stacks is called concurrency.
    1212
    13 Therefore, a minimal concurrency system can be achieved by creating coroutines, which instead of context switching among each other, always ask an oracle where to context switch next. While coroutines can execute on the caller's stack-frame, stackfull coroutines allow full generality and are sufficient as the basis for concurrency. The aforementioned oracle is a scheduler and the whole system now follows a cooperative threading-model (a.k.a non-preemptive scheduling). The oracle/scheduler can either be a stackless or stackfull entity and correspondingly require one or two context switches to run a different coroutine. In any case, a subset of concurrency related challenges start to appear. For the complete set of concurrency challenges to occur, the only feature missing is preemption.
    14 
    15 A scheduler introduces order of execution uncertainty, while preemption introduces uncertainty about where context-switches occur. Mutual-exclusion and synchronisation are ways of limiting non-determinism in a concurrent system. Now it is important to understand that uncertainty is desireable; uncertainty can be used by runtime systems to significantly increase performance and is often the basis of giving a user the illusion that tasks are running in parallel. Optimal performance in concurrent applications is often obtained by having as much non-determinism as correctness allows.
     13Therefore, a minimal concurrency system can be achieved by creating coroutines, which instead of context switching among each other, always ask an oracle where to context switch next. While coroutines can execute on the caller's stack-frame, stack-full coroutines allow full generality and are sufficient as the basis for concurrency. The aforementioned oracle is a scheduler and the whole system now follows a cooperative threading-model (a.k.a non-preemptive scheduling). The oracle/scheduler can either be a stack-less or stack-full entity and correspondingly require one or two context switches to run a different coroutine. In any case, a subset of concurrency related challenges start to appear. For the complete set of concurrency challenges to occur, the only feature missing is preemption.
     14
     15A scheduler introduces order of execution uncertainty, while preemption introduces uncertainty about where context-switches occur. Mutual-exclusion and synchronization are ways of limiting non-determinism in a concurrent system. Now it is important to understand that uncertainty is desirable; uncertainty can be used by runtime systems to significantly increase performance and is often the basis of giving a user the illusion that tasks are running in parallel. Optimal performance in concurrent applications is often obtained by having as much non-determinism as correctness allows.
    1616
    1717\section{\protect\CFA 's Thread Building Blocks}
    18 One of the important features that is missing in C is threading. On modern architectures, a lack of threading is unacceptable\cite{Sutter05, Sutter05b}, and therefore modern programming languages must have the proper tools to allow users to write performant concurrent programs to take advantage of parallelism. As an extension of C, \CFA needs to express these concepts in a way that is as natural as possible to programmers familiar with imperative languages. And being a system-level language means programmers expect to choose precisely which features they need and which cost they are willing to pay.
     18One of the important features that is missing in C is threading. On modern architectures, a lack of threading is unacceptable~\cite{Sutter05, Sutter05b}, and therefore modern programming languages must have the proper tools to allow users to write performant concurrent programs to take advantage of parallelism. As an extension of C, \CFA needs to express these concepts in a way that is as natural as possible to programmers familiar with imperative languages. And being a system-level language means programmers expect to choose precisely which features they need and which cost they are willing to pay.
    1919
    2020\section{Coroutines: A stepping stone}\label{coroutine}
    2121While the main focus of this proposal is concurrency and parallelism, it is important to address coroutines, which are actually a significant building block of a concurrency system. Coroutines need to deal with context-switches and other context-management operations. Therefore, this proposal includes coroutines both as an intermediate step for the implementation of threads, and a first class feature of \CFA. Furthermore, many design challenges of threads are at least partially present in designing coroutines, which makes the design effort that much more relevant. The core \acrshort{api} of coroutines revolve around two features: independent call stacks and \code{suspend}/\code{resume}.
    2222
    23 \begin{figure}
     23\begin{table}
    2424\begin{center}
    2525\begin{tabular}{c @{\hskip 0.025in}|@{\hskip 0.025in} c @{\hskip 0.025in}|@{\hskip 0.025in} c}
     
    6262void fibonacci_array(
    6363        int n,
    64         int * array
     64        int* array
    6565) {
    6666        int f1 = 0; int f2 = 1;
     
    9999
    100100int fibonacci_state(
    101         Iterator_t * it
     101        Iterator_t* it
    102102) {
    103103        int f;
     
    129129\end{tabular}
    130130\end{center}
    131 \caption{Different implementations of a fibonacci sequence generator in C.}
     131\caption{Different implementations of a Fibonacci sequence generator in C.},
    132132\label{lst:fibonacci-c}
    133 \end{figure}
    134 
    135 A good example of a problem made easier with coroutines is generators, like the fibonacci sequence. This problem comes with the challenge of decoupling how a sequence is generated and how it is used. Figure \ref{lst:fibonacci-c} shows conventional approaches to writing generators in C. All three of these approach suffer from strong coupling. The left and center approaches require that the generator have knowledge of how the sequence is used, while the rightmost approach requires holding internal state between calls on behalf of the generator and makes it much harder to handle corner cases like the Fibonacci seed.
    136 
    137 Figure \ref{lst:fibonacci-cfa} is an example of a solution to the fibonnaci problem using \CFA coroutines, where the coroutine stack holds sufficient state for the generation. This solution has the advantage of having very strong decoupling between how the sequence is generated and how it is used. Indeed, this version is as easy to use as the \code{fibonacci_state} solution, while the imlpementation is very similar to the \code{fibonacci_func} example.
     133\end{table}
     134
     135A good example of a problem made easier with coroutines is generators, like the Fibonacci sequence. This problem comes with the challenge of decoupling how a sequence is generated and how it is used. Table \ref{lst:fibonacci-c} shows conventional approaches to writing generators in C. All three of these approach suffer from strong coupling. The left and center approaches require that the generator have knowledge of how the sequence is used, while the rightmost approach requires holding internal state between calls on behalf of the generator and makes it much harder to handle corner cases like the Fibonacci seed.
     136
     137Listing \ref{lst:fibonacci-cfa} is an example of a solution to the Fibonacci problem using \CFA coroutines, where the coroutine stack holds sufficient state for the next generation. This solution has the advantage of having very strong decoupling between how the sequence is generated and how it is used. Indeed, this version is as easy to use as the \code{fibonacci_state} solution, while the implementation is very similar to the \code{fibonacci_func} example.
    138138
    139139\begin{figure}
    140 \begin{cfacode}
     140\begin{cfacode}[caption={Implementation of Fibonacci using coroutines},label={lst:fibonacci-cfa}]
    141141coroutine Fibonacci {
    142142        int fn; //used for communication
    143143};
    144144
    145 void ?{}(Fibonacci & this) { //constructor
     145void ?{}(Fibonacci& this) { //constructor
    146146        this.fn = 0;
    147147}
    148148
    149 //main automacically called on first resume
    150 void main(Fibonacci & this) with (this) {
     149//main automatically called on first resume
     150void main(Fibonacci& this) with (this) {
    151151        int fn1, fn2;           //retained between resumes
    152152        fn  = 0;
     
    167167}
    168168
    169 int next(Fibonacci & this) {
     169int next(Fibonacci& this) {
    170170        resume(this); //transfer to last suspend
    171171        return this.fn;
     
    179179}
    180180\end{cfacode}
    181 \caption{Implementation of fibonacci using coroutines}
    182 \label{lst:fibonacci-cfa}
    183181\end{figure}
    184182
    185 Figure \ref{lst:fmt-line} shows the \code{Format} coroutine which rearranges text in order to group characters into blocks of fixed size. The example takes advantage of resuming coroutines in the constructor to simplify the code and highlights the idea that interesting control flow can occur in the constructor.
     183Listing \ref{lst:fmt-line} shows the \code{Format} coroutine for restructuring text into groups of character blocks of fixed size. The example takes advantage of resuming coroutines in the constructor to simplify the code and highlights the idea that interesting control flow can occur in the constructor.
    186184
    187185\begin{figure}
    188 \begin{cfacode}[tabsize=3]
     186\begin{cfacode}[tabsize=3,caption={Formatting text into lines of 5 blocks of 4 characters.},label={lst:fmt-line}]
    189187//format characters into blocks of 4 and groups of 5 blocks per line
    190188coroutine Format {
     
    193191};
    194192
    195 void  ?{}(Format & fmt) {
     193void  ?{}(Format& fmt) {
    196194        resume( fmt );                                                  //prime (start) coroutine
    197195}
    198196
    199 void ^?{}(Format & fmt) with fmt {
     197void ^?{}(Format& fmt) with fmt {
    200198        if ( fmt.g != 0 || fmt.b != 0 )
    201199        sout | endl;
    202200}
    203201
    204 void main(Format & fmt) with fmt {
     202void main(Format& fmt) with fmt {
    205203        for ( ;; ) {                                                    //for as many characters
    206204                for(g = 0; g < 5; g++) {                //groups of 5 blocks
     
    230228}
    231229\end{cfacode}
    232 \caption{Formatting text into lines of 5 blocks of 4 characters.}
    233 \label{lst:fmt-line}
    234230\end{figure}
    235231
    236232\subsection{Construction}
    237 One important design challenge for coroutines and threads (shown in section \ref{threads}) is that the runtime system needs to run code after the user-constructor runs to connect the fully constructed object into the system. In the case of coroutines, this challenge is simpler since there is no non-determinism from preemption or scheduling. However, the underlying challenge remains the same for coroutines and threads.
    238 
    239 The runtime system needs to create the coroutine's stack and more importantly prepare it for the first resumption. The timing of the creation is non-trivial since users both expect to have fully constructed objects once execution enters the coroutine main and to be able to resume the coroutine from the constructor. As regular objects, constructors can leak coroutines before they are ready. There are several solutions to this problem but the chosen options effectively forces the design of the coroutine.
     233One important design challenge for implementing coroutines and threads (shown in section \ref{threads}) is that the runtime system needs to run code after the user-constructor runs to connect the fully constructed object into the system. In the case of coroutines, this challenge is simpler since there is no non-determinism from preemption or scheduling. However, the underlying challenge remains the same for coroutines and threads.
     234
     235The runtime system needs to create the coroutine's stack and more importantly prepare it for the first resumption. The timing of the creation is non-trivial since users both expect to have fully constructed objects once execution enters the coroutine main and to be able to resume the coroutine from the constructor. There are several solutions to this problem but the chosen options effectively forces the design of the coroutine.
    240236
    241237Furthermore, \CFA faces an extra challenge as polymorphic routines create invisible thunks when casted to non-polymorphic routines and these thunks have function scope. For example, the following code, while looking benign, can run into undefined behaviour because of thunks:
     
    258254
    259255\begin{ccode}
    260 extern void async(/* omitted */, void (*func)(void *), void *obj);
    261 
    262 void noop(/* omitted */, void *obj){}
     256extern void async(/* omitted */, void (*func)(void*), void* obj);
     257
     258void noop(/* omitted */, void* obj){}
    263259
    264260void bar(){
    265261        int a;
    266         void _thunk0(int *_p0){
     262        void _thunk0(int* _p0){
    267263                /* omitted */
    268264                noop(/* omitted */, _p0);
    269265        }
    270266        /* omitted */
    271         async(/* omitted */, ((void (*)(void *))(&_thunk0)), (&a));
     267        async(/* omitted */, ((void (*)(void*))(&_thunk0)), (&a));
    272268}
    273269\end{ccode}
    274 The problem in this example is a storage management issue, the function pointer \code{_thunk0} is only valid until the end of the block, which limits the viable solutions because storing the function pointer for too long causes undefined behavior; i.e., the stack-based thunk being destroyed before it can be used. This challenge is an extension of challenges that come with second-class routines. Indeed, GCC nested routines also have the limitation that nested routine cannot be passed outside of the declaration scope. The case of coroutines and threads is simply an extension of this problem to multiple call-stacks.
     270The problem in this example is a storage management issue, the function pointer \code{_thunk0} is only valid until the end of the block, which limits the viable solutions because storing the function pointer for too long causes Undefined Behavior; i.e., the stack-based thunk being destroyed before it can be used. This challenge is an extension of challenges that come with second-class routines. Indeed, GCC nested routines also have the limitation that nested routine cannot be passed outside of the declaration scope. The case of coroutines and threads is simply an extension of this problem to multiple call-stacks.
    275271
    276272\subsection{Alternative: Composition}
    277 One solution to this challenge is to use composition/containement, where coroutine fields are added to manage the coroutine.
     273One solution to this challenge is to use composition/containment, where coroutine fields are added to manage the coroutine.
    278274
    279275\begin{cfacode}
     
    283279};
    284280
    285 void FibMain(void *) {
     281void FibMain(void*) {
    286282        //...
    287283}
    288284
    289 void ?{}(Fibonacci & this) {
     285void ?{}(Fibonacci& this) {
    290286        this.fn = 0;
    291287        //Call constructor to initialize coroutine
     
    293289}
    294290\end{cfacode}
    295 The downside of this approach is that users need to correctly construct the coroutine handle before using it. Like any other objects, doing so the users carefully choose construction order to prevent usage of unconstructed objects. However, in the case of coroutines, users must also pass to the coroutine information about the coroutine main, like in the previous example. This opens the door for user errors and requires extra runtime storage to pass at runtime information that can be known statically.
     291The downside of this approach is that users need to correctly construct the coroutine handle before using it. Like any other objects, the user must carefully choose construction order to prevent usage of objects not yet constructed. However, in the case of coroutines, users must also pass to the coroutine information about the coroutine main, like in the previous example. This opens the door for user errors and requires extra runtime storage to pass at runtime information that can be known statically.
    296292
    297293\subsection{Alternative: Reserved keyword}
     
    303299};
    304300\end{cfacode}
    305 The \code{coroutine} keyword means the compiler can find and inject code where needed. The downside of this approach is that it makes coroutine a special case in the language. Users wantint to extend coroutines or build their own for various reasons can only do so in ways offered by the language. Furthermore, implementing coroutines without language supports also displays the power of the programming language used. While this is ultimately the option used for idiomatic \CFA code, coroutines and threads can still be constructed by users without using the language support. The reserved keywords are only present to improve ease of use for the common cases.
    306 
    307 \subsection{Alternative: Lamda Objects}
    308 
    309 For coroutines as for threads, many implementations are based on routine pointers or function objects\cite{Butenhof97, ANSI14:C++, MS:VisualC++, BoostCoroutines15}. For example, Boost implements coroutines in terms of four functor object types:
     301The \code{coroutine} keyword means the compiler can find and inject code where needed. The downside of this approach is that it makes coroutine a special case in the language. Users wanting to extend coroutines or build their own for various reasons can only do so in ways offered by the language. Furthermore, implementing coroutines without language supports also displays the power of the programming language used. While this is ultimately the option used for idiomatic \CFA code, coroutines and threads can still be constructed by users without using the language support. The reserved keywords are only present to improve ease of use for the common cases.
     302
     303\subsection{Alternative: Lambda Objects}
     304
     305For coroutines as for threads, many implementations are based on routine pointers or function objects~\cite{Butenhof97, ANSI14:C++, MS:VisualC++, BoostCoroutines15}. For example, Boost implements coroutines in terms of four functor object types:
    310306\begin{cfacode}
    311307asymmetric_coroutine<>::pull_type
     
    318314A variation of this would be to use a simple function pointer in the same way pthread does for threads :
    319315\begin{cfacode}
    320 void foo( coroutine_t cid, void * arg ) {
    321         int * value = (int *)arg;
     316void foo( coroutine_t cid, void* arg ) {
     317        int* value = (int*)arg;
    322318        //Coroutine body
    323319}
     
    329325}
    330326\end{cfacode}
    331 This semantics is more common for thread interfaces than coroutines works equally well. As discussed in section \ref{threads}, this approach is superseeded by static approaches in terms of expressivity.
     327This semantics is more common for thread interfaces but coroutines work equally well. As discussed in section \ref{threads}, this approach is superseded by static approaches in terms of expressivity.
    332328
    333329\subsection{Alternative: Trait-based coroutines}
     
    337333\begin{cfacode}
    338334trait is_coroutine(dtype T) {
    339       void main(T & this);
    340       coroutine_desc * get_coroutine(T & this);
    341 };
    342 
    343 forall( dtype T | is_coroutine(T) ) void suspend(T &);
    344 forall( dtype T | is_coroutine(T) ) void resume (T &);
    345 \end{cfacode}
    346 This ensures an object is not a coroutine until \code{resume} is called on the object. Correspondingly, any object that is passed to \code{resume} is a coroutine since it must satisfy the \code{is_coroutine} trait to compile. The advantage of this approach is that users can easily create different types of coroutines, for example, changing the memory layout of a coroutine is trivial when implementing the \code{get_coroutine} routine. The \CFA keyword \code{coroutine} only has the effect of implementing the getter and forward declarations required for users to only have to implement the main routine.
     335      void main(T& this);
     336      coroutine_desc* get_coroutine(T& this);
     337};
     338
     339forall( dtype T | is_coroutine(T) ) void suspend(T&);
     340forall( dtype T | is_coroutine(T) ) void resume (T&);
     341\end{cfacode}
     342This ensures an object is not a coroutine until \code{resume} is called on the object. Correspondingly, any object that is passed to \code{resume} is a coroutine since it must satisfy the \code{is_coroutine} trait to compile. The advantage of this approach is that users can easily create different types of coroutines, for example, changing the memory layout of a coroutine is trivial when implementing the \code{get_coroutine} routine. The \CFA keyword \code{coroutine} only has the effect of implementing the getter and forward declarations required for users to implement the main routine.
    347343
    348344\begin{center}
     
    359355
    360356static inline
    361 coroutine_desc * get_coroutine(
    362         struct MyCoroutine & this
     357coroutine_desc* get_coroutine(
     358        struct MyCoroutine& this
    363359) {
    364360        return &this.__cor;
    365361}
    366362
    367 void main(struct MyCoroutine * this);
     363void main(struct MyCoroutine* this);
    368364\end{cfacode}
    369365\end{tabular}
    370366\end{center}
    371367
    372 The combination of these two approaches allows users new to coroutinning and concurrency to have an easy and concise specification, while more advanced users have tighter control on memory layout and initialization.
     368The combination of these two approaches allows users new to coroutining and concurrency to have an easy and concise specification, while more advanced users have tighter control on memory layout and initialization.
    373369
    374370\section{Thread Interface}\label{threads}
     
    379375\end{cfacode}
    380376
    381 As for coroutines, the keyword is a thin wrapper arount a \CFA trait:
     377As for coroutines, the keyword is a thin wrapper around a \CFA trait:
    382378
    383379\begin{cfacode}
     
    389385\end{cfacode}
    390386
    391 Obviously, for this thread implementation to be usefull it must run some user code. Several other threading interfaces use a function-pointer representation as the interface of threads (for example \Csharp~\cite{Csharp} and Scala~\cite{Scala}). However, this proposal considers that statically tying a \code{main} routine to a thread superseeds this approach. Since the \code{main} routine is already a special routine in \CFA (where the program begins), it is a natural extension of the semantics using overloading to declare mains for different threads (the normal main being the main of the initial thread). As such the \code{main} routine of a thread can be defined as
     387Obviously, for this thread implementation to be useful it must run some user code. Several other threading interfaces use a function-pointer representation as the interface of threads (for example \Csharp~\cite{Csharp} and Scala~\cite{Scala}). However, this proposal considers that statically tying a \code{main} routine to a thread supersedes this approach. Since the \code{main} routine is already a special routine in \CFA (where the program begins), it is a natural extension of the semantics using overloading to declare mains for different threads (the normal main being the main of the initial thread). As such the \code{main} routine of a thread can be defined as
    392388\begin{cfacode}
    393389thread foo {};
     
    416412        this.func( this.arg );
    417413}
     414
     415void hello(/*unused*/ int) {
     416        sout | "Hello World!" | endl;
     417}
     418
     419int main() {
     420        FuncRunner f = {hello, 42};
     421        return 0'
     422}
    418423\end{cfacode}
    419424
     
    439444\end{cfacode}
    440445
    441 This semantic has several advantages over explicit semantics: a thread is always started and stopped exaclty once, users cannot make any progamming errors, and it naturally scales to multiple threads meaning basic synchronisation is very simple.
     446This semantic has several advantages over explicit semantics: a thread is always started and stopped exactly once, users cannot make any programming errors, and it naturally scales to multiple threads meaning basic synchronization is very simple.
    442447
    443448\begin{cfacode}
     
    447452
    448453//main
    449 void main(MyThread & this) {
     454void main(MyThread& this) {
    450455        //...
    451456}
     
    461466\end{cfacode}
    462467
    463 However, one of the drawbacks of this approach is that threads now always form a lattice, that is they are always destroyed in the opposite order of construction because of block structure. This restriction is relaxed by using dynamic allocation, so threads can outlive the scope in which they are created, much like dynamically allocating memory lets objects outlive the scope in which they are created.
     468However, one of the drawbacks of this approach is that threads always form a lattice, i.e., they are always destroyed in the opposite order of construction because of block structure. This restriction is relaxed by using dynamic allocation, so threads can outlive the scope in which they are created, much like dynamically allocating memory lets objects outlive the scope in which they are created.
    464469
    465470\begin{cfacode}
     
    468473};
    469474
    470 void main(MyThread & this) {
     475void main(MyThread& this) {
    471476        //...
    472477}
    473478
    474479void foo() {
    475         MyThread * long_lived;
     480        MyThread* long_lived;
    476481        {
    477482                //Start a thread at the beginning of the scope
  • doc/proposals/concurrency/text/cforall.tex

    r875a72f r35bae526  
    11% ======================================================================
    22% ======================================================================
    3 \chapter{Cforall Overview}
     3\chapter{\CFA Overview}
    44% ======================================================================
    55% ======================================================================
     
    77The following is a quick introduction to the \CFA language, specifically tailored to the features needed to support concurrency.
    88
    9 \CFA is a extension of ISO-C and therefore supports all of the same paradigms as C. It is a non-object oriented system language, meaning most of the major abstractions have either no runtime overhead or can be opt-out easily. Like C, the basics of \CFA revolve around structures and routines, which are thin abstractions over machine code. The vast majority of the code produced by the \CFA translator respects memory-layouts and calling-conventions laid out by C. Interestingly, while \CFA is not an object-oriented language, lacking the concept of a receiver (e.g., this), it does have some notion of objects\footnote{C defines the term objects as : ``region of data storage in the execution environment, the contents of which can represent
    10 values''\cite[3.15]{C11}}, most importantly construction and destruction of objects. Most of the following code examples can be found on the \CFA website \cite{www-cfa}
     9\CFA is an extension of ISO-C and therefore supports all of the same paradigms as C. It is a non-object-oriented system-language, meaning most of the major abstractions have either no runtime overhead or can be opt-out easily. Like C, the basics of \CFA revolve around structures and routines, which are thin abstractions over machine code. The vast majority of the code produced by the \CFA translator respects memory-layouts and calling-conventions laid out by C. Interestingly, while \CFA is not an object-oriented language, lacking the concept of a receiver (e.g., {\tt this}), it does have some notion of objects\footnote{C defines the term objects as : ``region of data storage in the execution environment, the contents of which can represent
     10values''~\cite[3.15]{C11}}, most importantly construction and destruction of objects. Most of the following code examples can be found on the \CFA website~\cite{www-cfa}
    1111
     12% ======================================================================
    1213\section{References}
    1314
    14 Like \CC, \CFA introduces rebindable references providing multiple dereferecing as an alternative to pointers. In regards to concurrency, the semantic difference between pointers and references are not particularly relevant, but since this document uses mostly references, here is a quick overview of the semantics:
     15Like \CC, \CFA introduces rebind-able references providing multiple dereferencing as an alternative to pointers. In regards to concurrency, the semantic difference between pointers and references are not particularly relevant, but since this document uses mostly references, here is a quick overview of the semantics:
    1516\begin{cfacode}
    1617int x, *p1 = &x, **p2 = &p1, ***p3 = &p2,
     
    2122*p3   = ...;                                            //change p2
    2223int y, z, & ar[3] = {x, y, z};          //initialize array of references
    23 typeof( ar[1]) p;                                       //is int, i.e., the type of referenced object
    24 typeof(&ar[1]) q;                                       //is int &, i.e., the type of reference
    25 sizeof( ar[1]) == sizeof(int);          //is true, i.e., the size of referenced object
    26 sizeof(&ar[1]) == sizeof(int *);        //is true, i.e., the size of a reference
     24typeof( ar[1]) p;                                       //is int, referenced object type
     25typeof(&ar[1]) q;                                       //is int &, reference type
     26sizeof( ar[1]) == sizeof(int);          //is true, referenced object size
     27sizeof(&ar[1]) == sizeof(int *);        //is true, reference size
    2728\end{cfacode}
    28 The important take away from this code example is that references offer a handle to an object, much like pointers, but which is automatically dereferenced for convinience.
     29The important take away from this code example is that a reference offers a handle to an object, much like a pointer, but which is automatically dereferenced for convenience.
    2930
     31% ======================================================================
    3032\section{Overloading}
    3133
    32 Another important feature of \CFA is function overloading as in Java and \CC, where routines with the same name are selected based on the number and type of the arguments. As well, \CFA uses the return type as part of the selection criteria, as in Ada\cite{Ada}. For routines with multiple parameters and returns, the selection is complex.
     34Another important feature of \CFA is function overloading as in Java and \CC, where routines with the same name are selected based on the number and type of the arguments. As well, \CFA uses the return type as part of the selection criteria, as in Ada~\cite{Ada}. For routines with multiple parameters and returns, the selection is complex.
    3335\begin{cfacode}
    3436//selection based on type and number of parameters
     
    4850This feature is particularly important for concurrency since the runtime system relies on creating different types to represent concurrency objects. Therefore, overloading is necessary to prevent the need for long prefixes and other naming conventions that prevent name clashes. As seen in chapter \ref{basics}, routine \code{main} is an example that benefits from overloading.
    4951
     52% ======================================================================
    5053\section{Operators}
    5154Overloading also extends to operators. The syntax for denoting operator-overloading is to name a routine with the symbol of the operator and question marks where the arguments of the operation occur, e.g.:
     
    6770While concurrency does not use operator overloading directly, this feature is more important as an introduction for the syntax of constructors.
    6871
     72% ======================================================================
    6973\section{Constructors/Destructors}
    7074Object life-time is often a challenge in concurrency. \CFA uses the approach of giving concurrent meaning to object life-time as a mean of synchronization and/or mutual exclusion. Since \CFA relies heavily on the life time of objects, constructors and destructors are a core feature required for concurrency and parallelism. \CFA uses the following syntax for constructors and destructors :
     
    8286}
    8387int main() {
    84         S x = {10}, y = {100};          //implict calls: ?{}(x, 10), ?{}(y, 100)
     88        S x = {10}, y = {100};          //implicit calls: ?{}(x, 10), ?{}(y, 100)
    8589        ...                                                     //use x and y
    8690        ^x{};  ^y{};                            //explicit calls to de-initialize
    8791        x{20};  y{200};                         //explicit calls to reinitialize
    8892        ...                                                     //reuse x and y
    89 }                                                               //implict calls: ^?{}(y), ^?{}(x)
     93}                                                               //implicit calls: ^?{}(y), ^?{}(x)
    9094\end{cfacode}
    9195The language guarantees that every object and all their fields are constructed. Like \CC, construction of an object is automatically done on allocation and destruction of the object is done on deallocation. Allocation and deallocation can occur on the stack or on the heap.
     
    99103delete(s);                              //deallocation, call destructor
    100104\end{cfacode}
    101 Note that like \CC, \CFA introduces \code{new} and \code{delete}, which behave like \code{malloc} and \code{free} in addition to constructing and destructing objects, after calling \code{malloc} and before calling \code{free} respectively.
     105Note that like \CC, \CFA introduces \code{new} and \code{delete}, which behave like \code{malloc} and \code{free} in addition to constructing and destructing objects, after calling \code{malloc} and before calling \code{free}, respectively.
    102106
     107% ======================================================================
    103108\section{Parametric Polymorphism}
    104 Routines in \CFA can also be reused for multiple types. This capability is done using the \code{forall} clause which gives \CFA its name. \code{forall} clauses allow separately compiled routines to support generic usage over multiple types. For example, the following sum function works for any type that supports construction from 0 and addition :
     109Routines in \CFA can also be reused for multiple types. This capability is done using the \code{forall} clause, which gives \CFA its name. \code{forall} clauses allow separately compiled routines to support generic usage over multiple types. For example, the following sum function works for any type that supports construction from 0 and addition :
    105110\begin{cfacode}
    106111//constraint type, 0 and +
     
    130135\end{cfacode}
    131136
     137Note that the type use for assertions can be either an \code{otype} or a \code{dtype}. Types declares as \code{otype} refer to ``complete'' objects, i.e., objects with a size, a default constructor, a copy constructor, a destructor and an assignment operator. Using \code{dtype} on the other hand has none of these assumptions but is extremely restrictive, it only guarantees the object is addressable.
     138
     139% ======================================================================
    132140\section{with Clause/Statement}
    133141Since \CFA lacks the concept of a receiver, certain functions end-up needing to repeat variable names often. To remove this inconvenience, \CFA provides the \code{with} statement, which opens an aggregate scope making its fields directly accessible (like Pascal).
     
    135143struct S { int i, j; };
    136144int mem(S & this) with (this)           //with clause
    137         i = 1;                                          //this->i
    138         j = 2;                                          //this->j
     145        i = 1;                                                  //this->i
     146        j = 2;                                                  //this->j
    139147}
    140148int foo() {
    141149        struct S1 { ... } s1;
    142150        struct S2 { ... } s2;
    143         with (s1)                                       //with statement
     151        with (s1)                                               //with statement
    144152        {
    145                 //access fields of s1
    146                 //without qualification
     153                //access fields of s1 without qualification
    147154                with (s2)                                       //nesting
    148155                {
    149                         //access fields of s1 and s2
    150                         //without qualification
     156                        //access fields of s1 and s2 without qualification
    151157                }
    152158        }
    153         with (s1, s2)                           //scopes open in parallel
     159        with (s1, s2)                                   //scopes open in parallel
    154160        {
    155                 //access fields of s1 and s2
    156                 //without qualification
     161                //access fields of s1 and s2 without qualification
    157162        }
    158163}
  • doc/proposals/concurrency/text/concurrency.tex

    r875a72f r35bae526  
    44% ======================================================================
    55% ======================================================================
    6 Several tool can be used to solve concurrency challenges. Since many of these challenges appear with the use of mutable shared-state, some languages and libraries simply disallow mutable shared-state (Erlang~\cite{Erlang}, Haskell~\cite{Haskell}, Akka (Scala)~\cite{Akka}). In these paradigms, interaction among concurrent objects relies on message passing~\cite{Thoth,Harmony,V-Kernel} or other paradigms closely relate to networking concepts (channels\cite{CSP,Go} for example). However, in languages that use routine calls as their core abstraction-mechanism, these approaches force a clear distinction between concurrent and non-concurrent paradigms (i.e., message passing versus routine call). This distinction in turn means that, in order to be effective, programmers need to learn two sets of designs patterns. While this distinction can be hidden away in library code, effective use of the librairy still has to take both paradigms into account.
    7 
    8 Approaches based on shared memory are more closely related to non-concurrent paradigms since they often rely on basic constructs like routine calls and shared objects. At the lowest level, concurrent paradigms are implemented as atomic operations and locks. Many such mechanisms have been proposed, including semaphores~\cite{Dijkstra68b} and path expressions~\cite{Campbell74}. However, for productivity reasons it is desireable to have a higher-level construct be the core concurrency paradigm~\cite{HPP:Study}.
    9 
    10 An approach that is worth mentioning because it is gaining in popularity is transactionnal memory~\cite{Dice10}[Check citation]. While this approach is even pursued by system languages like \CC\cite{Cpp-Transactions}, the performance and feature set is currently too restrictive to be the main concurrency paradigm for systems language, which is why it was rejected as the core paradigm for concurrency in \CFA.
     6Several tool can be used to solve concurrency challenges. Since many of these challenges appear with the use of mutable shared-state, some languages and libraries simply disallow mutable shared-state (Erlang~\cite{Erlang}, Haskell~\cite{Haskell}, Akka (Scala)~\cite{Akka}). In these paradigms, interaction among concurrent objects relies on message passing~\cite{Thoth,Harmony,V-Kernel} or other paradigms closely relate to networking concepts (channels~\cite{CSP,Go} for example). However, in languages that use routine calls as their core abstraction-mechanism, these approaches force a clear distinction between concurrent and non-concurrent paradigms (i.e., message passing versus routine call). This distinction in turn means that, in order to be effective, programmers need to learn two sets of designs patterns. While this distinction can be hidden away in library code, effective use of the library still has to take both paradigms into account.
     7
     8Approaches based on shared memory are more closely related to non-concurrent paradigms since they often rely on basic constructs like routine calls and shared objects. At the lowest level, concurrent paradigms are implemented as atomic operations and locks. Many such mechanisms have been proposed, including semaphores~\cite{Dijkstra68b} and path expressions~\cite{Campbell74}. However, for productivity reasons it is desirable to have a higher-level construct be the core concurrency paradigm~\cite{HPP:Study}.
     9
     10An approach that is worth mentioning because it is gaining in popularity is transactional memory~\cite{Herlihy93}. While this approach is even pursued by system languages like \CC~\cite{Cpp-Transactions}, the performance and feature set is currently too restrictive to be the main concurrency paradigm for systems language, which is why it was rejected as the core paradigm for concurrency in \CFA.
    1111
    1212One of the most natural, elegant, and efficient mechanisms for synchronization and communication, especially for shared-memory systems, is the \emph{monitor}. Monitors were first proposed by Brinch Hansen~\cite{Hansen73} and later described and extended by C.A.R.~Hoare~\cite{Hoare74}. Many programming languages---e.g., Concurrent Pascal~\cite{ConcurrentPascal}, Mesa~\cite{Mesa}, Modula~\cite{Modula-2}, Turing~\cite{Turing:old}, Modula-3~\cite{Modula-3}, NeWS~\cite{NeWS}, Emerald~\cite{Emerald}, \uC~\cite{Buhr92a} and Java~\cite{Java}---provide monitors as explicit language constructs. In addition, operating-system kernels and device drivers have a monitor-like structure, although they often use lower-level primitives such as semaphores or locks to simulate monitors. For these reasons, this project proposes monitors as the core concurrency-construct.
    1313
    1414\section{Basics}
    15 Non-determinism requires concurrent systems to offer support for mutual-exclusion and synchronisation. Mutual-exclusion is the concept that only a fixed number of threads can access a critical section at any given time, where a critical section is a group of instructions on an associated portion of data that requires the restricted access. On the other hand, synchronization enforces relative ordering of execution and synchronization tools provide numerous mechanisms to establish timing relationships among threads.
     15Non-determinism requires concurrent systems to offer support for mutual-exclusion and synchronization. Mutual-exclusion is the concept that only a fixed number of threads can access a critical section at any given time, where a critical section is a group of instructions on an associated portion of data that requires the restricted access. On the other hand, synchronization enforces relative ordering of execution and synchronization tools provide numerous mechanisms to establish timing relationships among threads.
    1616
    1717\subsection{Mutual-Exclusion}
    18 As mentionned above, mutual-exclusion is the guarantee that only a fix number of threads can enter a critical section at once. However, many solutions exist for mutual exclusion, which vary in terms of performance, flexibility and ease of use. Methods range from low-level locks, which are fast and flexible but require significant attention to be correct, to  higher-level mutual-exclusion methods, which sacrifice some performance in order to improve ease of use. Ease of use comes by either guaranteeing some problems cannot occur (e.g., being deadlock free) or by offering a more explicit coupling between data and corresponding critical section. For example, the \CC \code{std::atomic<T>} offers an easy way to express mutual-exclusion on a restricted set of operations (e.g.: reading/writing large types atomically). Another challenge with low-level locks is composability. Locks have restricted composability because it takes careful organising for multiple locks to be used while preventing deadlocks. Easing composability is another feature higher-level mutual-exclusion mechanisms often offer.
     18As mentioned above, mutual-exclusion is the guarantee that only a fix number of threads can enter a critical section at once. However, many solutions exist for mutual exclusion, which vary in terms of performance, flexibility and ease of use. Methods range from low-level locks, which are fast and flexible but require significant attention to be correct, to  higher-level mutual-exclusion methods, which sacrifice some performance in order to improve ease of use. Ease of use comes by either guaranteeing some problems cannot occur (e.g., being deadlock free) or by offering a more explicit coupling between data and corresponding critical section. For example, the \CC \code{std::atomic<T>} offers an easy way to express mutual-exclusion on a restricted set of operations (e.g.: reading/writing large types atomically). Another challenge with low-level locks is composability. Locks have restricted composability because it takes careful organizing for multiple locks to be used while preventing deadlocks. Easing composability is another feature higher-level mutual-exclusion mechanisms often offer.
    1919
    2020\subsection{Synchronization}
    21 As for mutual-exclusion, low-level synchronisation primitives often offer good performance and good flexibility at the cost of ease of use. Again, higher-level mechanism often simplify usage by adding better coupling between synchronization and data, e.g.: message passing, or offering simpler solution to otherwise involved challenges. As mentioned above, synchronization can be expressed as guaranteeing that event \textit{X} always happens before \textit{Y}. Most of the time, synchronisation happens within a critical section, where threads must acquire mutual-exclusion in a certain order. However, it may also be desirable to guarantee that event \textit{Z} does not occur between \textit{X} and \textit{Y}. Not satisfying this property called barging. For example, where event \textit{X} tries to effect event \textit{Y} but another thread acquires the critical section and emits \textit{Z} before \textit{Y}. The classic exmaple is the thread that finishes using a ressource and unblocks a thread waiting to use the resource, but the unblocked thread must compete again to acquire the resource. Preventing or detecting barging is an involved challenge with low-level locks, which can be made much easier by higher-level constructs. This challenge is often split into two different methods, barging avoidance and barging prevention. Algorithms that use status flags and other flag variables to detect barging threads are said to be using barging avoidance while algorithms that baton-passing locks between threads instead of releasing the locks are said to be using barging prevention.
     21As for mutual-exclusion, low-level synchronization primitives often offer good performance and good flexibility at the cost of ease of use. Again, higher-level mechanism often simplify usage by adding better coupling between synchronization and data, e.g.: message passing, or offering a simpler solution to otherwise involved challenges. As mentioned above, synchronization can be expressed as guaranteeing that event \textit{X} always happens before \textit{Y}. Most of the time, synchronization happens within a critical section, where threads must acquire mutual-exclusion in a certain order. However, it may also be desirable to guarantee that event \textit{Z} does not occur between \textit{X} and \textit{Y}. Not satisfying this property is called barging. For example, where event \textit{X} tries to effect event \textit{Y} but another thread acquires the critical section and emits \textit{Z} before \textit{Y}. The classic example is the thread that finishes using a resource and unblocks a thread waiting to use the resource, but the unblocked thread must compete again to acquire the resource. Preventing or detecting barging is an involved challenge with low-level locks, which can be made much easier by higher-level constructs. This challenge is often split into two different methods, barging avoidance and barging prevention. Algorithms that use flag variables to detect barging threads are said to be using barging avoidance, while algorithms that baton-pass locks~\cite{Andrews89} between threads instead of releasing the locks are said to be using barging prevention.
    2222
    2323% ======================================================================
     
    2929\begin{cfacode}
    3030typedef /*some monitor type*/ monitor;
    31 int f(monitor & m);
     31int f(monitor& m);
    3232
    3333int main() {
     
    4242% ======================================================================
    4343% ======================================================================
    44 The above monitor example displays some of the intrinsic characteristics. First, it is necessary to use pass-by-reference over pass-by-value for monitor routines. This semantics is important because at their core, monitors are implicit mutual-exclusion objects (locks), and these objects cannot be copied. Therefore, monitors are implicitly non-copyable objects.
     44The above monitor example displays some of the intrinsic characteristics. First, it is necessary to use pass-by-reference over pass-by-value for monitor routines. This semantics is important, because at their core, monitors are implicit mutual-exclusion objects (locks), and these objects cannot be copied. Therefore, monitors are implicitly non-copy-able objects (\code{dtype}).
    4545
    4646Another aspect to consider is when a monitor acquires its mutual exclusion. For example, a monitor may need to be passed through multiple helper routines that do not acquire the monitor mutual-exclusion on entry. Pass through can occur for generic helper routines (\code{swap}, \code{sort}, etc.) or specific helper routines like the following to implement an atomic counter :
     
    7171\end{tabular}
    7272\end{center}
    73 Notice how the counter is used without any explicit synchronisation and yet supports thread-safe semantics for both reading and writting, which is similar in usage to \CC \code{atomic} template.
    74 
    75 Here, the constructor(\code{?\{\}}) uses the \code{nomutex} keyword to signify that it does not acquire the monitor mutual-exclusion when constructing. This semantics is because an object not yet con\-structed should never be shared and therefore does not require mutual exclusion. The prefix increment operator uses \code{mutex} to protect the incrementing process from race conditions. Finally, there is a conversion operator from \code{counter_t} to \code{size_t}. This conversion may or may not require the \code{mutex} keyword depending on whether or not reading a \code{size_t} is an atomic operation.
    76 
    77 For maximum usability, monitors use \gls{multi-acq} semantics, which means a single thread can acquire the same monitor multiple times without deadlock. For example, figure \ref{fig:search} uses recursion and \gls{multi-acq} to print values inside a binary tree.
     73Notice how the counter is used without any explicit synchronization and yet supports thread-safe semantics for both reading and writing, which is similar in usage to \CC \code{atomic} template.
     74
     75Here, the constructor (\code{?\{\}}) uses the \code{nomutex} keyword to signify that it does not acquire the monitor mutual-exclusion when constructing. This semantics is because an object not yet con\-structed should never be shared and therefore does not require mutual exclusion. Furthermore, it allows the implementation greater freedom when it initializes the monitor locking. The prefix increment operator uses \code{mutex} to protect the incrementing process from race conditions. Finally, there is a conversion operator from \code{counter_t} to \code{size_t}. This conversion may or may not require the \code{mutex} keyword depending on whether or not reading a \code{size_t} is an atomic operation.
     76
     77For maximum usability, monitors use \gls{multi-acq} semantics, which means a single thread can acquire the same monitor multiple times without deadlock. For example, listing \ref{fig:search} uses recursion and \gls{multi-acq} to print values inside a binary tree.
    7878\begin{figure}
    79 \label{fig:search}
    80 \begin{cfacode}
     79\begin{cfacode}[caption={Recursive printing algorithm using \gls{multi-acq}.},label={fig:search}]
    8180monitor printer { ... };
    8281struct tree {
     
    9291}
    9392\end{cfacode}
    94 \caption{Recursive printing algorithm using \gls{multi-acq}.}
    9593\end{figure}
    9694
    97 Having both \code{mutex} and \code{nomutex} keywords is redundant based on the meaning of a routine having neither of these keywords. For example, given a routine without qualifiers \code{void foo(counter_t & this)}, then it is reasonable that it should default to the safest option \code{mutex}, whereas assuming \code{nomutex} is unsafe and may cause subtle errors. In fact, \code{nomutex} is the ``normal'' parameter behaviour, with the \code{nomutex} keyword effectively stating explicitly that ``this routine is not special''. Another alternative is making exactly one of these keywords mandatory, which provides the same semantics but without the ambiguity of supporting routines with neither keyword. Mandatory keywords would also have the added benefit of being self-documented but at the cost of extra typing. While there are several benefits to mandatory keywords, they do bring a few challenges. Mandatory keywords in \CFA would imply that the compiler must know without doubt whether or not a parameter is a monitor or not. Since \CFA relies heavily on traits as an abstraction mechanism, the distinction between a type that is a monitor and a type that looks like a monitor can become blurred. For this reason, \CFA only has the \code{mutex} keyword and uses no keyword to mean \code{nomutex}.
     95Having both \code{mutex} and \code{nomutex} keywords is redundant based on the meaning of a routine having neither of these keywords. For example, it is reasonable that it should default to the safest option (\code{mutex}) when given a routine without qualifiers \code{void foo(counter_t & this)}, whereas assuming \code{nomutex} is unsafe and may cause subtle errors. On the other hand, \code{nomutex} is the ``normal'' parameter behaviour, it effectively states explicitly that ``this routine is not special''. Another alternative is making exactly one of these keywords mandatory, which provides the same semantics but without the ambiguity of supporting routines with neither keyword. Mandatory keywords would also have the added benefit of being self-documented but at the cost of extra typing. While there are several benefits to mandatory keywords, they do bring a few challenges. Mandatory keywords in \CFA would imply that the compiler must know without doubt whether or not a parameter is a monitor or not. Since \CFA relies heavily on traits as an abstraction mechanism, the distinction between a type that is a monitor and a type that looks like a monitor can become blurred. For this reason, \CFA only has the \code{mutex} keyword and uses no keyword to mean \code{nomutex}.
    9896
    9997The next semantic decision is to establish when \code{mutex} may be used as a type qualifier. Consider the following declarations:
    10098\begin{cfacode}
    101 int f1(monitor & mutex m);
     99int f1(monitor& mutex m);
    102100int f2(const monitor & mutex m);
    103 int f3(monitor ** mutex m);
    104 int f4(monitor * mutex m []);
     101int f3(monitor** mutex m);
     102int f4(monitor* mutex m []);
    105103int f5(graph(monitor*) & mutex m);
    106104\end{cfacode}
    107 The problem is to indentify which object(s) should be acquired. Furthermore, each object needs to be acquired only once. In the case of simple routines like \code{f1} and \code{f2} it is easy to identify an exhaustive list of objects to acquire on entry. Adding indirections (\code{f3}) still allows the compiler and programmer to indentify which object is acquired. However, adding in arrays (\code{f4}) makes it much harder. Array lengths are not necessarily known in C, and even then making sure objects are only acquired once becomes none-trivial. This problem can be extended to absurd limits like \code{f5}, which uses a graph of monitors. To make the issue tractable, this project imposes the requirement that a routine may only acquire one monitor per parameter and it must be the type of the parameter with at most one level of indirection (ignoring potential qualifiers). Also note that while routine \code{f3} can be supported, meaning that monitor \code{**m} is be acquired, passing an array to this routine would be type safe and yet result in undefined behavior because only the first element of the array is acquired. However, this ambiguity is part of the C type-system with respects to arrays. For this reason, \code{mutex} is disallowed in the context where arrays may be passed:
    108 \begin{cfacode}
    109 int f1(monitor & mutex m);   //Okay : recommanded case
    110 int f2(monitor * mutex m);   //Okay : could be an array but probably not
    111 int f3(monitor mutex m []);  //Not Okay : Array of unkown length
    112 int f4(monitor ** mutex m);  //Not Okay : Could be an array
    113 int f5(monitor * mutex m []); //Not Okay : Array of unkown length
     105The problem is to identify which object(s) should be acquired. Furthermore, each object needs to be acquired only once. In the case of simple routines like \code{f1} and \code{f2} it is easy to identify an exhaustive list of objects to acquire on entry. Adding indirections (\code{f3}) still allows the compiler and programmer to identify which object is acquired. However, adding in arrays (\code{f4}) makes it much harder. Array lengths are not necessarily known in C, and even then, making sure objects are only acquired once becomes none-trivial. This problem can be extended to absurd limits like \code{f5}, which uses a graph of monitors. To make the issue tractable, this project imposes the requirement that a routine may only acquire one monitor per parameter and it must be the type of the parameter with at most one level of indirection (ignoring potential qualifiers). Also note that while routine \code{f3} can be supported, meaning that monitor \code{**m} is be acquired, passing an array to this routine would be type safe and yet result in undefined behaviour because only the first element of the array is acquired. However, this ambiguity is part of the C type-system with respects to arrays. For this reason, \code{mutex} is disallowed in the context where arrays may be passed:
     106\begin{cfacode}
     107int f1(monitor& mutex m);   //Okay : recommended case
     108int f2(monitor* mutex m);   //Okay : could be an array but probably not
     109int f3(monitor mutex m []);  //Not Okay : Array of unknown length
     110int f4(monitor** mutex m);  //Not Okay : Could be an array
     111int f5(monitor* mutex m []); //Not Okay : Array of unknown length
    114112\end{cfacode}
    115113Note that not all array functions are actually distinct in the type system. However, even if the code generation could tell the difference, the extra information is still not sufficient to extend meaningfully the monitor call semantic.
     
    123121f(a,b);
    124122\end{cfacode}
    125 While OO monitors could be extended with a mutex qualifier for multiple-monitor calls, no example of this feature could be found. The capacity to acquire multiple locks before entering a critical section is called \emph{\gls{bulk-acq}}. In practice, writing multi-locking routines that do not lead to deadlocks is tricky. Having language support for such a feature is therefore a significant asset for \CFA. In the case presented above, \CFA guarantees that the order of aquisition is consistent across calls to different routines using the same monitors as arguments. This consistent ordering means acquiring multiple monitors in the way is safe from deadlock. However, users can still force the acquiring order. For example, notice which routines use \code{mutex}/\code{nomutex} and how this affects aquiring order:
    126 \begin{cfacode}
    127 void foo(A & mutex a, B & mutex b) { //acquire a & b
     123While OO monitors could be extended with a mutex qualifier for multiple-monitor calls, no example of this feature could be found. The capability to acquire multiple locks before entering a critical section is called \emph{\gls{bulk-acq}}. In practice, writing multi-locking routines that do not lead to deadlocks is tricky. Having language support for such a feature is therefore a significant asset for \CFA. In the case presented above, \CFA guarantees that the order of acquisition is consistent across calls to different routines using the same monitors as arguments. This consistent ordering means acquiring multiple monitors is safe from deadlock when using \gls{bulk-acq}. However, users can still force the acquiring order. For example, notice which routines use \code{mutex}/\code{nomutex} and how this affects acquiring order:
     124\begin{cfacode}
     125void foo(A& mutex a, B& mutex b) { //acquire a & b
    128126        ...
    129127}
    130128
    131 void bar(A & mutex a, B & /*nomutex*/ b) { //acquire a
     129void bar(A& mutex a, B& /*nomutex*/ b) { //acquire a
    132130        ... foo(a, b); ... //acquire b
    133131}
    134132
    135 void baz(A & /*nomutex*/ a, B & mutex b) { //acquire b
     133void baz(A& /*nomutex*/ a, B& mutex b) { //acquire b
    136134        ... foo(a, b); ... //acquire a
    137135}
     
    139137The \gls{multi-acq} monitor lock allows a monitor lock to be acquired by both \code{bar} or \code{baz} and acquired again in \code{foo}. In the calls to \code{bar} and \code{baz} the monitors are acquired in opposite order.
    140138
    141 However, such use leads to the lock acquiring order problem. In the example above, the user uses implicit ordering in the case of function \code{foo} but explicit ordering in the case of \code{bar} and \code{baz}. This subtle mistake means that calling these routines concurrently may lead to deadlock and is therefore undefined behavior. As shown\cite{Lister77}, solving this problem requires:
     139However, such use leads to the lock acquiring order problem. In the example above, the user uses implicit ordering in the case of function \code{foo} but explicit ordering in the case of \code{bar} and \code{baz}. This subtle difference means that calling these routines concurrently may lead to deadlock and is therefore Undefined Behavior. As shown~\cite{Lister77}, solving this problem requires:
    142140\begin{enumerate}
    143141        \item Dynamically tracking of the monitor-call order.
    144142        \item Implement rollback semantics.
    145143\end{enumerate}
    146 While the first requirement is already a significant constraint on the system, implementing a general rollback semantics in a C-like language is still prohibitively complex \cite{Dice10}. In \CFA, users simply need to be carefull when acquiring multiple monitors at the same time or only use \gls{bulk-acq} of all the monitors. While \CFA provides only a partial solution, many system provide no solution and the \CFA partial solution handles many useful cases.
     144While the first requirement is already a significant constraint on the system, implementing a general rollback semantics in a C-like language is still prohibitively complex~\cite{Dice10}. In \CFA, users simply need to be careful when acquiring multiple monitors at the same time or only use \gls{bulk-acq} of all the monitors. While \CFA provides only a partial solution, most systems provide no solution and the \CFA partial solution handles many useful cases.
    147145
    148146For example, \gls{multi-acq} and \gls{bulk-acq} can be used together in interesting ways:
     
    157155}
    158156\end{cfacode}
    159 This example shows a trivial solution to the bank-account transfer-problem\cite{BankTransfer}. Without \gls{multi-acq} and \gls{bulk-acq}, the solution to this problem is much more involved and requires carefull engineering.
     157This example shows a trivial solution to the bank-account transfer-problem~\cite{BankTransfer}. Without \gls{multi-acq} and \gls{bulk-acq}, the solution to this problem is much more involved and requires careful engineering.
    160158
    161159\subsection{\code{mutex} statement} \label{mutex-stmt}
    162160
    163 The call semantics discussed aboved have one software engineering issue, only a named routine can acquire the mutual-exclusion of a set of monitor. \CFA offers the \code{mutex} statement to workaround the need for unnecessary names, avoiding a major software engineering problem\cite{2FTwoHardThings}. Listing \ref{lst:mutex-stmt} shows an example of the \code{mutex} statement, which introduces a new scope in which the mutual-exclusion of a set of monitor is acquired. Beyond naming, the \code{mutex} statement has no semantic difference from a routine call with \code{mutex} parameters.
    164 
    165 \begin{figure}
     161The call semantics discussed above have one software engineering issue, only a named routine can acquire the mutual-exclusion of a set of monitor. \CFA offers the \code{mutex} statement to workaround the need for unnecessary names, avoiding a major software engineering problem~\cite{2FTwoHardThings}. Table \ref{lst:mutex-stmt} shows an example of the \code{mutex} statement, which introduces a new scope in which the mutual-exclusion of a set of monitor is acquired. Beyond naming, the \code{mutex} statement has no semantic difference from a routine call with \code{mutex} parameters.
     162
     163\begin{table}
    166164\begin{center}
    167165\begin{tabular}{|c|c|}
     
    170168\begin{cfacode}[tabsize=3]
    171169monitor M {};
    172 void foo( M & mutex m ) {
     170void foo( M & mutex m1, M & mutex m2 ) {
    173171        //critical section
    174172}
    175173
    176 void bar( M & m ) {
    177         foo( m );
     174void bar( M & m1, M & m2 ) {
     175        foo( m1, m2 );
    178176}
    179177\end{cfacode}&\begin{cfacode}[tabsize=3]
    180178monitor M {};
    181 void bar( M & m ) {
    182         mutex(m) {
     179void bar( M & m1, M & m2 ) {
     180        mutex(m1, m2) {
    183181                //critical section
    184182        }
     
    191189\caption{Regular call semantics vs. \code{mutex} statement}
    192190\label{lst:mutex-stmt}
    193 \end{figure}
     191\end{table}
    194192
    195193% ======================================================================
     
    225223};
    226224\end{cfacode}
    227 Note that the destructor of a monitor must be a \code{mutex} routine. This requirement ensures that the destructor has mutual-exclusion. As with any object, any call to a monitor, using \code{mutex} or otherwise, is Undefined Behaviour after the destructor has run.
     225Note that the destructor of a monitor must be a \code{mutex} routine to prevent deallocation while a thread is accessing the monitor. As with any object, calls to a monitor, using \code{mutex} or otherwise, is Undefined Behaviour after the destructor has run.
    228226
    229227% ======================================================================
     
    232230% ======================================================================
    233231% ======================================================================
    234 In addition to mutual exclusion, the monitors at the core of \CFA's concurrency can also be used to achieve synchronisation. With monitors, this capability is generally achieved with internal or external scheduling as in \cite{Hoare74}. Since internal scheduling within a single monitor is mostly a solved problem, this thesis concentrates on extending internal scheduling to multiple monitors. Indeed, like the \gls{bulk-acq} semantics, internal scheduling extends to multiple monitors in a way that is natural to the user but requires additional complexity on the implementation side.
    235 
    236 First, here is a simple example of such a technique:
     232In addition to mutual exclusion, the monitors at the core of \CFA's concurrency can also be used to achieve synchronization. With monitors, this capability is generally achieved with internal or external scheduling as in~\cite{Hoare74}. Since internal scheduling within a single monitor is mostly a solved problem, this thesis concentrates on extending internal scheduling to multiple monitors. Indeed, like the \gls{bulk-acq} semantics, internal scheduling extends to multiple monitors in a way that is natural to the user but requires additional complexity on the implementation side.
     233
     234First, here is a simple example of internal-scheduling :
    237235
    238236\begin{cfacode}
     
    241239}
    242240
    243 void foo(A & mutex a) {
     241void foo(A& mutex a1, A& mutex a2) {
    244242        ...
    245243        //Wait for cooperation from bar()
    246         wait(a.e);
     244        wait(a1.e);
    247245        ...
    248246}
    249247
    250 void bar(A & mutex a) {
     248void bar(A& mutex a1, A& mutex a2) {
    251249        //Provide cooperation for foo()
    252250        ...
    253251        //Unblock foo
    254         signal(a.e);
    255 }
    256 \end{cfacode}
    257 
    258 There are two details to note here. First, the \code{signal} is a delayed operation, it only unblocks the waiting thread when it reaches the end of the critical section. This semantic is needed to respect mutual-exclusion. The alternative is to return immediately after the call to \code{signal}, which is significantly more restrictive. Second, in \CFA, while it is common to store a \code{condition} as a field of the monitor, a \code{condition} variable can be stored/created independently of a monitor. Here routine \code{foo} waits for the \code{signal} from \code{bar} before making further progress, effectively ensuring a basic ordering.
    259 
    260 An important aspect of the implementation is that \CFA does not allow barging, which means that once function \code{bar} releases the monitor, \code{foo} is guaranteed to resume immediately after (unless some other thread waited on the same condition). This guarantees offers the benefit of not having to loop arount waits in order to guarantee that a condition is still met. The main reason \CFA offers this guarantee is that users can easily introduce barging if it becomes a necessity but adding barging prevention or barging avoidance is more involved without language support. Supporting barging prevention as well as extending internal scheduling to multiple monitors is the main source of complexity in the design of \CFA concurrency.
     252        signal(a1.e);
     253}
     254\end{cfacode}
     255There are two details to note here. First, the \code{signal} is a delayed operation, it only unblocks the waiting thread when it reaches the end of the critical section. This semantic is needed to respect mutual-exclusion, i.e., the signaller and signalled thread cannot be in the monitor simultaneously. The alternative is to return immediately after the call to \code{signal}, which is significantly more restrictive. Second, in \CFA, while it is common to store a \code{condition} as a field of the monitor, a \code{condition} variable can be stored/created independently of a monitor. Here routine \code{foo} waits for the \code{signal} from \code{bar} before making further progress, effectively ensuring a basic ordering.
     256
     257An important aspect of the implementation is that \CFA does not allow barging, which means that once function \code{bar} releases the monitor, \code{foo} is guaranteed to resume immediately after (unless some other thread waited on the same condition). This guarantee offers the benefit of not having to loop around waits to recheck that a condition is met. The main reason \CFA offers this guarantee is that users can easily introduce barging if it becomes a necessity but adding barging prevention or barging avoidance is more involved without language support. Supporting barging prevention as well as extending internal scheduling to multiple monitors is the main source of complexity in the design of \CFA concurrency.
    261258
    262259% ======================================================================
     
    265262% ======================================================================
    266263% ======================================================================
    267 It is easier to understand the problem of multi-monitor scheduling using a series of pseudo-code. Note that for simplicity in the following snippets of pseudo-code, waiting and signalling is done using an implicit condition variable, like Java built-in monitors. Indeed, \code{wait} statements always use the implicit condition as paremeter and explicitly names the monitors (A and B) associated with the condition. Note that in \CFA, condition variables are tied to a set of monitors on first use (called branding) which means that using internal scheduling with distinct sets of monitors requires one condition variable per set of monitors.
     264It is easier to understand the problem of multi-monitor scheduling using a series of pseudo-code examples. Note that for simplicity in the following snippets of pseudo-code, waiting and signalling is done using an implicit condition variable, like Java built-in monitors. Indeed, \code{wait} statements always use the implicit condition variable as parameter and explicitly names the monitors (A and B) associated with the condition. Note that in \CFA, condition variables are tied to a \emph{group} of monitors on first use (called branding), which means that using internal scheduling with distinct sets of monitors requires one condition variable per set of monitors. The example below shows the simple case of having two threads (one for each column) and a single monitor A.
    268265
    269266\begin{multicols}{2}
     
    284281\end{pseudo}
    285282\end{multicols}
    286 The example shows the simple case of having two threads (one for each column) and a single monitor A. One thread acquires before waiting (atomically blocking and releasing A) and the other acquires before signalling. It is important to note here that both \code{wait} and \code{signal} must be called with the proper monitor(s) already acquired. This semantic is a logical requirement for barging prevention.
     283One thread acquires before waiting (atomically blocking and releasing A) and the other acquires before signalling. It is important to note here that both \code{wait} and \code{signal} must be called with the proper monitor(s) already acquired. This semantic is a logical requirement for barging prevention.
    287284
    288285A direct extension of the previous example is a \gls{bulk-acq} version:
    289 
    290286\begin{multicols}{2}
    291287\begin{pseudo}
     
    294290release A & B
    295291\end{pseudo}
    296 
    297292\columnbreak
    298 
    299293\begin{pseudo}
    300294acquire A & B
     
    305299This version uses \gls{bulk-acq} (denoted using the {\sf\&} symbol), but the presence of multiple monitors does not add a particularly new meaning. Synchronization happens between the two threads in exactly the same way and order. The only difference is that mutual exclusion covers more monitors. On the implementation side, handling multiple monitors does add a degree of complexity as the next few examples demonstrate.
    306300
    307 While deadlock issues can occur when nesting monitors, these issues are only a symptom of the fact that locks, and by extension monitors, are not perfectly composable. For monitors, a well known deadlock problem is the Nested Monitor Problem \cite{Lister77}, which occurs when a \code{wait} is made by a thread that holds more than one monitor. For example, the following pseudo-code runs into the nested-monitor problem :
     301While deadlock issues can occur when nesting monitors, these issues are only a symptom of the fact that locks, and by extension monitors, are not perfectly composable. For monitors, a well known deadlock problem is the Nested Monitor Problem~\cite{Lister77}, which occurs when a \code{wait} is made by a thread that holds more than one monitor. For example, the following pseudo-code runs into the nested-monitor problem :
    308302\begin{multicols}{2}
    309303\begin{pseudo}
     
    325319\end{pseudo}
    326320\end{multicols}
    327 
    328 The \code{wait} only releases monitor \code{B} so the signalling thread cannot acquire monitor \code{A} to get to the \code{signal}. Attempting release of all acquired monitors at the \code{wait} results in another set of problems such as releasing monitor \code{C}, which has nothing to do with the \code{signal}.
    329 
    330 However, for monitors as for locks, it is possible to write a program using nesting without encountering any problems if nesting is done correctly. For example, the next pseudo-code snippet acquires monitors {\sf A} then {\sf B} before waiting, while only acquiring {\sf B} when signalling, effectively avoiding the nested monitor problem.
     321The \code{wait} only releases monitor \code{B} so the signalling thread cannot acquire monitor \code{A} to get to the \code{signal}. Attempting release of all acquired monitors at the \code{wait} introduces a different set of problems, such as releasing monitor \code{C}, which has nothing to do with the \code{signal}.
     322
     323However, for monitors as for locks, it is possible to write a program using nesting without encountering any problems if nesting is done correctly. For example, the next pseudo-code snippet acquires monitors {\sf A} then {\sf B} before waiting, while only acquiring {\sf B} when signalling, effectively avoiding the Nested Monitor Problem~\cite{Lister77}.
    331324
    332325\begin{multicols}{2}
     
    350343\end{multicols}
    351344
     345This simple refactoring may not be possible, forcing more complex restructuring.
     346
    352347% ======================================================================
    353348% ======================================================================
     
    356351% ======================================================================
    357352
    358 A larger example is presented to show complex issuesfor \gls{bulk-acq} and all the implementation options are analyzed. Listing \ref{lst:int-bulk-pseudo} shows an example where \gls{bulk-acq} adds a significant layer of complexity to the internal signalling semantics, and listing \ref{lst:int-bulk-cfa} shows the corresponding \CFA code which implements the pseudo-code in listing \ref{lst:int-bulk-pseudo}. For the purpose of translating the given pseudo-code into \CFA-code any method of introducing monitor into context, other than a \code{mutex} parameter, is acceptable, e.g., global variables, pointer parameters or using locals with the \code{mutex}-statement.
    359 
    360 \begin{figure}[!b]
     353A larger example is presented to show complex issues for \gls{bulk-acq} and all the implementation options are analyzed. Listing \ref{lst:int-bulk-pseudo} shows an example where \gls{bulk-acq} adds a significant layer of complexity to the internal signalling semantics, and listing \ref{lst:int-bulk-cfa} shows the corresponding \CFA code to implement the pseudo-code in listing \ref{lst:int-bulk-pseudo}. For the purpose of translating the given pseudo-code into \CFA-code, any method of introducing a monitor is acceptable, e.g., \code{mutex} parameter, global variables, pointer parameters or using locals with the \code{mutex}-statement.
     354
     355\begin{figure}[!t]
    361356\begin{multicols}{2}
    362357Waiting thread
     
    372367release A
    373368\end{pseudo}
    374 
    375369\columnbreak
    376 
    377370Signalling thread
    378 \begin{pseudo}[numbers=left, firstnumber=10]
     371\begin{pseudo}[numbers=left, firstnumber=10,escapechar=|]
    379372acquire A
    380373        //Code Section 5
    381374        acquire A & B
    382375                //Code Section 6
    383                 signal A & B
     376                |\label{line:signal1}|signal A & B
    384377                //Code Section 7
    385378        release A & B
    386379        //Code Section 8
    387 release A
     380|\label{line:lastRelease}|release A
    388381\end{pseudo}
    389382\end{multicols}
    390 \caption{Internal scheduling with \gls{bulk-acq}}
    391 \label{lst:int-bulk-pseudo}
    392 \end{figure}
    393 
    394 \begin{figure}[!b]
     383\begin{cfacode}[caption={Internal scheduling with \gls{bulk-acq}},label={lst:int-bulk-pseudo}]
     384\end{cfacode}
    395385\begin{center}
    396386\begin{cfacode}[xleftmargin=.4\textwidth]
     
    413403}
    414404\end{cfacode}
    415 
    416405\columnbreak
    417 
    418406Signalling thread
    419407\begin{cfacode}
     
    429417\end{cfacode}
    430418\end{multicols}
    431 \caption{Equivalent \CFA code for listing \ref{lst:int-bulk-pseudo}}
    432 \label{lst:int-bulk-cfa}
    433 \end{figure}
    434 
    435 The complexity begins at code sections 4 and 8, which are where the existing semantics of internal scheduling need to be extended for multiple monitors. The root of the problem is that \gls{bulk-acq} is used in a context where one of the monitors is already acquired and is why it is important to define the behaviour of the previous pseudo-code. When the signaller thread reaches the location where it should ``release \code{A & B}'' (line 16), it must actually transfer ownership of monitor \code{B} to the waiting thread. This ownership trasnfer is required in order to prevent barging. Since the signalling thread still needs monitor \code{A}, simply waking up the waiting thread is not an option because it violates mutual exclusion. There are three options.
    436 
    437 \subsubsection{Delaying signals}
    438 The obvious solution to solve the problem of multi-monitor scheduling is to keep ownership of all locks until the last lock is ready to be transferred. It can be argued that that moment is when the last lock is no longer needed because this semantics fits most closely to the behaviour of single-monitor scheduling. This solution has the main benefit of transferring ownership of groups of monitors, which simplifies the semantics from mutiple objects to a single group of objects, effectively making the existing single-monitor semantic viable by simply changing monitors to monitor groups.
     419\begin{cfacode}[caption={Equivalent \CFA code for listing \ref{lst:int-bulk-pseudo}},label={lst:int-bulk-cfa}]
     420\end{cfacode}
    439421\begin{multicols}{2}
    440422Waiter
     
    450432
    451433Signaller
    452 \begin{pseudo}[numbers=left, firstnumber=6]
     434\begin{pseudo}[numbers=left, firstnumber=6,escapechar=|]
    453435acquire A
    454436        acquire A & B
    455437                signal A & B
    456438        release A & B
    457         //Secretly keep B here
     439        |\label{line:secret}|//Secretly keep B here
    458440release A
    459441//Wakeup waiter and transfer A & B
    460442\end{pseudo}
    461443\end{multicols}
    462 However, this solution can become much more complicated depending on what is executed while secretly holding B (at line 10). Indeed, nothing prevents signalling monitor A on a different condition variable:
     444\begin{cfacode}[caption={Listing \ref{lst:int-bulk-pseudo}, with delayed signalling comments},label={lst:int-secret}]
     445\end{cfacode}
     446\end{figure}
     447
     448The complexity begins at code sections 4 and 8, which are where the existing semantics of internal scheduling need to be extended for multiple monitors. The root of the problem is that \gls{bulk-acq} is used in a context where one of the monitors is already acquired and is why it is important to define the behaviour of the previous pseudo-code. When the signaller thread reaches the location where it should ``release \code{A & B}'' (listing \ref{lst:int-bulk-pseudo} line \ref{line:signal1}), it must actually transfer ownership of monitor \code{B} to the waiting thread. This ownership transfer is required in order to prevent barging into \code{B} by another thread, since both the signalling and signalled threads still need monitor \code{A}. There are three options.
     449
     450\subsubsection{Delaying signals}
     451The obvious solution to solve the problem of multi-monitor scheduling is to keep ownership of all locks until the last lock is ready to be transferred. It can be argued that that moment is when the last lock is no longer needed because this semantics fits most closely to the behaviour of single-monitor scheduling. This solution has the main benefit of transferring ownership of groups of monitors, which simplifies the semantics from multiple objects to a single group of objects, effectively making the existing single-monitor semantic viable by simply changing monitors to monitor groups. The naive approach to this solution is to only release monitors once every monitor in a group can be released. However, since some monitors are never released (i.e., the monitor of a thread), this interpretation means groups can grow but may never shrink. A more interesting interpretation is to only transfer groups as one but to recreate the groups on every operation, i.e., limit ownership transfer to one per \code{signal}/\code{release}.
     452
     453However, this solution can become much more complicated depending on what is executed while secretly holding B (listing \ref{lst:int-secret} line \ref{line:secret}).
     454The goal in this solution is to avoid the need to transfer ownership of a subset of the condition monitors. However, listing \ref{lst:dependency} shows a slightly different example where a third thread is waiting on monitor \code{A}, using a different condition variable. Because the third thread is signalled when secretly holding \code{B}, the goal  becomes unreachable. Depending on the order of signals (listing \ref{lst:dependency} line \ref{line:signal-ab} and \ref{line:signal-a}) two cases can happen :
     455
     456\paragraph{Case 1: thread $\alpha$ goes first.} In this case, the problem is that monitor \code{A} needs to be passed to thread $\beta$ when thread $\alpha$ is done with it.
     457\paragraph{Case 2: thread $\beta$ goes first.} In this case, the problem is that monitor \code{B} needs to be retained and passed to thread $\alpha$ along with monitor \code{A}, which can be done directly or possibly using thread $\beta$ as an intermediate.
     458\\
     459
     460Note that ordering is not determined by a race condition but by whether signalled threads are enqueued in FIFO or FILO order. However, regardless of the answer, users can move line \ref{line:signal-a} before line \ref{line:signal-ab} and get the reverse effect for listing \ref{lst:dependency}.
     461
     462In both cases, the threads need to be able to distinguish, on a per monitor basis, which ones need to be released and which ones need to be transferred, which means monitors cannot be handled as a single homogeneous group and therefore effectively precludes this approach.
     463
     464\subsubsection{Dependency graphs}
     465
     466
    463467\begin{figure}
    464468\begin{multicols}{3}
     
    471475release A
    472476\end{pseudo}
    473 
    474477\columnbreak
    475 
    476478Thread $\gamma$
    477 \begin{pseudo}[numbers=left, firstnumber=1]
     479\begin{pseudo}[numbers=left, firstnumber=6, escapechar=|]
    478480acquire A
    479481        acquire A & B
    480                 signal A & B
    481         release A & B
    482         signal A
    483 release A
    484 \end{pseudo}
    485 
     482                |\label{line:signal-ab}|signal A & B
     483        |\label{line:release-ab}|release A & B
     484        |\label{line:signal-a}|signal A
     485|\label{line:release-a}|release A
     486\end{pseudo}
    486487\columnbreak
    487 
    488488Thread $\beta$
    489 \begin{pseudo}[numbers=left, firstnumber=1]
     489\begin{pseudo}[numbers=left, firstnumber=12, escapechar=|]
    490490acquire A
    491491        wait A
    492 release A
    493 \end{pseudo}
    494 
     492|\label{line:release-aa}|release A
     493\end{pseudo}
    495494\end{multicols}
    496 \caption{Dependency graph}
    497 \label{lst:dependency}
    498 \end{figure}
    499 
    500 The goal in this solution is to avoid the need to transfer ownership of a subset of the condition monitors. However, this goal is unreacheable in the previous example. Depending on the order of signals (line 12 and 15) two cases can happen.
    501 
    502 \paragraph{Case 1: thread 1 goes first.} In this case, the problem is that monitor A needs to be passed to thread 2 when thread 1 is done with it.
    503 \paragraph{Case 2: thread 2 goes first.} In this case, the problem is that monitor B needs to be passed to thread 1, which can be done directly or using thread 2 as an intermediate.
    504 \\
    505 
    506 Note that ordering is not determined by a race condition but by whether signalled threads are enqueued in FIFO or FILO order. However, regardless of the answer, users can move line 15 before line 11 and get the reverse effect.
    507 
    508 In both cases, the threads need to be able to distinguish, on a per monitor basis, which ones need to be released and which ones need to be transferred, which means monitors cannot be handled as a single homogenous group and therefore effectively precludes this approach.
    509 
    510 \subsubsection{Dependency graphs}
    511 In the listing \ref{lst:int-bulk-pseudo} pseudo-code, there is a solution which statisfies both barging prevention and mutual exclusion. If ownership of both monitors is transferred to the waiter when the signaller releases \code{A & B} and then the waiter transfers back ownership of \code{A} when it releases it, then the problem is solved (\code{B} is no longer in use at this point). Dynamically finding the correct order is therefore the second possible solution. The problem it encounters is that it effectively boils down to resolving a dependency graph of ownership requirements. Here even the simplest of code snippets requires two transfers and it seems to increase in a manner closer to polynomial. For example, the following code, which is just a direct extension to three monitors, requires at least three ownership transfer and has multiple solutions:
    512 
    513 \begin{multicols}{2}
    514 \begin{pseudo}
    515 acquire A
    516         acquire B
    517                 acquire C
    518                         wait A & B & C
    519                 release C
    520         release B
    521 release A
    522 \end{pseudo}
    523 
    524 \columnbreak
    525 
    526 \begin{pseudo}
    527 acquire A
    528         acquire B
    529                 acquire C
    530                         signal A & B & C
    531                 release C
    532         release B
    533 release A
    534 \end{pseudo}
    535 \end{multicols}
    536 
    537 \begin{figure}
     495\begin{cfacode}[caption={Pseudo-code for the three thread example.},label={lst:dependency}]
     496\end{cfacode}
    538497\begin{center}
    539498\input{dependency}
     
    543502\end{figure}
    544503
    545 Listing \ref{lst:dependency} is the three thread example rewritten for dependency graphs. Figure \ref{fig:dependency} shows the corresponding dependency graph that results, where every node is a statement of one of the three threads, and the arrows the dependency of that statement (e.g., $\alpha1$ must happen before $\alpha2$). The extra challenge is that this dependency graph is effectively post-mortem, but the runtime system needs to be able to build and solve these graphs as the dependency unfolds. Resolving dependency graph being a complex and expensive endeavour, this solution is not the preffered one.
     504In the listing \ref{lst:int-bulk-pseudo} pseudo-code, there is a solution that satisfies both barging prevention and mutual exclusion. If ownership of both monitors is transferred to the waiter when the signaller releases \code{A & B} and then the waiter transfers back ownership of \code{A} back to the signaller when it releases it, then the problem is solved (\code{B} is no longer in use at this point). Dynamically finding the correct order is therefore the second possible solution. The problem is effectively resolving a dependency graph of ownership requirements. Here even the simplest of code snippets requires two transfers and it seems to increase in a manner close to polynomial. This complexity explosion can be seen in listing \ref{lst:explosion}, which is just a direct extension to three monitors, requires at least three ownership transfer and has multiple solutions. Furthermore, the presence of multiple solutions for ownership transfer can cause deadlock problems if a specific solution is not consistently picked; In the same way that multiple lock acquiring order can cause deadlocks.
     505\begin{figure}
     506\begin{multicols}{2}
     507\begin{pseudo}
     508acquire A
     509        acquire B
     510                acquire C
     511                        wait A & B & C
     512                release C
     513        release B
     514release A
     515\end{pseudo}
     516
     517\columnbreak
     518
     519\begin{pseudo}
     520acquire A
     521        acquire B
     522                acquire C
     523                        signal A & B & C
     524                release C
     525        release B
     526release A
     527\end{pseudo}
     528\end{multicols}
     529\begin{cfacode}[caption={Extension to three monitors of listing \ref{lst:int-bulk-pseudo}},label={lst:explosion}]
     530\end{cfacode}
     531\end{figure}
     532
     533Listing \ref{lst:dependency} is the three threads example used in the delayed signals solution. Figure \ref{fig:dependency} shows the corresponding dependency graph that results, where every node is a statement of one of the three threads, and the arrows the dependency of that statement (e.g., $\alpha1$ must happen before $\alpha2$). The extra challenge is that this dependency graph is effectively post-mortem, but the runtime system needs to be able to build and solve these graphs as the dependency unfolds. Resolving dependency graphs being a complex and expensive endeavour, this solution is not the preferred one.
    546534
    547535\subsubsection{Partial signalling} \label{partial-sig}
    548 Finally, the solution that is chosen for \CFA is to use partial signalling. Again using listing \ref{lst:int-bulk-pseudo}, the partial signalling solution transfers ownership of monitor B at lines 10 but does not wake the waiting thread since it is still using monitor A. Only when it reaches line 11 does it actually wakeup the waiting thread. This solution has the benefit that complexity is encapsulated into only two actions, passing monitors to the next owner when they should be release and conditionally waking threads if all conditions are met. This solution has a much simpler implementation than a dependency graph solving algorithm which is why it was chosen. Furthermore, after being fully implemented, this solution does not appear to have any downsides worth mentionning.
     536Finally, the solution that is chosen for \CFA is to use partial signalling. Again using listing \ref{lst:int-bulk-pseudo}, the partial signalling solution transfers ownership of monitor \code{B} at lines \ref{line:signal1} to the waiter but does not wake the waiting thread since it is still using monitor \code{A}. Only when it reaches line \ref{line:lastRelease} does it actually wakeup the waiting thread. This solution has the benefit that complexity is encapsulated into only two actions, passing monitors to the next owner when they should be released and conditionally waking threads if all conditions are met. This solution has a much simpler implementation than a dependency graph solving algorithm, which is why it was chosen. Furthermore, after being fully implemented, this solution does not appear to have any significant downsides.
     537
     538While listing \ref{lst:dependency} is a complicated problem for previous solutions, it can be solved easily with partial signalling :
     539\begin{itemize}
     540        \item When thread $\gamma$ reaches line \ref{line:release-ab} it transfers monitor \code{B} to thread $\alpha$ and continues to hold monitor \code{A}.
     541        \item When thread $\gamma$ reaches line \ref{line:release-a}  it transfers monitor \code{A} to thread $\beta$  and wakes it up.
     542        \item When thread $\beta$  reaches line \ref{line:release-aa} it transfers monitor \code{A} to thread $\alpha$ and wakes it up.
     543        \item Problem solved!
     544\end{itemize}
    549545
    550546% ======================================================================
     
    553549% ======================================================================
    554550% ======================================================================
    555 \begin{figure}
     551\begin{table}
    556552\begin{tabular}{|c|c|}
    557553\code{signal} & \code{signal_block} \\
     
    654650\end{tabular}
    655651\caption{Dating service example using \code{signal} and \code{signal_block}. }
    656 \label{lst:datingservice}
    657 \end{figure}
    658 An important note is that, until now, signalling a monitor was a delayed operation. The ownership of the monitor is transferred only when the monitor would have otherwise been released, not at the point of the \code{signal} statement. However, in some cases, it may be more convenient for users to immediately transfer ownership to the thread that is waiting for cooperation, which is achieved using the \code{signal_block} routine\footnote{name to be discussed}.
    659 
    660 The example in listing \ref{lst:datingservice} highlights the difference in behaviour. As mentioned, \code{signal} only transfers ownership once the current critical section exits, this behaviour requires additional synchronisation when a two-way handshake is needed. To avoid this extraneous synchronisation, the \code{condition} type offers the \code{signal_block} routine, which handles the two-way handshake as shown in the example. This removes the need for a second condition variables and simplifies programming. Like every other monitor semantic, \code{signal_block} uses barging prevention, which means mutual-exclusion is baton-passed both on the frond-end and the back-end of the call to \code{signal_block}, meaning no other thread can acquire the monitor neither before nor after the call.
     652\label{tbl:datingservice}
     653\end{table}
     654An important note is that, until now, signalling a monitor was a delayed operation. The ownership of the monitor is transferred only when the monitor would have otherwise been released, not at the point of the \code{signal} statement. However, in some cases, it may be more convenient for users to immediately transfer ownership to the thread that is waiting for cooperation, which is achieved using the \code{signal_block} routine.
     655
     656The example in table \ref{tbl:datingservice} highlights the difference in behaviour. As mentioned, \code{signal} only transfers ownership once the current critical section exits, this behaviour requires additional synchronization when a two-way handshake is needed. To avoid this explicit synchronization, the \code{condition} type offers the \code{signal_block} routine, which handles the two-way handshake as shown in the example. This feature removes the need for a second condition variables and simplifies programming. Like every other monitor semantic, \code{signal_block} uses barging prevention, which means mutual-exclusion is baton-passed both on the frond-end and the back-end of the call to \code{signal_block}, meaning no other thread can acquire the monitor either before or after the call.
    661657
    662658% ======================================================================
     
    727723\end{tabular}
    728724\end{center}
    729 This method is more constrained and explicit, which helps users tone down the undeterministic nature of concurrency. Indeed, as the following examples demonstrates, external scheduling allows users to wait for events from other threads without the concern of unrelated events occuring. External scheduling can generally be done either in terms of control flow (e.g., \uC with \code{_Accept}) or in terms of data (e.g., Go with channels). Of course, both of these paradigms have their own strenghts and weaknesses but for this project control-flow semantics were chosen to stay consistent with the rest of the languages semantics. Two challenges specific to \CFA arise when trying to add external scheduling with loose object definitions and multi-monitor routines. The previous example shows a simple use \code{_Accept} versus \code{wait}/\code{signal} and its advantages. Note that while other languages often use \code{accept}/\code{select} as the core external scheduling keyword, \CFA uses \code{waitfor} to prevent name collisions with existing socket \acrshort{api}s.
     725This method is more constrained and explicit, which helps users reduce the non-deterministic nature of concurrency. Indeed, as the following examples demonstrates, external scheduling allows users to wait for events from other threads without the concern of unrelated events occurring. External scheduling can generally be done either in terms of control flow (e.g., Ada with \code{accept}, \uC with \code{_Accept}) or in terms of data (e.g., Go with channels). Of course, both of these paradigms have their own strengths and weaknesses, but for this project control-flow semantics were chosen to stay consistent with the rest of the languages semantics. Two challenges specific to \CFA arise when trying to add external scheduling with loose object definitions and multiple-monitor routines. The previous example shows a simple use \code{_Accept} versus \code{wait}/\code{signal} and its advantages. Note that while other languages often use \code{accept}/\code{select} as the core external scheduling keyword, \CFA uses \code{waitfor} to prevent name collisions with existing socket \acrshort{api}s.
    730726
    731727For the \code{P} member above using internal scheduling, the call to \code{wait} only guarantees that \code{V} is the last routine to access the monitor, allowing a third routine, say \code{isInUse()}, acquire mutual exclusion several times while routine \code{P} is waiting. On the other hand, external scheduling guarantees that while routine \code{P} is waiting, no routine other than \code{V} can acquire the monitor.
     
    736732% ======================================================================
    737733% ======================================================================
    738 In \uC, monitor declarations include an exhaustive list of monitor operations. Since \CFA is not object oriented, monitors become both more difficult to implement and less clear for a user:
     734In \uC, a monitor class declaration includee an exhaustive list of monitor operations. Since \CFA is not object oriented, monitors become both more difficult to implement and less clear for a user:
    739735
    740736\begin{cfacode}
     
    752748\end{cfacode}
    753749
    754 Furthermore, external scheduling is an example where implementation constraints become visible from the interface. Indeed, since there is no hard limit to the number of threads trying to acquire a monitor concurrently, performance is a significant concern. Here is the pseudo code for the entering phase of a monitor:
    755 
     750Furthermore, external scheduling is an example where implementation constraints become visible from the interface. Here is the pseudo code for the entering phase of a monitor:
    756751\begin{center}
    757752\begin{tabular}{l}
     
    768763\end{tabular}
    769764\end{center}
    770 
    771765For the first two conditions, it is easy to implement a check that can evaluate the condition in a few instruction. However, a fast check for \pscode{monitor accepts me} is much harder to implement depending on the constraints put on the monitors. Indeed, monitors are often expressed as an entry queue and some acceptor queue as in the following figure:
    772766
     
    778772\end{figure}
    779773
    780 There are other alternatives to these pictures, but in the case of this picture, implementing a fast accept check is relatively easy. Restricted to a fixed number of mutex members, N, the accept check reduces to updating a bitmask when the acceptor queue changes, a check that executes in a single instruction even with a fairly large number (e.g., 128) of mutex members. This technique cannot be used in \CFA because it relies on the fact that the monitor type enumerates (declares) all the acceptable routines. For OO languages this does not compromise much since monitors already have an exhaustive list of member routines. However, for \CFA this is not the case; routines can be added to a type anywhere after its declaration. It is important to note that the bitmask approach does not actually require an exhaustive list of routines, but it requires a dense unique ordering of routines with an upper-bound and that ordering must be consistent across translation units.
    781 The alternative is to alter the implementeation like this:
     774There are other alternatives to these pictures, but in the case of this picture, implementing a fast accept check is relatively easy. Restricted to a fixed number of mutex members, N, the accept check reduces to updating a bitmask when the acceptor queue changes, a check that executes in a single instruction even with a fairly large number (e.g., 128) of mutex members. This approach requires a dense unique ordering of routines with an upper-bound and that ordering must be consistent across translation units. For OO languages these constraints are common, since objects only offer adding member routines consistently across translation units via inheritence. However, in \CFA users can extend objects with mutex routines that are only visible in certain translation unit. This means that establishing a program-wide dense-ordering among mutex routines can only be done in the program linking phase, and still could have issues when using dynamically shared objects.
     775
     776The alternative is to alter the implementation like this:
    782777
    783778\begin{center}
     
    785780\end{center}
    786781
    787 Generating a mask dynamically means that the storage for the mask information can vary between calls to \code{waitfor}, allowing for more flexibility and extensions. Storing an array of accepted function-pointers replaces the single instruction bitmask compare with dereferencing a pointer followed by a linear search. Furthermore, supporting nested external scheduling (e.g., listing \ref{lst:nest-ext}) may now require additionnal searches on calls to \code{waitfor} statement to check if a routine is already queued in.
     782Here, the mutex routine called is associated with a thread on the entry queue while a list of acceptable routines is kept seperately. Generating a mask dynamically means that the storage for the mask information can vary between calls to \code{waitfor}, allowing for more flexibility and extensions. Storing an array of accepted function-pointers replaces the single instruction bitmask compare with dereferencing a pointer followed by a linear search. Furthermore, supporting nested external scheduling (e.g., listing \ref{lst:nest-ext}) may now require additional searches for the \code{waitfor} statement to check if a routine is already queued.
    788783
    789784\begin{figure}
    790 \begin{cfacode}
     785\begin{cfacode}[caption={Example of nested external scheduling},label={lst:nest-ext}]
    791786monitor M {};
    792787void foo( M & mutex a ) {}
     
    800795
    801796\end{cfacode}
    802 \caption{Example of nested external scheduling}
    803 \label{lst:nest-ext}
    804797\end{figure}
    805798
    806 Note that in the second picture, tasks need to always keep track of which routine they are attempting to acquire the monitor and the routine mask needs to have both a function pointer and a set of monitors, as will be discussed in the next section. These details where omitted from the picture for the sake of simplifying the representation.
    807 
    808 At this point, a decision must be made between flexibility and performance. Many design decisions in \CFA achieve both flexibility and performance, for example polymorphic routines add significant flexibility but inlining them means the optimizer can easily remove any runtime cost. Here however, the cost of flexibility cannot be trivially removed. In the end, the most flexible approach has been chosen since it allows users to write programs that would otherwise be prohibitively hard to write. This decision is based on the assumption that writing fast but inflexible locks is closer to a solved problems than writing locks that are as flexible as external scheduling in \CFA.
     799Note that in the second picture, tasks need to always keep track of the monitors associated with mutex routines, and the routine mask needs to have both a function pointer and a set of monitors, as is be discussed in the next section. These details are omitted from the picture for the sake of simplicity.
     800
     801At this point, a decision must be made between flexibility and performance. Many design decisions in \CFA achieve both flexibility and performance, for example polymorphic routines add significant flexibility but inlining them means the optimizer can easily remove any runtime cost. Here however, the cost of flexibility cannot be trivially removed. In the end, the most flexible approach has been chosen since it allows users to write programs that would otherwise be hard to write. This decision is based on the assumption that writing fast but inflexible locks is closer to a solved problems than writing locks that are as flexible as external scheduling in \CFA.
    809802
    810803% ======================================================================
     
    821814
    822815void g(M & mutex b, M & mutex c) {
    823         waitfor(f); //two monitors M => unkown which to pass to f(M & mutex)
    824 }
    825 \end{cfacode}
    826 
     816        waitfor(f); //two monitors M => unknown which to pass to f(M & mutex)
     817}
     818\end{cfacode}
    827819The obvious solution is to specify the correct monitor as follows:
    828820
     
    833825
    834826void g(M & mutex a, M & mutex b) {
    835         waitfor( f, b );
    836 }
    837 \end{cfacode}
    838 
    839 This syntax is unambiguous. Both locks are acquired and kept by \code{g}. When routine \code{f} is called, the lock for monitor \code{b} is temporarily transferred from \code{g} to \code{f} (while \code{g} still holds lock \code{a}). This behavior can be extended to multi-monitor \code{waitfor} statement as follows.
     827        //wait for call to f with argument b
     828        waitfor(f, b);
     829}
     830\end{cfacode}
     831This syntax is unambiguous. Both locks are acquired and kept by \code{g}. When routine \code{f} is called, the lock for monitor \code{b} is temporarily transferred from \code{g} to \code{f} (while \code{g} still holds lock \code{a}). This behaviour can be extended to the multi-monitor \code{waitfor} statement as follows.
    840832
    841833\begin{cfacode}
     
    845837
    846838void g(M & mutex a, M & mutex b) {
    847         waitfor( f, a, b);
     839        //wait for call to f with argument a and b
     840        waitfor(f, a, b);
    848841}
    849842\end{cfacode}
     
    851844Note that the set of monitors passed to the \code{waitfor} statement must be entirely contained in the set of monitors already acquired in the routine. \code{waitfor} used in any other context is Undefined Behaviour.
    852845
    853 An important behavior to note is when a set of monitors only match partially :
     846An important behaviour to note is when a set of monitors only match partially :
    854847
    855848\begin{cfacode}
     
    870863
    871864void bar() {
    872         f(a2, b); //fufill cooperation
    873 }
    874 \end{cfacode}
    875 
    876 While the equivalent can happen when using internal scheduling, the fact that conditions are specific to a set of monitors means that users have to use two different condition variables. In both cases, partially matching monitor sets does not wake-up the waiting thread. It is also important to note that in the case of external scheduling, as for routine calls, the order of parameters is irrelevant; \code{waitfor(f,a,b)} and \code{waitfor(f,b,a)} are indistinguishable waiting condition.
     865        f(a2, b); //fulfill cooperation
     866}
     867\end{cfacode}
     868While the equivalent can happen when using internal scheduling, the fact that conditions are specific to a set of monitors means that users have to use two different condition variables. In both cases, partially matching monitor sets does not wake-up the waiting thread. It is also important to note that in the case of external scheduling the order of parameters is irrelevant; \code{waitfor(f,a,b)} and \code{waitfor(f,b,a)} are indistinguishable waiting condition.
    877869
    878870% ======================================================================
     
    882874% ======================================================================
    883875
    884 Syntactically, the \code{waitfor} statement takes a function identifier and a set of monitors. While the set of monitors can be any list of expression, the function name is more restricted because the compiler validates at compile time the validity of the function type and the parameters used with the \code{waitfor} statement. It checks that the set of monitor passed in matches the requirements for a function call. Listing \ref{lst:waitfor} shows various usage of the waitfor statement and which are acceptable. The choice of the function type is made ignoring any non-\code{mutex} parameter. One limitation of the current implementation is that it does not handle overloading.
     876Syntactically, the \code{waitfor} statement takes a function identifier and a set of monitors. While the set of monitors can be any list of expression, the function name is more restricted because the compiler validates at compile time the validity of the function type and the parameters used with the \code{waitfor} statement. It checks that the set of monitors passed in matches the requirements for a function call. Listing \ref{lst:waitfor} shows various usage of the waitfor statement and which are acceptable. The choice of the function type is made ignoring any non-\code{mutex} parameter. One limitation of the current implementation is that it does not handle overloading but overloading is possible.
    885877\begin{figure}
    886 \begin{cfacode}
     878\begin{cfacode}[caption={Various correct and incorrect uses of the waitfor statement},label={lst:waitfor}]
    887879monitor A{};
    888880monitor B{};
     
    911903        waitfor(f4, a1);     //Incorrect : f4 ambiguous
    912904
    913         waitfor(f2, a1, b2); //Undefined Behaviour : b2 may not acquired
    914 }
    915 \end{cfacode}
    916 \caption{Various correct and incorrect uses of the waitfor statement}
    917 \label{lst:waitfor}
     905        waitfor(f2, a1, b2); //Undefined Behaviour : b2 not mutex
     906}
     907\end{cfacode}
    918908\end{figure}
    919909
    920 Finally, for added flexibility, \CFA supports constructing complex \code{waitfor} mask using the \code{or}, \code{timeout} and \code{else}. Indeed, multiple \code{waitfor} can be chained together using \code{or}; this chain forms a single statement that uses baton-pass to any one function that fits one of the function+monitor set passed in. To eanble users to tell which accepted function is accepted, \code{waitfor}s are followed by a statement (including the null statement \code{;}) or a compound statement. When multiple \code{waitfor} are chained together, only the statement corresponding to the accepted function is executed. A \code{waitfor} chain can also be followed by a \code{timeout}, to signify an upper bound on the wait, or an \code{else}, to signify that the call should be non-blocking, that is only check of a matching function call already arrived and return immediately otherwise. Any and all of these clauses can be preceded by a \code{when} condition to dynamically construct the mask based on some current state. Listing \ref{lst:waitfor2}, demonstrates several complex masks and some incorrect ones.
     910Finally, for added flexibility, \CFA supports constructing a complex \code{waitfor} statement using the \code{or}, \code{timeout} and \code{else}. Indeed, multiple \code{waitfor} clauses can be chained together using \code{or}; this chain forms a single statement that uses baton-pass to any one function that fits one of the function+monitor set passed in. To enable users to tell which accepted function executed, \code{waitfor}s are followed by a statement (including the null statement \code{;}) or a compound statement, which is executed after the clause is triggered. A \code{waitfor} chain can also be followed by a \code{timeout}, to signify an upper bound on the wait, or an \code{else}, to signify that the call should be non-blocking, which checks for a matching function call already arrived and otherwise continues. Any and all of these clauses can be preceded by a \code{when} condition to dynamically toggle the accept clauses on or off based on some current state. Listing \ref{lst:waitfor2}, demonstrates several complex masks and some incorrect ones.
    921911
    922912\begin{figure}
    923 \begin{cfacode}
     913\begin{cfacode}[caption={Various correct and incorrect uses of the or, else, and timeout clause around a waitfor statement},label={lst:waitfor2}]
    924914monitor A{};
    925915
     
    979969}
    980970\end{cfacode}
    981 \caption{Various correct and incorrect uses of the or, else, and timeout clause around a waitfor statement}
    982 \label{lst:waitfor2}
    983971\end{figure}
    984972
     
    990978An interesting use for the \code{waitfor} statement is destructor semantics. Indeed, the \code{waitfor} statement can accept any \code{mutex} routine, which includes the destructor (see section \ref{data}). However, with the semantics discussed until now, waiting for the destructor does not make any sense since using an object after its destructor is called is undefined behaviour. The simplest approach is to disallow \code{waitfor} on a destructor. However, a more expressive approach is to flip execution ordering when waiting for the destructor, meaning that waiting for the destructor allows the destructor to run after the current \code{mutex} routine, similarly to how a condition is signalled.
    991979\begin{figure}
    992 \begin{cfacode}
     980\begin{cfacode}[caption={Example of an executor which executes action in series until the destructor is called.},label={lst:dtor-order}]
    993981monitor Executer {};
    994982struct  Action;
     
    1005993}
    1006994\end{cfacode}
    1007 \caption{Example of an executor which executes action in series until the destructor is called.}
    1008 \label{lst:dtor-order}
    1009995\end{figure}
    1010996For example, listing \ref{lst:dtor-order} shows an example of an executor with an infinite loop, which waits for the destructor to break out of this loop. Switching the semantic meaning introduces an idiomatic way to terminate a task and/or wait for its termination via destruction.
  • doc/proposals/concurrency/text/future.tex

    r875a72f r35bae526  
     1
     2\chapter{Conclusion}
     3As mentionned in the introduction, this thesis provides a minimal concurrency \acrshort{api} that is simple, efficient and usable as the basis for higher-level features. The approach presented is based on a lighweight thread system for parallelism which sits on top of clusters of processors. This M:N model is jugded to be both more efficient and allow more flexibility for users. Furthermore, this document introduces monitors as the main concurrency tool for users. This thesis also offers a novel approach which allows using multiple monitors at once without running into the Nested Monitor Problem~\cite{Lister77}. It also offers a full implmentation of the concurrency runtime wirtten enterily in \CFA, effectively the largest \CFA code base to date.
     4
     5
    16% ======================================================================
    27% ======================================================================
    3 \chapter{Future Work}
     8\section{Future Work}
    49% ======================================================================
    510% ======================================================================
    611
    7 \section{Flexible Scheduling} \label{futur:sched}
    8 An important part of concurrency is scheduling. Different scheduling algorithm can affact peformance (both in terms of average and variation). However, no single scheduler is optimal for all workloads and therefore there is value in being able to change the scheduler for given programs. One solution is to offer various tweaking options to users, allowing the scheduler to be adjusted the to requirements of the workload. However, in order to be truly flexible, it would be interesting to allow users to add arbitrary data and arbirary scheduling algorithms to the scheduler. For example, a web server could attach Type-of-Service information to threads and have a ``ToS aware'' scheduling algorithm tailored to this specific web server. This path of flexible schedulers will be explored for \CFA.
     12\subsection{Performance} \label{futur:perf}
     13This thesis presents a first implementation of the \CFA runtime. Therefore, there is still significant work to do to improve performance. Many of the data structures and algorithms will change in the future to more efficient versions. For example, \CFA the number of monitors in a single \gls{bulk-acq} is only bound by the stack size, this is probably unnecessarily generous. It may be possible that limiting the number help increase performance. However, it is not obvious that the benefit would be significant.
    914
    10 \section{Non-Blocking IO} \label{futur:nbio}
    11 While most of the parallelism tools
    12 However, many modern workloads are not bound on computation but on IO operations, an common case being webservers and XaaS (anything as a service). These type of workloads often require significant engineering around amortising costs of blocking IO operations. While improving throughtput of these operations is outside what \CFA can do as a language, it can help users to make better use of the CPU time otherwise spent waiting on IO operations. The current trend is to use asynchronous programming using tools like callbacks and/or futurs and promises\cite. However, while these are valid solutions, they lead to code that is harder to read and maintain because it is much less linear
     15\subsection{Flexible Scheduling} \label{futur:sched}
     16An important part of concurrency is scheduling. Different scheduling algorithm can affect performance (both in terms of average and variation). However, no single scheduler is optimal for all workloads and therefore there is value in being able to change the scheduler for given programs. One solution is to offer various tweaking options to users, allowing the scheduler to be adjusted to the requirements of the workload. However, in order to be truly flexible, it would be interesting to allow users to add arbitrary data and arbitrary scheduling algorithms to the scheduler. For example, a web server could attach Type-of-Service information to threads and have a ``ToS aware'' scheduling algorithm tailored to this specific web server. This path of flexible schedulers will be explored for \CFA.
    1317
    14 \section{Other concurrency tools} \label{futur:tools}
    15 While monitors offer a flexible and powerful concurent core for \CFA, other concurrency tools are also necessary for a complete multi-paradigm concurrency package. Example of such tools can include simple locks and condition variables, futures and promises\cite{promises}, and executors. These additional features are useful when monitors offer a level of abstraction which is indaquate for certain tasks.
     18\subsection{Non-Blocking IO} \label{futur:nbio}
     19While most of the parallelism tools are aimed at data parallelism and control-flow parallelism, many modern workloads are not bound on computation but on IO operations, a common case being web-servers and XaaS (anything as a service). These type of workloads often require significant engineering around amortizing costs of blocking IO operations. At its core, Non-Blocking IO is a operating system level feature that allows queuing IO operations (e.g., network operations) and registering for notifications instead of waiting for requests to complete. In this context, the role of the language make Non-Blocking IO easily available and with low overhead. The current trend is to use asynchronous programming using tools like callbacks and/or futures and promises, which can be seen in frameworks like Node.js~\cite{NodeJs} for JavaScript, Spring MVC~\cite{SpringMVC} for Java and Django~\cite{Django} for Python. However, while these are valid solutions, they lead to code that is harder to read and maintain because it is much less linear.
    1620
    17 \section{Implicit threading} \label{futur:implcit}
    18 Simpler applications can benefit greatly from having implicit parallelism. That is, parallelism that does not rely on the user to write concurrency. This type of parallelism can be achieved both at the language level and at the library level. The cannonical example of implcit parallelism is parallel for loops, which are the simplest example of a divide and conquer algorithm\cite{uC++book}. Listing \ref{lst:parfor} shows three different code examples that accomplish pointwise sums of large arrays. Note that none of these example explicitly declare any concurrency or parallelism objects.
     21\subsection{Other concurrency tools} \label{futur:tools}
     22While monitors offer a flexible and powerful concurrent core for \CFA, other concurrency tools are also necessary for a complete multi-paradigm concurrency package. Example of such tools can include simple locks and condition variables, futures and promises~\cite{promises}, executors and actors. These additional features are useful when monitors offer a level of abstraction that is inadequate for certain tasks.
    1923
    20 \begin{figure}
     24\subsection{Implicit threading} \label{futur:implcit}
     25Simpler applications can benefit greatly from having implicit parallelism. That is, parallelism that does not rely on the user to write concurrency. This type of parallelism can be achieved both at the language level and at the library level. The canonical example of implicit parallelism is parallel for loops, which are the simplest example of a divide and conquer algorithm~\cite{uC++book}. Table \ref{lst:parfor} shows three different code examples that accomplish point-wise sums of large arrays. Note that none of these examples explicitly declare any concurrency or parallelism objects.
     26
     27\begin{table}
    2128\begin{center}
    2229\begin{tabular}[t]{|c|c|c|}
     
    99106\caption{For loop to sum numbers: Sequential, using library parallelism and language parallelism.}
    100107\label{lst:parfor}
    101 \end{figure}
     108\end{table}
    102109
    103 Implicit parallelism is a general solution and therefore has its limitations. However, it is a quick and simple approach to parallelism which may very well be sufficient for smaller applications and reduces the amount of boiler-plate that is needed to start benefiting from parallelism in modern CPUs.
     110Implicit parallelism is a restrictive solution and therefore has its limitations. However, it is a quick and simple approach to parallelism, which may very well be sufficient for smaller applications and reduces the amount of boiler-plate needed to start benefiting from parallelism in modern CPUs.
    104111
    105112
  • doc/proposals/concurrency/text/internals.tex

    r875a72f r35bae526  
    11
    22\chapter{Behind the scene}
    3 There are several challenges specific to \CFA when implementing concurrency. These challenges are a direct result of \gls{bulk-acq} and loose object-definitions. These two constraints are the root cause of most design decisions in the implementation. Furthermore, to avoid contention from dynamically allocating memory in a concurrent environment, the internal-scheduling design is (almost) entirely free of mallocs. This is to avoid the chicken and egg problem \cite{Chicken} of having a memory allocator that relies on the threading system and a threading system that relies on the runtime. This extra goal, means that memory management is a constant concern in the design of the system.
    4 
    5 The main memory concern for concurrency is queues. All blocking operations are made by parking threads onto queues. The queue design needs to be intrusive\cite{IntrusiveData} to avoid the need for memory allocation, which entails that all the nodes need specific fields to keep track of all needed information. Since many concurrency operations can use an unbound amount of memory (depending on \gls{bulk-acq}), statically defining information in the intrusive fields of threads is insufficient. The only variable sized container that does not require memory allocation is the callstack, which is heavily used in the implementation of internal scheduling. Particularly variable length arrays, which are used extensively.
    6 
    7 Since stack allocation is based around scope, the first step of the implementation is to identify the scopes that are available to store the information, and which of these can have a variable length. The threads and the condition both allow a fixed amount of memory to be stored, while mutex-routines and the actual blocking call allow for an unbound amount (though the later is preferable in terms of performance).
    8 
    9 Note that since the major contributions of this thesis are extending monitor semantics to \gls{bulk-acq} and loose object definitions, any challenges that are not resulting of these characteristiques of \CFA are considered as solved problems and therefore not discussed further.
     3There are several challenges specific to \CFA when implementing concurrency. These challenges are a direct result of \gls{bulk-acq} and loose object-definitions. These two constraints are the root cause of most design decisions in the implementation. Furthermore, to avoid contention from dynamically allocating memory in a concurrent environment, the internal-scheduling design is (almost) entirely free of mallocs. This approach avoids the chicken and egg problem~\cite{Chicken} of having a memory allocator that relies on the threading system and a threading system that relies on the runtime. This extra goal means that memory management is a constant concern in the design of the system.
     4
     5The main memory concern for concurrency is queues. All blocking operations are made by parking threads onto queues and all queues are designed with intrusive nodes, where each not has pre-allocated link fields for chaining, to avoid the need for memory allocation. Since several concurrency operations can use an unbound amount of memory (depending on \gls{bulk-acq}), statically defining information in the intrusive fields of threads is insufficient.The only way to use a variable amount of memory without requiring memory allocation is to pre-allocate large buffers of memory eagerly and store the information in these buffers. Conveniently, the callstack fits that description and is easy to use, which is why it is used heavily in the implementation of internal scheduling, particularly variable-length arrays. Since stack allocation is based around scope, the first step of the implementation is to identify the scopes that are available to store the information, and which of these can have a variable-length array. The threads and the condition both have a fixed amount of memory, while mutex-routines and the actual blocking call allow for an unbound amount, within the stack size.
     6
     7Note that since the major contributions of this thesis are extending monitor semantics to \gls{bulk-acq} and loose object definitions, any challenges that are not resulting of these characteristics of \CFA are considered as solved problems and therefore not discussed.
    108
    119% ======================================================================
     
    1513% ======================================================================
    1614
    17 The first step towards the monitor implementation is simple mutex-routines using monitors. In the single monitor case, this is done using the entry/exit procedure highlighted in listing \ref{lst:entry1}. This entry/exit procedure does not actually have to be extended to support multiple monitors, indeed it is sufficient to enter/leave monitors one-by-one as long as the order is correct to prevent deadlocks\cite{Havender68}. In \CFA, ordering of monitor relies on memory ordering, this is sufficient because all objects are guaranteed to have distinct non-overlaping memory layouts and mutual-exclusion for a monitor is only defined for its lifetime, meaning that destroying a monitor while it is acquired is undefined behavior. When a mutex call is made, the concerned monitors are agregated into a variable-length pointer array and sorted based on pointer values. This array presists for the entire duration of the mutual-exclusion and its ordering reused extensively.
     15The first step towards the monitor implementation is simple mutex-routines. In the single monitor case, mutual-exclusion is done using the entry/exit procedure in listing \ref{lst:entry1}. The entry/exit procedures do not have to be extended to support multiple monitors. Indeed it is sufficient to enter/leave monitors one-by-one as long as the order is correct to prevent deadlock~\cite{Havender68}. In \CFA, ordering of monitor acquisition relies on memory ordering. This approach is sufficient because all objects are guaranteed to have distinct non-overlapping memory layouts and mutual-exclusion for a monitor is only defined for its lifetime, meaning that destroying a monitor while it is acquired is Undefined Behavior. When a mutex call is made, the concerned monitors are aggregated into a variable-length pointer-array and sorted based on pointer values. This array persists for the entire duration of the mutual-exclusion and its ordering reused extensively.
    1816\begin{figure}
    1917\begin{multicols}{2}
     
    3735\end{pseudo}
    3836\end{multicols}
    39 \caption{Initial entry and exit routine for monitors}
    40 \label{lst:entry1}
     37\begin{pseudo}[caption={Initial entry and exit routine for monitors},label={lst:entry1}]
     38\end{pseudo}
    4139\end{figure}
    4240
     
    4442Depending on the choice of semantics for when monitor locks are acquired, interaction between monitors and \CFA's concept of polymorphism can be more complex to support. However, it is shown that entry-point locking solves most of the issues.
    4543
    46 First of all, interaction between \code{otype} polymorphism and monitors is impossible since monitors do not support copying. Therefore, the main question is how to support \code{dtype} polymorphism. It is important to present the difference between the two acquiring options : callsite and entry-point locking, i.e. acquiring the monitors before making a mutex routine call or as the first operation of the mutex routine-call. For example:
    47 \begin{figure}[H]
     44First of all, interaction between \code{otype} polymorphism and monitors is impossible since monitors do not support copying. Therefore, the main question is how to support \code{dtype} polymorphism. It is important to present the difference between the two acquiring options : \glspl{callsite-locking} and entry-point locking, i.e., acquiring the monitors before making a mutex routine-call or as the first operation of the mutex routine-call. For example:
     45\begin{table}[H]
    4846\begin{center}
    4947\begin{tabular}{|c|c|c|}
     
    9795\end{center}
    9896\caption{Call-site vs entry-point locking for mutex calls}
    99 \label{fig:locking-site}
    100 \end{figure}
    101 
    102 Note the \code{mutex} keyword relies on the type system, which means that in cases where a generic monitor routine is desired, writing the mutex routine is possible with the proper trait, for example:
     97\label{tbl:locking-site}
     98\end{table}
     99
     100Note the \code{mutex} keyword relies on the type system, which means that in cases where a generic monitor-routine is desired, writing the mutex routine is possible with the proper trait, e.g.:
    103101\begin{cfacode}
    104102//Incorrect: T may not be monitor
     
    111109\end{cfacode}
    112110
    113 Both entry-point and callsite locking are feasible implementations. The current \CFA implementations uses entry-point locking because it requires less work when using \gls{raii}, effectively transferring the burden of implementation to object construction/destruction. The same could be said of callsite locking, the difference being that the later does not necessarily have an existing scope that matches exactly the scope of the mutual exclusion, i.e.: the function body. Furthermore, entry-point locking requires less code generation since any useful routine is called at least as often as it is define, there can be only one entry-point but many callsites.
     111Both entry-point and \gls{callsite-locking} are feasible implementations. The current \CFA implementations uses entry-point locking because it requires less work when using \gls{raii}, effectively transferring the burden of implementation to object construction/destruction. It is harder to use \gls{raii} for call-site locking, as it does not necessarily have an existing scope that matches exactly the scope of the mutual exclusion, i.e.: the function body. For example, the monitor call can appear in the middle of an expression. Furthermore, entry-point locking requires less code generation since any useful routine multiple times, but there is only one entry-point for many call-sites.
    114112
    115113% ======================================================================
     
    119117% ======================================================================
    120118
    121 Figure \ref{fig:system1} shows a high-level picture if the \CFA runtime system in regards to concurrency. Each component of the picture is explained in details in the fllowing sections.
     119Figure \ref{fig:system1} shows a high-level picture if the \CFA runtime system in regards to concurrency. Each component of the picture is explained in details in the flowing sections.
    122120
    123121\begin{figure}
     
    130128
    131129\subsection{Context Switching}
    132 As mentionned in section \ref{coroutine}, coroutines are a stepping stone for implementing threading. This is because they share the same mechanism for context-switching between different stacks. To improve performance and simplicity, context-switching is implemented using the following assumption: all context-switches happen inside a specific function call. This assumption means that the context-switch only has to copy the callee-saved registers onto the stack and then switch the stack registers with the ones of the target coroutine/thread. Note that the instruction pointer can be left untouched since the context-switch is always inside the same function. Threads however do not context-switch between each other directly. They context-switch to the scheduler. This method is called a 2-step context-switch and has the advantage of having a clear distinction between user code and the kernel where scheduling and other system operation happen. Obiously, this has the cost of doubling the context-switch cost because threads must context-switch to an intermediate stack. However, the performance of the 2-step context-switch is still superior to a \code{pthread_yield}(see section \ref{results}). additionally, for users in need for optimal performance, it is important to note that having a 2-step context-switch as the default does not prevent \CFA from offering a 1-step context-switch to use manually (or as part of monitors). This option is not currently present in \CFA but the changes required to add it are strictly additive.
     130As mentioned in section \ref{coroutine}, coroutines are a stepping stone for implementing threading, because they share the same mechanism for context-switching between different stacks. To improve performance and simplicity, context-switching is implemented using the following assumption: all context-switches happen inside a specific function call. This assumption means that the context-switch only has to copy the callee-saved registers onto the stack and then switch the stack registers with the ones of the target coroutine/thread. Note that the instruction pointer can be left untouched since the context-switch is always inside the same function. Threads however do not context-switch between each other directly. They context-switch to the scheduler. This method is called a 2-step context-switch and has the advantage of having a clear distinction between user code and the kernel where scheduling and other system operation happen. Obviously, this doubles the context-switch cost because threads must context-switch to an intermediate stack. The alternative 1-step context-switch uses the stack of the ``from'' thread to schedule and then context-switches directly to the ``to'' thread. However, the performance of the 2-step context-switch is still superior to a \code{pthread_yield} (see section \ref{results}). Additionally, for users in need for optimal performance, it is important to note that having a 2-step context-switch as the default does not prevent \CFA from offering a 1-step context-switch (akin to the Microsoft \code{SwitchToFiber}~\cite{switchToWindows} routine). This option is not currently present in \CFA but the changes required to add it are strictly additive.
    133131
    134132\subsection{Processors}
    135 Parallelism in \CFA is built around using processors to specify how much parallelism is desired. \CFA processors are object wrappers around kernel threads, specifically pthreads in the current implementation of \CFA. Indeed, any parallelism must go through operating-system librairies. However, \glspl{uthread} are still the main source of concurrency, processors are simply the underlying source of parallelism. Indeed, processor \glspl{kthread} simply fetch a \glspl{uthread} from the scheduler and run, they are effectively executers for user-threads. The main benefit of this approach is that it offers a well defined boundary between kernel code and user code, for example, kernel thread quiescing, scheduling and interrupt handling. Processors internally use coroutines to take advantage of the existing context-switching semantics.
     133Parallelism in \CFA is built around using processors to specify how much parallelism is desired. \CFA processors are object wrappers around kernel threads, specifically pthreads in the current implementation of \CFA. Indeed, any parallelism must go through operating-system libraries. However, \glspl{uthread} are still the main source of concurrency, processors are simply the underlying source of parallelism. Indeed, processor \glspl{kthread} simply fetch a \gls{uthread} from the scheduler and run it; they are effectively executers for user-threads. The main benefit of this approach is that it offers a well defined boundary between kernel code and user code, for example, kernel thread quiescing, scheduling and interrupt handling. Processors internally use coroutines to take advantage of the existing context-switching semantics.
    136134
    137135\subsection{Stack management}
    138 One of the challenges of this system is to reduce the footprint as much as possible. Specifically, all pthreads created also have a stack created with them, which should be used as much as possible. Normally, coroutines also create there own stack to run on, however, in the case of the coroutines used for processors, these coroutines run directly on the kernel thread stack, effectively stealing the processor stack. The exception to this rule is the Main Processor, i.e. the initial kernel thread that is given to any program. In order to respect user expectations, the stack of the initial kernel thread, the main stack of the program, is used by the main user thread rather than the main processor.
     136One of the challenges of this system is to reduce the footprint as much as possible. Specifically, all pthreads created also have a stack created with them, which should be used as much as possible. Normally, coroutines also create there own stack to run on, however, in the case of the coroutines used for processors, these coroutines run directly on the \gls{kthread} stack, effectively stealing the processor stack. The exception to this rule is the Main Processor, i.e. the initial \gls{kthread} that is given to any program. In order to respect C user-expectations, the stack of the initial kernel thread, the main stack of the program, is used by the main user thread rather than the main processor, which can grow very large
    139137
    140138\subsection{Preemption} \label{preemption}
    141 Finally, an important aspect for any complete threading system is preemption. As mentionned in chapter \ref{basics}, preemption introduces an extra degree of uncertainty, which enables users to have multiple threads interleave transparently, rather than having to cooperate among threads for proper scheduling and CPU distribution. Indeed, preemption is desireable because it adds a degree of isolation among threads. In a fully cooperative system, any thread that runs into a long loop can starve other threads, while in a preemptive system starvation can still occur but it does not rely on every thread having to yield or block on a regular basis, which reduces significantly a programmer burden. Obviously, preemption is not optimal for every workload, however any preemptive system can become a cooperative system by making the time-slices extremely large. Which is why \CFA uses a preemptive threading system.
    142 
    143 Preemption in \CFA is based on kernel timers, which are used to run a discrete-event simulation. Every processor keeps track of the current time and registers an expiration time with the preemption system. When the preemption system receives a change in preemption, it sorts these expiration times in a list and sets a kernel timer for the closest one, effectively stepping between preemption events on each signals sent by the timer. These timers use the linux signal {\tt SIGALRM}, which is delivered to the process rather than the kernel-thread. This results in an implementation problem,because when delivering signals to a process, the kernel documentation states that the signal can be delivered to any kernel thread for which the signal is not blocked i.e. :
     139Finally, an important aspect for any complete threading system is preemption. As mentioned in chapter \ref{basics}, preemption introduces an extra degree of uncertainty, which enables users to have multiple threads interleave transparently, rather than having to cooperate among threads for proper scheduling and CPU distribution. Indeed, preemption is desirable because it adds a degree of isolation among threads. In a fully cooperative system, any thread that runs a long loop can starve other threads, while in a preemptive system, starvation can still occur but it does not rely on every thread having to yield or block on a regular basis, which reduces significantly a programmer burden. Obviously, preemption is not optimal for every workload, however any preemptive system can become a cooperative system by making the time-slices extremely large. Therefore, \CFA uses a preemptive threading system.
     140
     141Preemption in \CFA is based on kernel timers, which are used to run a discrete-event simulation. Every processor keeps track of the current time and registers an expiration time with the preemption system. When the preemption system receives a change in preemption, it inserts the time in a sorted order and sets a kernel timer for the closest one, effectively stepping through preemption events on each signal sent by the timer. These timers use the Linux signal {\tt SIGALRM}, which is delivered to the process rather than the kernel-thread. This results in an implementation problem, because when delivering signals to a process, the kernel can deliver the signal to any kernel thread for which the signal is not blocked, i.e. :
    144142\begin{quote}
    145143A process-directed signal may be delivered to any one of the threads that does not currently have the signal blocked. If more than one of the threads has the signal unblocked, then the kernel chooses an arbitrary thread to which to deliver the signal.
    146144SIGNAL(7) - Linux Programmer's Manual
    147145\end{quote}
    148 For the sake of simplicity and in order to prevent the case of having two threads receiving alarms simultaneously, \CFA programs block the {\tt SIGALRM} signal on every thread except one. Now because of how involontary context-switches are handled, the kernel thread handling {\tt SIGALRM} cannot also be a processor thread.
    149 
    150 Involuntary context-switching is done by sending signal {\tt SIGUSER1} to the corresponding processor and having the thread yield from inside the signal handler. Effectively context-switching away from the signal-handler back to the kernel and the signal-handler frame is eventually unwound when the thread is scheduled again. This approach means that a signal-handler can start on one kernel thread and terminate on a second kernel thread (but the same user thread). It is important to note that signal-handlers save and restore signal masks because user-thread migration can cause signal mask to migrate from one kernel thread to another. This behaviour is only a problem if all kernel threads among which a user thread can migrate differ in terms of signal masks\footnote{Sadly, official POSIX documentation is silent on what distiguishes ``async-signal-safe'' functions from other functions}. However, since the kernel thread hanlding preemption requires a different signal mask, executing user threads on the kernel alarm thread can cause deadlocks. For this reason, the alarm thread is on a tight loop around a system call to \code{sigwaitinfo}, requiring very little CPU time for preemption. One final detail about the alarm thread is how to wake it when additional communication is required (e.g., on thread termination). This unblocking is also done using {\tt SIGALRM}, but sent throught the \code{pthread_sigqueue}. Indeed, \code{sigwait} can differentiate signals sent from \code{pthread_sigqueue} from signals sent from alarms or the kernel.
     146For the sake of simplicity and in order to prevent the case of having two threads receiving alarms simultaneously, \CFA programs block the {\tt SIGALRM} signal on every kernel thread except one. Now because of how involuntary context-switches are handled, the kernel thread handling {\tt SIGALRM} cannot also be a processor thread.
     147
     148Involuntary context-switching is done by sending signal {\tt SIGUSER1} to the corresponding proces\-sor and having the thread yield from inside the signal handler. This approach effectively context-switches away from the signal-handler back to the kernel and the signal-handler frame is eventually unwound when the thread is scheduled again. As a result, a signal-handler can start on one kernel thread and terminate on a second kernel thread (but the same user thread). It is important to note that signal-handlers save and restore signal masks because user-thread migration can cause a signal mask to migrate from one kernel thread to another. This behaviour is only a problem if all kernel threads, among which a user thread can migrate, differ in terms of signal masks\footnote{Sadly, official POSIX documentation is silent on what distinguishes ``async-signal-safe'' functions from other functions.}. However, since the kernel thread handling preemption requires a different signal mask, executing user threads on the kernel-alarm thread can cause deadlocks. For this reason, the alarm thread is in a tight loop around a system call to \code{sigwaitinfo}, requiring very little CPU time for preemption. One final detail about the alarm thread is how to wake it when additional communication is required (e.g., on thread termination). This unblocking is also done using {\tt SIGALRM}, but sent through the \code{pthread_sigqueue}. Indeed, \code{sigwait} can differentiate signals sent from \code{pthread_sigqueue} from signals sent from alarms or the kernel.
    151149
    152150\subsection{Scheduler}
    153 Finally, an aspect that was not mentionned yet is the scheduling algorithm. Currently, the \CFA scheduler uses a single ready queue for all processors, which is the simplest approach to scheduling. Further discussion on scheduling is present in section \label{futur:sched}.
     151Finally, an aspect that was not mentioned yet is the scheduling algorithm. Currently, the \CFA scheduler uses a single ready queue for all processors, which is the simplest approach to scheduling. Further discussion on scheduling is present in section \ref{futur:sched}.
    154152
    155153% ======================================================================
     
    165163\end{center}
    166164\caption{Traditional illustration of a monitor}
    167 \label{fig:monitor}
    168 \end{figure}
    169 
    170 This picture has several components, the two most important being the entry-queue and the AS-stack. The entry-queue is an (almost) FIFO list where threads waiting to enter are parked, while the acceptor-signalor (AS) stack is a FILO list used for threads that have been signalled or otherwise marked as running next.
    171 
    172 For \CFA, this picture does not have support for blocking multiple monitors on a single condition. To support \gls{bulk-acq} two changes to this picture are required. First, it is non longer helpful to attach the condition to a single monitor. Secondly, the thread waiting on the conditions has to be seperated multiple monitors, which yields :
     165\end{figure}
     166
     167This picture has several components, the two most important being the entry-queue and the AS-stack. The entry-queue is an (almost) FIFO list where threads waiting to enter are parked, while the acceptor-signaler (AS) stack is a FILO list used for threads that have been signalled or otherwise marked as running next.
     168
     169For \CFA, this picture does not have support for blocking multiple monitors on a single condition. To support \gls{bulk-acq} two changes to this picture are required. First, it is no longer helpful to attach the condition to \emph{a single} monitor. Secondly, the thread waiting on the condition has to be separated across multiple monitors, seen in figure \ref{fig:monitor_cfa}.
    173170
    174171\begin{figure}[H]
     
    180177\end{figure}
    181178
    182 This picture and the proper entry and leave algorithms is the fundamental implementation of internal scheduling (see listing \ref{lst:entry2}). Note that when threads are moved from the condition to the AS-stack, it splits the thread into to pieces. The thread is woken up when all the pieces have moved from the AS-stacks to the active thread seat. In this picture, the threads are split into halves but this is only because there are two monitors in this picture. For a specific signaling operation every monitor needs a piece of thread on its AS-stack.
     179This picture and the proper entry and leave algorithms (see listing \ref{lst:entry2}) is the fundamental implementation of internal scheduling. Note that when a thread is moved from the condition to the AS-stack, it is conceptually split the thread into N pieces, where N is the number of monitors specified in the parameter list. The thread is woken up when all the pieces have popped from the AS-stacks and made active. In this picture, the threads are split into halves but this is only because there are two monitors. For a specific signaling operation every monitor needs a piece of thread on its AS-stack.
    183180
    184181\begin{figure}[b]
     
    209206\end{pseudo}
    210207\end{multicols}
    211 \caption{Entry and exit routine for monitors with internal scheduling}
    212 \label{lst:entry2}
    213 \end{figure}
    214 
    215 Some important things to notice about the exit routine. The solution discussed in \ref{intsched} can be seen in the exit routine of listing \ref{lst:entry2}. Basically, the solution boils down to having a seperate data structure for the condition queue and the AS-stack, and unconditionally transferring ownership of the monitors but only unblocking the thread when the last monitor has transferred ownership. This solution is deadlock safe as well as preventing any potential barging. The data structure used for the AS-stack are reused extensively for external scheduling, but in the case of internal scheduling, the data is allocated using variable-length arrays on the callstack of the \code{wait} and \code{signal_block} routines.
     208\begin{pseudo}[caption={Entry and exit routine for monitors with internal scheduling},label={lst:entry2}]
     209\end{pseudo}
     210\end{figure}
     211
     212Some important things to notice about the exit routine. The solution discussed in \ref{intsched} can be seen in the exit routine of listing \ref{lst:entry2}. Basically, the solution boils down to having a separate data structure for the condition queue and the AS-stack, and unconditionally transferring ownership of the monitors but only unblocking the thread when the last monitor has transferred ownership. This solution is deadlock safe as well as preventing any potential barging. The data structure used for the AS-stack are reused extensively for external scheduling, but in the case of internal scheduling, the data is allocated using variable-length arrays on the call-stack of the \code{wait} and \code{signal_block} routines.
    216213
    217214\begin{figure}[H]
     
    223220\end{figure}
    224221
    225 Figure \ref{fig:structs} shows a high level representation of these data-structures. The main idea behind them is that, while figure \ref{fig:monitor_cfa} is a nice illustration in theory, in practice breaking a threads into multiple pieces to put unto intrusive stacks does not make sense. The \code{condition node} is the data structure that is queued into a condition variable and, when signaled, the condition queue is popped and each \code{condition criterion} are moved to the AS-stack. Once all the criterion have be popped from their respective AS-stacks, the thread is woken-up, which is what is shown in listing \ref{lst:entry2}.
     222Figure \ref{fig:structs} shows a high-level representation of these data-structures. The main idea behind them is that, a thread cannot contain an arbitrary number of intrusive stacks for linking onto monitor. The \code{condition node} is the data structure that is queued onto a condition variable and, when signaled, the condition queue is popped and each \code{condition criterion} are moved to the AS-stack. Once all the criterion have be popped from their respective AS-stacks, the thread is woken-up, which is what is shown in listing \ref{lst:entry2}.
    226223
    227224% ======================================================================
     
    230227% ======================================================================
    231228% ======================================================================
    232 Similarly to internal scheduling, external scheduling for multiple monitors relies on the idea that waiting-thread queues are no longer specific to a single monitor, as mentionned in section \ref{extsched}. For internal scheduling, these queues are part of condition variables which are still unique for a given scheduling operation (e.g., no single statment uses multiple conditions). However, in the case of external scheduling, there is no equivalent object which is associated with \code{waitfor} statements. This absence means the queues holding the waiting threads must be stored inside at least one of the monitors that is acquired. The monitors being the only objects that have sufficient lifetime and are available on both sides of the \code{waitfor} statment. This requires an algorithm to choose which monitor holds the relevant queue. It is also important that said algorithm be independent of the order in which users list parameters. The proposed algorithm is to fall back on monitor lock ordering and specify that the monitor that is acquired first is the one with the relevant wainting queue. This assumes that the lock acquiring order is static for the lifetime of all concerned objects but that is a reasonable constraint.
     229Similarly to internal scheduling, external scheduling for multiple monitors relies on the idea that waiting-thread queues are no longer specific to a single monitor, as mentioned in section \ref{extsched}. For internal scheduling, these queues are part of condition variables, which are still unique for a given scheduling operation (e.g., no signal statement uses multiple conditions). However, in the case of external scheduling, there is no equivalent object which is associated with \code{waitfor} statements. This absence means the queues holding the waiting threads must be stored inside at least one of the monitors that is acquired. These monitors being the only objects that have sufficient lifetime and are available on both sides of the \code{waitfor} statement. This requires an algorithm to choose which monitor holds the relevant queue. It is also important that said algorithm be independent of the order in which users list parameters. The proposed algorithm is to fall back on monitor lock ordering (sorting by address) and specify that the monitor that is acquired first is the one with the relevant waiting queue. This assumes that the lock acquiring order is static for the lifetime of all concerned objects but that is a reasonable constraint.
    233230
    234231This algorithm choice has two consequences :
    235232\begin{itemize}
    236         \item The queue of the highest priority monitor is no longer a true FIFO queue because threads can be moved to the front of the queue. These queues need to contain a set of monitors for each of the waiting threads. Therefore, another thread whose set contains the same highest priority monitor but different lower priority monitors may arrive first but enter the critical section after a thread with the correct pairing.
    237         \item The queue of the lowest priority monitor is both required and potentially unused. Indeed, since it is not known at compile time which monitor will be the lowest priority monitor, every monitor needs to have the correct queues even though it is possible that some queues will go unused for the entire duration of the program, for example if a monitor is only used in a specific pair.
     233        \item The queue of the monitor with the lowest address is no longer a true FIFO queue because threads can be moved to the front of the queue. These queues need to contain a set of monitors for each of the waiting threads. Therefore, another thread whose set contains the same lowest address monitor but different lower priority monitors may arrive first but enter the critical section after a thread with the correct pairing.
     234        \item The queue of the lowest priority monitor is both required and potentially unused. Indeed, since it is not known at compile time which monitor is the monitor with have the lowest address, every monitor needs to have the correct queues even though it is possible that some queues go unused for the entire duration of the program, for example if a monitor is only used in a specific pair.
    238235\end{itemize}
    239 
    240236Therefore, the following modifications need to be made to support external scheduling :
    241237\begin{itemize}
    242         \item The threads waiting on the entry-queue need to keep track of which routine is trying to enter, and using which set of monitors. The \code{mutex} routine already has all the required information on its stack so the thread only needs to keep a pointer to that information.
    243         \item The monitors need to keep a mask of acceptable routines. This mask contains for each acceptable routine, a routine pointer and an array of monitors to go with it. It also needs storage to keep track of which routine was accepted. Since this information is not specific to any monitor, the monitors actually contain a pointer to an integer on the stack of the waiting thread. Note that the complete mask can be pushed to any owned monitors, regardless of \code{when} statements, the \code{waitfor} statement is used in a context where the thread already has full ownership of (at least) every concerned monitor and therefore monitors will refuse all calls no matter what.
     238        \item The threads waiting on the entry-queue need to keep track of which routine it is trying to enter, and using which set of monitors. The \code{mutex} routine already has all the required information on its stack so the thread only needs to keep a pointer to that information.
     239        \item The monitors need to keep a mask of acceptable routines. This mask contains for each acceptable routine, a routine pointer and an array of monitors to go with it. It also needs storage to keep track of which routine was accepted. Since this information is not specific to any monitor, the monitors actually contain a pointer to an integer on the stack of the waiting thread. Note that if a thread has acquired two monitors but executes a \code{waitfor} with only one monitor as a parameter, setting the mask of acceptable routines to both monitors will not cause any problems since the extra monitor will not change ownership regardless. This becomes relevant when \code{when} clauses affect the number of monitors passed to a \code{waitfor} statement.
    244240        \item The entry/exit routine need to be updated as shown in listing \ref{lst:entry3}.
    245241\end{itemize}
    246242
    247243\subsection{External scheduling - destructors}
    248 Finally, to support the ordering inversion of destructors, the code generation needs to be modified to use a special entry routine. This routine is needed because of the storage requirements of the call order inversion. Indeed, when waiting for the destructors, storage is need for the waiting context and the lifetime of said storage needs to outlive the waiting operation it is needed for. For regular \code{waitfor} statements, the callstack of the routine itself matches this requirement but it is no longer the case when waiting for the destructor since it is pushed on to the AS-stack for later. The waitfor semantics can then be adjusted correspondingly, as seen in listing \ref{lst:entry-dtor}
     244Finally, to support the ordering inversion of destructors, the code generation needs to be modified to use a special entry routine. This routine is needed because of the storage requirements of the call order inversion. Indeed, when waiting for the destructors, storage is need for the waiting context and the lifetime of said storage needs to outlive the waiting operation it is needed for. For regular \code{waitfor} statements, the call-stack of the routine itself matches this requirement but it is no longer the case when waiting for the destructor since it is pushed on to the AS-stack for later. The waitfor semantics can then be adjusted correspondingly, as seen in listing \ref{lst:entry-dtor}
    249245
    250246\begin{figure}
     
    280276\end{pseudo}
    281277\end{multicols}
    282 \caption{Entry and exit routine for monitors with internal scheduling and external scheduling}
    283 \label{lst:entry3}
     278\begin{pseudo}[caption={Entry and exit routine for monitors with internal scheduling and external scheduling},label={lst:entry3}]
     279\end{pseudo}
    284280\end{figure}
    285281
     
    326322\end{pseudo}
    327323\end{multicols}
    328 \caption{Pseudo code for the \code{waitfor} routine and the \code{mutex} entry routine for destructors}
    329 \label{lst:entry-dtor}
    330 \end{figure}
     324\begin{pseudo}[caption={Pseudo code for the \code{waitfor} routine and the \code{mutex} entry routine for destructors},label={lst:entry-dtor}]
     325\end{pseudo}
     326\end{figure}
  • doc/proposals/concurrency/text/parallelism.tex

    r875a72f r35bae526  
    77% #       #     # #     # #     # ####### ####### ####### ####### ###  #####  #     #
    88\chapter{Parallelism}
    9 Historically, computer performance was about processor speeds and instructions count. However, with heat dissipation being a direct consequence of speed increase, parallelism has become the new source for increased performance~\cite{Sutter05, Sutter05b}. In this decade, it is not longer reasonnable to create a high-performance application without caring about parallelism. Indeed, parallelism is an important aspect of performance and more specifically throughput and hardware utilization. The lowest-level approach of parallelism is to use \glspl{kthread} in combination with semantics like \code{fork}, \code{join}, etc. However, since these have significant costs and limitations, \glspl{kthread} are now mostly used as an implementation tool rather than a user oriented one. There are several alternatives to solve these issues that all have strengths and weaknesses. While there are many variations of the presented paradigms, most of these variations do not actually change the guarantees or the semantics, they simply move costs in order to achieve better performance for certain workloads.
     9Historically, computer performance was about processor speeds and instructions count. However, with heat dissipation being a direct consequence of speed increase, parallelism has become the new source for increased performance~\cite{Sutter05, Sutter05b}. In this decade, it is not longer reasonable to create a high-performance application without caring about parallelism. Indeed, parallelism is an important aspect of performance and more specifically throughput and hardware utilization. The lowest-level approach of parallelism is to use \glspl{kthread} in combination with semantics like \code{fork}, \code{join}, etc. However, since these have significant costs and limitations, \glspl{kthread} are now mostly used as an implementation tool rather than a user oriented one. There are several alternatives to solve these issues that all have strengths and weaknesses. While there are many variations of the presented paradigms, most of these variations do not actually change the guarantees or the semantics, they simply move costs in order to achieve better performance for certain workloads.
    1010
    11 \section{Paradigm}
     11\section{Paradigms}
    1212\subsection{User-level threads}
    13 A direct improvement on the \gls{kthread} approach is to use \glspl{uthread}. These threads offer most of the same features that the operating system already provide but can be used on a much larger scale. This approach is the most powerfull solution as it allows all the features of multi-threading, while removing several of the more expensive costs of kernel threads. The down side is that almost none of the low-level threading problems are hidden; users still have to think about data races, deadlocks and synchronization issues. These issues can be somewhat alleviated by a concurrency toolkit with strong garantees but the parallelism toolkit offers very little to reduce complexity in itself.
     13A direct improvement on the \gls{kthread} approach is to use \glspl{uthread}. These threads offer most of the same features that the operating system already provide but can be used on a much larger scale. This approach is the most powerful solution as it allows all the features of multi-threading, while removing several of the more expensive costs of kernel threads. The down side is that almost none of the low-level threading problems are hidden; users still have to think about data races, deadlocks and synchronization issues. These issues can be somewhat alleviated by a concurrency toolkit with strong guarantees but the parallelism toolkit offers very little to reduce complexity in itself.
    1414
    1515Examples of languages that support \glspl{uthread} are Erlang~\cite{Erlang} and \uC~\cite{uC++book}.
    1616
    1717\subsection{Fibers : user-level threads without preemption} \label{fibers}
    18 A popular varient of \glspl{uthread} is what is often refered to as \glspl{fiber}. However, \glspl{fiber} do not present meaningful semantical differences with \glspl{uthread}. The significant difference between \glspl{uthread} and \glspl{fiber} is the lack of \gls{preemption} in the later one. Advocates of \glspl{fiber} list their high performance and ease of implementation as majors strenghts of \glspl{fiber} but the performance difference between \glspl{uthread} and \glspl{fiber} is controversial, and the ease of implementation, while true, is a weak argument in the context of language design. Therefore this proposal largely ignores fibers.
     18A popular variant of \glspl{uthread} is what is often referred to as \glspl{fiber}. However, \glspl{fiber} do not present meaningful semantical differences with \glspl{uthread}. The significant difference between \glspl{uthread} and \glspl{fiber} is the lack of \gls{preemption} in the latter. Advocates of \glspl{fiber} list their high performance and ease of implementation as majors strengths but the performance difference between \glspl{uthread} and \glspl{fiber} is controversial, and the ease of implementation, while true, is a weak argument in the context of language design. Therefore this proposal largely ignores fibers.
    1919
    2020An example of a language that uses fibers is Go~\cite{Go}
     
    2626
    2727\subsection{Paradigm performance}
    28 While the choice between the three paradigms listed above may have significant performance implication, it is difficult to pindown the performance implications of chosing a model at the language level. Indeed, in many situations one of these paradigms may show better performance but it all strongly depends on the workload. Having a large amount of mostly independent units of work to execute almost guarantess that the \gls{pool} based system has the best performance thanks to the lower memory overhead (i.e., no thread stack per job). However, interactions among jobs can easily exacerbate contention. User-level threads allow fine-grain context switching, which results in better resource utilisation, but a context switch is more expensive and the extra control means users need to tweak more variables to get the desired performance. Finally, if the units of uninterrupted work are large enough the paradigm choice is largely amortised by the actual work done.
     28While the choice between the three paradigms listed above may have significant performance implication, it is difficult to pin-down the performance implications of choosing a model at the language level. Indeed, in many situations one of these paradigms may show better performance but it all strongly depends on the workload. Having a large amount of mostly independent units of work to execute almost guarantees that the \gls{pool} based system has the best performance thanks to the lower memory overhead (i.e., no thread stack per job). However, interactions among jobs can easily exacerbate contention. User-level threads allow fine-grain context switching, which results in better resource utilization, but a context switch is more expensive and the extra control means users need to tweak more variables to get the desired performance. Finally, if the units of uninterrupted work are large enough the paradigm choice is largely amortized by the actual work done.
    2929
    3030\section{The \protect\CFA\ Kernel : Processors, Clusters and Threads}\label{kernel}
     31A \gls{cfacluster} is a group of \gls{kthread} executed in isolation. \Glspl{uthread} are scheduled on the \glspl{kthread} of a given \gls{cfacluster}, allowing organization between \glspl{uthread} and \glspl{kthread}. It is important that \glspl{kthread} belonging to a same \glspl{cfacluster} have homogeneous settings, otherwise migrating a \gls{uthread} from one \gls{kthread} to the other can cause issues. A \gls{cfacluster} also offers a plugable scheduler that can optimize the workload generated by the \glspl{uthread}.
    3132
    32 \Glspl{cfacluster} have not been fully implmented in the context of this thesis, currently \CFA only supports one \gls{cfacluster}, the initial one. The objective of \gls{cfacluster} is to group \gls{kthread} with identical settings together. \Glspl{uthread} can be scheduled on a \glspl{kthread} of a given \gls{cfacluster}, allowing organization between \glspl{kthread} and \glspl{uthread}. It is important that \glspl{kthread} belonging to a same \glspl{cfacluster} have homogenous settings, otherwise migrating a \gls{uthread} from one \gls{kthread} to the other can cause issues.
     33\Glspl{cfacluster} have not been fully implemented in the context of this thesis, currently \CFA only supports one \gls{cfacluster}, the initial one.
    3334
    3435\subsection{Future Work: Machine setup}\label{machine}
    35 While this was not done in the context of this thesis, another important aspect of clusters is affinity. While many common desktop and laptop PCs have homogeneous CPUs, other devices often have more heteregenous setups. For example, system using \acrshort{numa} configurations may benefit from users being able to tie clusters and\/or kernel threads to certains CPU cores. OS support for CPU affinity is now common \cite{affinityLinux, affinityWindows, affinityFreebsd, affinityNetbsd, affinityMacosx} which means it is both possible and desirable for \CFA to offer an abstraction mechanism for portable CPU affinity.
     36While this was not done in the context of this thesis, another important aspect of clusters is affinity. While many common desktop and laptop PCs have homogeneous CPUs, other devices often have more heterogeneous setups. For example, a system using \acrshort{numa} configurations may benefit from users being able to tie clusters and\/or kernel threads to certain CPU cores. OS support for CPU affinity is now common~\cite{affinityLinux, affinityWindows, affinityFreebsd, affinityNetbsd, affinityMacosx} which means it is both possible and desirable for \CFA to offer an abstraction mechanism for portable CPU affinity.
    3637
    37 % \subsection{Paradigms}\label{cfaparadigms}
    38 % Given these building blocks, it is possible to reproduce all three of the popular paradigms. Indeed, \glspl{uthread} is the default paradigm in \CFA. However, disabling \gls{preemption} on the \gls{cfacluster} means \glspl{cfathread} effectively become \glspl{fiber}. Since several \glspl{cfacluster} with different scheduling policy can coexist in the same application, this allows \glspl{fiber} and \glspl{uthread} to coexist in the runtime of an application. Finally, it is possible to build executors for thread pools from \glspl{uthread} or \glspl{fiber}.
     38\subsection{Paradigms}\label{cfaparadigms}
     39Given these building blocks, it is possible to reproduce all three of the popular paradigms. Indeed, \glspl{uthread} is the default paradigm in \CFA. However, disabling \gls{preemption} on the \gls{cfacluster} means \glspl{cfathread} effectively become \glspl{fiber}. Since several \glspl{cfacluster} with different scheduling policy can coexist in the same application, this allows \glspl{fiber} and \glspl{uthread} to coexist in the runtime of an application. Finally, it is possible to build executors for thread pools from \glspl{uthread} or \glspl{fiber}, which includes specialize jobs like actors~\cite{Actors}.
  • doc/proposals/concurrency/text/results.tex

    r875a72f r35bae526  
    55% ======================================================================
    66\section{Machine setup}
    7 Table \ref{tab:machine} shows the characteristiques of the machine used to run the benchmarks. All tests where made on this machine.
    8 \begin{figure}[H]
     7Table \ref{tab:machine} shows the characteristics of the machine used to run the benchmarks. All tests where made on this machine.
     8\begin{table}[H]
    99\begin{center}
    1010\begin{tabular}{| l | r | l | r |}
     
    2525\hline
    2626\hline
    27 Operating system                & Ubuntu 16.04.3 LTS    & Kernel                & Linux 4.4.0-97-generic \\
    28 \hline
    29 Compiler                        & gcc 6.3.0             & Translator    & CFA 1.0.0 \\
     27Operating system                & Ubuntu 16.04.3 LTS    & Kernel                & Linux 4.4-97-generic \\
     28\hline
     29Compiler                        & GCC 6.3               & Translator    & CFA 1 \\
     30\hline
     31Java version            & OpenJDK-9             & Go version    & 1.9.2 \\
    3032\hline
    3133\end{tabular}
     
    3335\caption{Machine setup used for the tests}
    3436\label{tab:machine}
    35 \end{figure}
     37\end{table}
    3638
    3739\section{Micro benchmarks}
     
    3941\begin{pseudo}
    4042#define BENCH(run, result)
    41         gettime();
     43        before = gettime();
    4244        run;
    43         gettime();
     45        after  = gettime();
    4446        result = (after - before) / N;
    4547\end{pseudo}
    46 The method used to get time is \code{clock_gettime(CLOCK_THREAD_CPUTIME_ID);}. Each benchmark is using many interations of a simple call to measure the cost of the call. The specific number of interation dependes on the specific benchmark.
     48The method used to get time is \code{clock_gettime(CLOCK_THREAD_CPUTIME_ID);}. Each benchmark is using many iterations of a simple call to measure the cost of the call. The specific number of iteration depends on the specific benchmark.
    4749
    4850\subsection{Context-switching}
    49 The first interesting benchmark is to measure how long context-switches take. The simplest approach to do this is to yield on a thread, which executes a 2-step context switch. In order to make the comparison fair, coroutines also execute a 2-step context-switch, which is a resume/suspend cycle instead of a yield. Listing \ref{lst:ctx-switch} shows the code for coroutines and threads. All omitted tests are functionally identical to one of these tests. The results can be shown in table \ref{tab:ctx-switch}.
     51The first interesting benchmark is to measure how long context-switches take. The simplest approach to do this is to yield on a thread, which executes a 2-step context switch. In order to make the comparison fair, coroutines also execute a 2-step context-switch (\gls{uthread} to \gls{kthread} then \gls{kthread} to \gls{uthread}), which is a resume/suspend cycle instead of a yield. Listing \ref{lst:ctx-switch} shows the code for coroutines and threads whith the results in table \ref{tab:ctx-switch}. All omitted tests are functionally identical to one of these tests.
    5052\begin{figure}
    5153\begin{multicols}{2}
     
    8890\end{cfacode}
    8991\end{multicols}
    90 \caption{\CFA benchmark code used to measure context-switches for coroutines and threads.}
    91 \label{lst:ctx-switch}
    92 \end{figure}
    93 
    94 \begin{figure}
    95 \begin{center}
    96 \begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
    97 \cline{2-4}
    98 \multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
    99 \hline
    100 Kernel Threads          & 239           & 242.57        & 5.54 \\
    101 \CFA Coroutines         & 38            & 38            & 0    \\
    102 \CFA Threads            & 102           & 102.39        & 1.57 \\
    103 \uC Coroutines          & 46            & 46.68 & 0.47 \\
    104 \uC Threads                     & 98            & 99.39 & 1.52 \\
    105 \hline
    106 \end{tabular}
    107 \end{center}
    108 \caption{Context Switch comparaison. All numbers are in nanoseconds(\si{\nano\second})}
     92\begin{cfacode}[caption={\CFA benchmark code used to measure context-switches for coroutines and threads.},label={lst:ctx-switch}]
     93\end{cfacode}
     94\end{figure}
     95
     96\begin{table}
     97\begin{center}
     98\begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
     99\cline{2-4}
     100\multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
     101\hline
     102Kernel Thread   & 241.5 & 243.86        & 5.08 \\
     103\CFA Coroutine  & 38            & 38            & 0    \\
     104\CFA Thread             & 103           & 102.96        & 2.96 \\
     105\uC Coroutine   & 46            & 45.86 & 0.35 \\
     106\uC Thread              & 98            & 99.11 & 1.42 \\
     107Goroutine               & 150           & 149.96        & 3.16 \\
     108Java Thread             & 289           & 290.68        & 8.72 \\
     109\hline
     110\end{tabular}
     111\end{center}
     112\caption{Context Switch comparison. All numbers are in nanoseconds(\si{\nano\second})}
    109113\label{tab:ctx-switch}
    110 \end{figure}
     114\end{table}
    111115
    112116\subsection{Mutual-exclusion}
    113 The next interesting benchmark is to measure the overhead to enter/leave a critical-section. For monitors, the simplest appraoch is to measure how long it takes enter and leave a monitor routine. Listing \ref{lst:mutex} shows the code for \CFA. To put the results in context, the cost of entering a non-inline function and the cost of acquiring and releasing a pthread mutex lock are also mesured. The results can be shown in table \ref{tab:mutex}.
    114 
    115 \begin{figure}
    116 \begin{cfacode}
     117The next interesting benchmark is to measure the overhead to enter/leave a critical-section. For monitors, the simplest approach is to measure how long it takes to enter and leave a monitor routine. Listing \ref{lst:mutex} shows the code for \CFA. To put the results in context, the cost of entering a non-inline function and the cost of acquiring and releasing a pthread mutex lock are also measured. The results can be shown in table \ref{tab:mutex}.
     118
     119\begin{figure}
     120\begin{cfacode}[caption={\CFA benchmark code used to measure mutex routines.},label={lst:mutex}]
    117121monitor M {};
    118122void __attribute__((noinline)) call( M & mutex m /*, m2, m3, m4*/ ) {}
     
    129133}
    130134\end{cfacode}
    131 \caption{\CFA benchmark code used to measure mutex routines.}
    132 \label{lst:mutex}
    133 \end{figure}
    134 
    135 \begin{figure}
    136 \begin{center}
    137 \begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
    138 \cline{2-4}
    139 \multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
    140 \hline
    141 C routine                                               & 2             & 2             & 0      \\
    142 Pthreads Mutex Lock                             & 31            & 31.86 & 0.99   \\
    143 \uC \code{monitor} member routine               & 30            & 30            & 0      \\
    144 \CFA \code{mutex} routine, 1 argument   & 46            & 46.14 & 0.74  \\
    145 \CFA \code{mutex} routine, 2 argument   & 82            & 83            & 1.93  \\
    146 \CFA \code{mutex} routine, 4 argument   & 165           & 161.15        & 54.04  \\
    147 \hline
    148 \end{tabular}
    149 \end{center}
    150 \caption{Mutex routine comparaison. All numbers are in nanoseconds(\si{\nano\second})}
     135\end{figure}
     136
     137\begin{table}
     138\begin{center}
     139\begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
     140\cline{2-4}
     141\multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
     142\hline
     143C routine                                               & 2             & 2             & 0    \\
     144FetchAdd + FetchSub                             & 26            & 26            & 0    \\
     145Pthreads Mutex Lock                             & 31            & 31.86 & 0.99 \\
     146\uC \code{monitor} member routine               & 30            & 30            & 0    \\
     147\CFA \code{mutex} routine, 1 argument   & 41            & 41.57 & 0.9  \\
     148\CFA \code{mutex} routine, 2 argument   & 76            & 76.96 & 1.57 \\
     149\CFA \code{mutex} routine, 4 argument   & 145           & 146.68        & 3.85 \\
     150Java synchronized routine                       & 27            & 28.57 & 2.6  \\
     151\hline
     152\end{tabular}
     153\end{center}
     154\caption{Mutex routine comparison. All numbers are in nanoseconds(\si{\nano\second})}
    151155\label{tab:mutex}
    152 \end{figure}
     156\end{table}
    153157
    154158\subsection{Internal scheduling}
    155 The Internal scheduling benchmark measures the cost of waiting on and signaling a condition variable. Listing \ref{lst:int-sched} shows the code for \CFA. The results can be shown in table \ref{tab:int-sched}. As with all other benchmarks, all omitted tests are functionally identical to one of these tests.
    156 
    157 \begin{figure}
    158 \begin{cfacode}
     159The internal-scheduling benchmark measures the cost of waiting on and signalling a condition variable. Listing \ref{lst:int-sched} shows the code for \CFA, with results table \ref{tab:int-sched}. As with all other benchmarks, all omitted tests are functionally identical to one of these tests.
     160
     161\begin{figure}
     162\begin{cfacode}[caption={Benchmark code for internal scheduling},label={lst:int-sched}]
    159163volatile int go = 0;
    160164condition c;
     
    187191}
    188192\end{cfacode}
    189 \caption{Benchmark code for internal scheduling}
    190 \label{lst:int-sched}
    191 \end{figure}
    192 
    193 \begin{figure}
    194 \begin{center}
    195 \begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
    196 \cline{2-4}
    197 \multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
    198 \hline
    199 \uC \code{signal}                                       & 322           & 322.57        & 2.77  \\
    200 \CFA \code{signal}, 1 \code{monitor}    & 1145  & 1163.64       & 27.52 \\
    201 \CFA \code{signal}, 2 \code{monitor}    & 1531  & 1550.75       & 32.77 \\
    202 \CFA \code{signal}, 4 \code{monitor}    & 2288.5        & 2326.86       & 54.73 \\
    203 \hline
    204 \end{tabular}
    205 \end{center}
    206 \caption{Internal scheduling comparaison. All numbers are in nanoseconds(\si{\nano\second})}
     193\end{figure}
     194
     195\begin{table}
     196\begin{center}
     197\begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
     198\cline{2-4}
     199\multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
     200\hline
     201\uC \code{signal}                                       & 322           & 323   & 3.36   \\
     202\CFA \code{signal}, 1 \code{monitor}    & 352.5 & 353.11        & 3.66   \\
     203\CFA \code{signal}, 2 \code{monitor}    & 430           & 430.29        & 8.97   \\
     204\CFA \code{signal}, 4 \code{monitor}    & 594.5 & 606.57        & 18.33  \\
     205Java \code{notify}                              & 13831.5       & 15698.21      & 4782.3 \\
     206\hline
     207\end{tabular}
     208\end{center}
     209\caption{Internal scheduling comparison. All numbers are in nanoseconds(\si{\nano\second})}
    207210\label{tab:int-sched}
    208 \end{figure}
     211\end{table}
    209212
    210213\subsection{External scheduling}
    211 The Internal scheduling benchmark measures the cost of the \code{waitfor} statement (\code{_Accept} in \uC). Listing \ref{lst:ext-sched} shows the code for \CFA. The results can be shown in table \ref{tab:ext-sched}. As with all other benchmarks, all omitted tests are functionally identical to one of these tests.
    212 
    213 \begin{figure}
    214 \begin{cfacode}
     214The Internal scheduling benchmark measures the cost of the \code{waitfor} statement (\code{_Accept} in \uC). Listing \ref{lst:ext-sched} shows the code for \CFA, with results in table \ref{tab:ext-sched}. As with all other benchmarks, all omitted tests are functionally identical to one of these tests.
     215
     216\begin{figure}
     217\begin{cfacode}[caption={Benchmark code for external scheduling},label={lst:ext-sched}]
    215218volatile int go = 0;
    216219monitor M {};
     
    242245}
    243246\end{cfacode}
    244 \caption{Benchmark code for external scheduling}
    245 \label{lst:ext-sched}
    246 \end{figure}
    247 
    248 \begin{figure}
    249 \begin{center}
    250 \begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
    251 \cline{2-4}
    252 \multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
    253 \hline
    254 \uC \code{Accept}                                       & 349           & 339.32        & 3.14  \\
    255 \CFA \code{waitfor}, 1 \code{monitor}   & 1155.5        & 1142.04       & 25.23 \\
    256 \CFA \code{waitfor}, 2 \code{monitor}   & 1361  & 1376.75       & 28.81 \\
    257 \CFA \code{waitfor}, 4 \code{monitor}   & 1941.5        & 1957.07       & 34.7  \\
    258 \hline
    259 \end{tabular}
    260 \end{center}
    261 \caption{External scheduling comparaison. All numbers are in nanoseconds(\si{\nano\second})}
     247\end{figure}
     248
     249\begin{table}
     250\begin{center}
     251\begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
     252\cline{2-4}
     253\multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
     254\hline
     255\uC \code{Accept}                                       & 350           & 350.61        & 3.11  \\
     256\CFA \code{waitfor}, 1 \code{monitor}   & 358.5 & 358.36        & 3.82  \\
     257\CFA \code{waitfor}, 2 \code{monitor}   & 422           & 426.79        & 7.95  \\
     258\CFA \code{waitfor}, 4 \code{monitor}   & 579.5 & 585.46        & 11.25 \\
     259\hline
     260\end{tabular}
     261\end{center}
     262\caption{External scheduling comparison. All numbers are in nanoseconds(\si{\nano\second})}
    262263\label{tab:ext-sched}
    263 \end{figure}
     264\end{table}
    264265
    265266\subsection{Object creation}
    266 Finaly, the last benchmark measured is the cost of creation for concurrent objects. Listing \ref{lst:creation} shows the code for pthreads and \CFA threads. The results can be shown in table \ref{tab:creation}. As with all other benchmarks, all omitted tests are functionally identical to one of these tests. The only note here is that the callstacks of \CFA coroutines are lazily created, therefore without priming the coroutine, the creation cost is very low.
    267 
    268 \begin{figure}
    269 \begin{multicols}{2}
     267Finally, the last benchmark measurs the cost of creation for concurrent objects. Listing \ref{lst:creation} shows the code for pthreads and \CFA threads, with results shown in table \ref{tab:creation}. As with all other benchmarks, all omitted tests are functionally identical to one of these tests. The only note here is that the call-stacks of \CFA coroutines are lazily created, therefore without priming the coroutine, the creation cost is very low.
     268
     269\begin{figure}
     270\begin{center}
    270271pthread
    271 \begin{cfacode}
     272\begin{ccode}
    272273int main() {
    273274        BENCH(
    274275                for(size_t i=0; i<n; i++) {
    275276                        pthread_t thread;
    276                         if(pthread_create(
    277                                 &thread,
    278                                 NULL,
    279                                 foo,
    280                                 NULL
    281                         ) < 0) {
     277                        if(pthread_create(&thread,NULL,foo,NULL)<0) {
    282278                                perror( "failure" );
    283279                                return 1;
    284280                        }
    285281
    286                         if(pthread_join(
    287                                 thread,
    288                                 NULL
    289                         ) < 0) {
     282                        if(pthread_join(thread, NULL)<0) {
    290283                                perror( "failure" );
    291284                                return 1;
     
    296289        printf("%llu\n", result);
    297290}
    298 \end{cfacode}
    299 \columnbreak
     291\end{ccode}
     292
     293
     294
    300295\CFA Threads
    301296\begin{cfacode}
     
    307302                result
    308303        )
    309 
    310         printf("%llu\n", result);
    311 }
    312 \end{cfacode}
    313 \end{multicols}
    314 \caption{Bechmark code for pthreads and \CFA to measure object creation}
    315 \label{lst:creation}
    316 \end{figure}
    317 
    318 \begin{figure}
    319 \begin{center}
    320 \begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
    321 \cline{2-4}
    322 \multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
    323 \hline
    324 Pthreads                        & 26974.5       & 26977 & 124.12 \\
    325 \CFA Coroutines Lazy    & 5             & 5             & 0      \\
    326 \CFA Coroutines Eager   & 335.0 & 357.67        & 34.2   \\
    327 \CFA Threads            & 1122.5        & 1109.86       & 36.54  \\
    328 \uC Coroutines          & 106           & 107.04        & 1.61   \\
    329 \uC Threads                     & 525.5 & 533.04        & 11.14  \\
    330 \hline
    331 \end{tabular}
    332 \end{center}
    333 \caption{Creation comparaison. All numbers are in nanoseconds(\si{\nano\second})}
     304        printf("%llu\n", result);
     305}
     306\end{cfacode}
     307\end{center}
     308\begin{cfacode}[caption={Benchmark code for pthreads and \CFA to measure object creation},label={lst:creation}]
     309\end{cfacode}
     310\end{figure}
     311
     312\begin{table}
     313\begin{center}
     314\begin{tabular}{| l | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] | S[table-format=5.2,table-number-alignment=right] |}
     315\cline{2-4}
     316\multicolumn{1}{c |}{} & \multicolumn{1}{c |}{ Median } &\multicolumn{1}{c |}{ Average } & \multicolumn{1}{c |}{ Standard Deviation} \\
     317\hline
     318Pthreads                        & 26996 & 26984.71      & 156.6  \\
     319\CFA Coroutine Lazy     & 6             & 5.71  & 0.45   \\
     320\CFA Coroutine Eager    & 708           & 706.68        & 4.82   \\
     321\CFA Thread                     & 1173.5        & 1176.18       & 15.18  \\
     322\uC Coroutine           & 109           & 107.46        & 1.74   \\
     323\uC Thread                      & 526           & 530.89        & 9.73   \\
     324Goroutine                       & 2520.5        & 2530.93       & 61,56  \\
     325Java Thread                     & 91114.5       & 92272.79      & 961.58 \\
     326\hline
     327\end{tabular}
     328\end{center}
     329\caption{Creation comparison. All numbers are in nanoseconds(\si{\nano\second})}
    334330\label{tab:creation}
    335 \end{figure}
     331\end{table}
  • doc/proposals/concurrency/text/together.tex

    r875a72f r35bae526  
    77
    88\section{Threads as monitors}
    9 As it was subtely alluded in section \ref{threads}, \code{threads} in \CFA are in fact monitors, which means that all monitor features are available when using threads. For example, here is a very simple two thread pipeline that could be used for a simulator of a game engine :
    10 \begin{cfacode}
     9As it was subtly alluded in section \ref{threads}, \code{thread}s in \CFA are in fact monitors, which means that all monitor features are available when using threads. For example, here is a very simple two thread pipeline that could be used for a simulator of a game engine :
     10\begin{figure}[H]
     11\begin{cfacode}[caption={Toy simulator using \code{thread}s and \code{monitor}s.},label={lst:engine-v1}]
    1112// Visualization declaration
    1213thread Renderer {} renderer;
     
    2021void draw( Renderer & mutex this, Frame * frame );
    2122
    22 // Simualation loop
     23// Simulation loop
    2324void main( Simulator & this ) {
    2425        while( true ) {
     
    3637}
    3738\end{cfacode}
     39\end{figure}
    3840One of the obvious complaints of the previous code snippet (other than its toy-like simplicity) is that it does not handle exit conditions and just goes on forever. Luckily, the monitor semantics can also be used to clearly enforce a shutdown order in a concise manner :
    39 \begin{cfacode}
     41\begin{figure}[H]
     42\begin{cfacode}[caption={Same toy simulator with proper termination condition.},label={lst:engine-v2}]
    4043// Visualization declaration
    4144thread Renderer {} renderer;
     
    4952void draw( Renderer & mutex this, Frame * frame );
    5053
    51 // Simualation loop
     54// Simulation loop
    5255void main( Simulator & this ) {
    5356        while( true ) {
     
    7679// Call destructor for renderer to signify shutdown
    7780\end{cfacode}
     81\end{figure}
    7882
    7983\section{Fibers \& Threads}
    80 As mentionned in section \ref{preemption}, \CFA uses preemptive threads by default but can use fibers on demand. Currently, using fibers is done by adding the following line of code to the program~:
     84As mentioned in section \ref{preemption}, \CFA uses preemptive threads by default but can use fibers on demand. Currently, using fibers is done by adding the following line of code to the program~:
    8185\begin{cfacode}
    8286unsigned int default_preemption() {
     
    8488}
    8589\end{cfacode}
    86 This function is called by the kernel to fetch the default preemption rate, where 0 signifies an infinite time-slice i.e. no preemption. However, once clusters are fully implemented, it will be possible to create fibers and uthreads in on the same system :
     90This function is called by the kernel to fetch the default preemption rate, where 0 signifies an infinite time-slice, i.e., no preemption. However, once clusters are fully implemented, it will be possible to create fibers and \glspl{uthread} in the same system, as in listing \ref{lst:fiber-uthread}
    8791\begin{figure}
    88 \begin{cfacode}
     92\begin{cfacode}[caption={Using fibers and \glspl{uthread} side-by-side in \CFA},label={lst:fiber-uthread}]
    8993//Cluster forward declaration
    9094struct cluster;
  • doc/proposals/concurrency/thesis.tex

    r875a72f r35bae526  
    8282\rfoot{v\input{version}}
    8383
    84 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    8584
     85
     86%======================================================================
     87%   L O G I C A L    D O C U M E N T -- the content of your thesis
     88%======================================================================
    8689\begin{document}
    87 % \linenumbers
    8890
    89 \title{Concurrency in \CFA}
    90 \author{Thierry Delisle \\
    91 School of Computer Science, University of Waterloo, \\ Waterloo, Ontario, Canada
    92 }
     91% For a large document, it is a good idea to divide your thesis
     92% into several files, each one containing one chapter.
     93% To illustrate this idea, the "front pages" (i.e., title page,
     94% declaration, borrowers' page, abstract, acknowledgements,
     95% dedication, table of contents, list of tables, list of figures,
     96% nomenclature) are contained within the file "thesis-frontpgs.tex" which is
     97% included into the document by the following statement.
     98%----------------------------------------------------------------------
     99% FRONT MATERIAL
     100%----------------------------------------------------------------------
     101\input{frontpgs}
    93102
    94 \maketitle
    95 
    96 \tableofcontents
     103%----------------------------------------------------------------------
     104% MAIN BODY
     105%----------------------------------------------------------------------
    97106
    98107\input{intro}
     
    114123\input{future}
    115124
    116 \chapter{Conclusion}
    117 
    118 \section*{Acknowledgements}
    119 
    120125\clearpage
    121126\printglossary[type=\acronymtype]
  • doc/proposals/concurrency/version

    r875a72f r35bae526  
    1 0.11.129
     10.11.280
  • src/GenPoly/InstantiateGeneric.cc

    r875a72f r35bae526  
    2121#include <vector>                      // for vector
    2222
     23#include "CodeGen/OperatorTable.h"
    2324#include "Common/PassVisitor.h"        // for PassVisitor, WithDeclsToAdd
    2425#include "Common/ScopedMap.h"          // for ScopedMap
     
    2728#include "Common/utility.h"            // for deleteAll, cloneAll
    2829#include "GenPoly.h"                   // for isPolyType, typesPolyCompatible
     30#include "InitTweak/InitTweak.h"
    2931#include "ResolvExpr/typeops.h"
    3032#include "ScopedSet.h"                 // for ScopedSet, ScopedSet<>::iterator
     
    154156
    155157        /// Add cast to dtype-static member expressions so that type information is not lost in GenericInstantiator
    156         struct FixDtypeStatic final {
     158        struct FixDtypeStatic final : public WithGuards, public WithVisitorRef<FixDtypeStatic>, public WithShortCircuiting, public WithStmtsToAdd {
    157159                Expression * postmutate( MemberExpr * memberExpr );
     160
     161                void premutate( ApplicationExpr * appExpr );
     162                void premutate( AddressExpr * addrExpr );
    158163
    159164                template<typename AggrInst>
    160165                Expression * fixMemberExpr( AggrInst * inst, MemberExpr * memberExpr );
     166
     167                bool isLvalueArg = false;
    161168        };
    162169
     
    210217                PassVisitor<GenericInstantiator> instantiator;
    211218
    212                 // mutateAll( translationUnit, fixer );
     219                mutateAll( translationUnit, fixer );
    213220                mutateAll( translationUnit, instantiator );
    214221        }
     
    501508                if ( isDtypeStatic( baseParams ) ) {
    502509                        if ( ! ResolvExpr::typesCompatible( memberExpr->result, memberExpr->member->get_type(), SymTab::Indexer() ) ) {
    503                                 // type of member and type of expression differ, so add cast to actual type
    504                                 return new CastExpr( memberExpr, memberExpr->result->clone() );
     510                                // type of member and type of expression differ
     511                                Type * concType = memberExpr->result->clone();
     512                                if ( isLvalueArg ) {
     513                                        // result must be C lvalue, so make a new reference variable with the correct actual type to replace the member expression
     514                                        //   forall(dtype T)
     515                                        //   struct Ptr {
     516                                        //     T * x
     517                                        //   };
     518                                        //   Ptr(int) p;
     519                                        //   int i;
     520                                        //   p.x = &i;
     521                                        // becomes
     522                                        //   int *& _dtype_static_member_0 = (int **)&p.x;
     523                                        //   _dtype_static_member_0 = &i;
     524                                        // Note: this currently creates more temporaries than is strictly necessary, since it does not check for duplicate uses of the same member expression.
     525                                        static UniqueName tmpNamer( "_dtype_static_member_" );
     526                                        Expression * init = new CastExpr( new AddressExpr( memberExpr ), new PointerType( Type::Qualifiers(), concType->clone() ) );
     527                                        ObjectDecl * tmp = ObjectDecl::newObject( tmpNamer.newName(), new ReferenceType( Type::Qualifiers(), concType ), new SingleInit( init ) );
     528                                        stmtsToAddBefore.push_back( new DeclStmt( noLabels, tmp ) );
     529                                        return new VariableExpr( tmp );
     530                                } else {
     531                                        // can simply add a cast to actual type
     532                                        return new CastExpr( memberExpr, concType );
     533                                }
    505534                        }
    506535                }
     
    520549        }
    521550
     551        void FixDtypeStatic::premutate( ApplicationExpr * appExpr ) {
     552                GuardValue( isLvalueArg );
     553                isLvalueArg = false;
     554                DeclarationWithType * function = InitTweak::getFunction( appExpr );
     555                if ( function->linkage == LinkageSpec::Intrinsic && CodeGen::isAssignment( function->name ) ) {
     556                        // explicitly visit children because only the first argument must be a C lvalue.
     557                        visit_children = false;
     558                        appExpr->env = maybeMutate( appExpr->env, *visitor );
     559                        appExpr->result = maybeMutate( appExpr->result, *visitor );
     560                        appExpr->function = maybeMutate( appExpr->function, *visitor );
     561                        isLvalueArg = true;
     562                        for ( Expression * arg : appExpr->args ) {
     563                                arg = maybeMutate( arg, *visitor );
     564                                isLvalueArg = false;
     565                        }
     566                }
     567        }
     568
     569        void FixDtypeStatic::premutate( AddressExpr * ) {
     570                // argument of & must be C lvalue
     571                GuardValue( isLvalueArg );
     572                isLvalueArg = true;
     573        }
    522574} // namespace GenPoly
    523575
  • src/ResolvExpr/AlternativeFinder.cc

    r875a72f r35bae526  
    897897                // sum cost and accumulate actuals
    898898                std::list<Expression*>& args = appExpr->get_args();
    899                 Cost cost = Cost::zero;
     899                Cost cost = func.cost;
    900900                const ArgPack* pack = &result;
    901901                while ( pack->expr ) {
  • src/SynTree/Expression.cc

    r875a72f r35bae526  
    356356        Type * res = member->get_type()->clone();
    357357        sub.apply( res );
    358         set_result( res );
    359         get_result()->set_lvalue( true );
     358        result = res;
     359        result->set_lvalue( true );
     360        result->get_qualifiers() |= aggregate->result->get_qualifiers();
    360361}
    361362
Note: See TracChangeset for help on using the changeset viewer.