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  • doc/proposals/concurrency/text/basics.tex

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    3 \chapter{Concurrency Basics}\label{basics}
     3\chapter{Basics}\label{basics}
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    6 Before any detailed discussion of the concurrency and parallelism in \CFA, it is important to describe the basics of concurrency and how they are expressed in \CFA user-code.
     6Before any detailed discussion of the concurrency and parallelism in \CFA, it is important to describe the basics of concurrency and how they are expressed in \CFA user code.
    77
    88\section{Basics of concurrency}
    9 At its core, concurrency is based on having multiple call-stacks and scheduling among threads of execution executing on these stacks. Concurrency without parallelism only requires having multiple call stacks (or contexts) for a single thread of execution.
    10 
    11 Indeed, while execution 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.
    12 
    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 \cit. 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. Indeed, concurrency challenges appear with non-determinism. Using mutual-exclusion or synchronisation are ways of limiting the lack of determinism in a system. A scheduler introduces order of execution uncertainty, while preemption introduces uncertainty about where context-switches occur. Now it is important to understand that uncertainty is not undesireable; uncertainty can often be used by 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\cit.
     9At its core, concurrency is based on having call-stacks and potentially multiple threads of execution for these stacks. Concurrency without parallelism only requires having multiple call stacks (or contexts) for a single thread of execution, and switching between these call stacks on a regular basis. A minimal concurrency product can be achieved by creating coroutines, which instead of context switching between each other, always ask an oracle where to context switch next. While coroutines do not technically require a stack, stackfull coroutines are the closest abstraction to a practical "naked"" call stack. When writing concurrency in terms of coroutines, the oracle effectively becomes a scheduler and the whole system now follows a cooperative threading-model \cit. 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. Indeed, concurrency challenges appear with non-determinism. Guaranteeing mutual-exclusion or synchronisation are simply ways of limiting the lack of determinism in a system. A scheduler introduces order of execution uncertainty, while preemption introduces incertainty about where context-switches occur. Now it is important to understand that uncertainty is not necessarily undesireable; uncertainty can often be used by 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\cit.
    1410
    1511\section{\protect\CFA 's Thread Building Blocks}
    16 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 and/or parallel programs. 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.
     12One of the important features that is missing in C is threading. On modern architectures, a lack of threading is becoming less and less forgivable\cite{Sutter05, Sutter05b}, and therefore modern programming languages must have the proper tools to allow users to write performant concurrent and/or parallel programs. As an extension of C, \CFA needs to express these concepts in a way that is as natural as possible to programmers used to 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.
    1713
    1814\section{Coroutines: A stepping stone}\label{coroutine}
    19 While 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-switchs 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}.
    20 
    21 A good example of a problem made easier with coroutines is genereting the fibonacci sequence. This problem comes with the challenge of decoupling how a sequence is generated and how it is used. Figure \ref{fig: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 will be used, while the rightmost approach requires to user to hold internal state between calls on behalf of th sequence generator and makes it much harder to handle corner cases like the Fibonacci seed.
    22 \begin{figure}
    23 \label{fig:fibonacci-c}
    24 \caption{Different implementations of a fibonacci sequence generator in C.}
    25 \begin{center}
    26 \begin{tabular}{c @{\hskip 0.025in}|@{\hskip 0.025in} c @{\hskip 0.025in}|@{\hskip 0.025in} c}
    27 \begin{ccode}[tabsize=2]
    28 //Using callbacks
    29 void fibonacci_func(
    30         int n,
    31         void (*callback)(int)
    32 ) {
    33         int first = 0;
    34         int second = 1;
    35         int next, i;
    36         for(i = 0; i < n; i++)
    37         {
    38                 if(i <= 1)
    39                         next = i;
    40                 else {
    41                         next = f1 + f2;
    42                         f1 = f2;
    43                         f2 = next;
    44                 }
    45                 callback(next);
    46         }
    47 }
    48 \end{ccode}&\begin{ccode}[tabsize=2]
    49 //Using output array
    50 void fibonacci_array(
    51         int n,
    52         int * array
    53 ) {
    54         int f1 = 0; int f2 = 1;
    55         int next, i;
    56         for(i = 0; i < n; i++)
    57         {
    58                 if(i <= 1)
    59                         next = i;
    60                 else {
    61                         next = f1 + f2;
    62                         f1 = f2;
    63                         f2 = next;
    64                 }
    65                 *array = next;
    66                 array++;
    67         }
    68 }
    69 \end{ccode}&\begin{ccode}[tabsize=2]
    70 //Using external state
    71 typedef struct {
    72         int f1, f2;
    73 } iterator_t;
    74 
    75 int fibonacci_state(
    76         iterator_t * it
    77 ) {
    78         int f;
    79         f = it->f1 + it->f2;
    80         it->f2 = it->f1;
    81         it->f1 = f;
    82         return f;
    83 }
    84 
    85 
    86 
    87 
    88 
    89 
    90 \end{ccode}
    91 \end{tabular}
    92 \end{center}
    93 \end{figure}
    94 
    95 
    96 Figure \ref{fig:fibonacci-cfa} is an example of a solution to the fibonnaci problem using \CFA coroutines, using the coroutine stack to hold 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 a easy to use as the \code{fibonacci_state} solution, while the imlpementation is very similar to the \code{fibonacci_func} example.
    97 
    98 \begin{figure}
    99 \label{fig:fibonacci-cfa}
    100 \caption{Implementation of fibonacci using coroutines}
    101 \begin{cfacode}
    102 coroutine Fibonacci {
    103         int fn; //used for communication
    104 };
    105 
    106 void ?{}(Fibonacci & this) { //constructor
    107         this.fn = 0;
    108 }
    109 
    110 //main automacically called on first resume
    111 void main(Fibonacci & this) {
    112         int fn1, fn2;           //retained between resumes
    113         this.fn = 0;
    114         fn1 = this.fn;
    115         suspend(this);          //return to last resume
    116 
    117         this.fn = 1;
    118         fn2 = fn1;
    119         fn1 = this.fn;
    120         suspend(this);          //return to last resume
    121 
    122         for ( ;; ) {
    123                 this.fn = fn1 + fn2;
     15While the main focus of this proposal is concurrency and parallelism, as mentionned above it is important to adress coroutines, which are actually a significant underlying aspect of a concurrency system. Indeed, while having nothing to do with parallelism and arguably little to do with concurrency, coroutines need to deal with context-switchs 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 API of coroutines revolve around two features: independent call stacks and \code{suspend}/\code{resume}.
     16
     17Here is an example of a solution to the fibonnaci problem using \CFA coroutines:
     18\begin{cfacode}
     19        coroutine Fibonacci {
     20              int fn; // used for communication
     21        };
     22
     23        void ?{}(Fibonacci & this) { // constructor
     24              this.fn = 0;
     25        }
     26
     27        // main automacically called on first resume
     28        void main(Fibonacci & this) {
     29                int fn1, fn2;           // retained between resumes
     30                this.fn = 0;
     31                fn1 = this.fn;
     32                suspend(this);          // return to last resume
     33
     34                this.fn = 1;
    12435                fn2 = fn1;
    12536                fn1 = this.fn;
    126                 suspend(this);  //return to last resume
    127         }
    128 }
    129 
    130 int next(Fibonacci & this) {
    131         resume(this); //transfer to last suspend
    132         return this.fn;
    133 }
    134 
    135 void main() { //regular program main
    136         Fibonacci f1, f2;
    137         for ( int i = 1; i <= 10; i += 1 ) {
    138                 sout | next( f1 ) | next( f2 ) | endl;
    139         }
    140 }
    141 \end{cfacode}
    142 \end{figure}
     37                suspend(this);          // return to last resume
     38
     39                for ( ;; ) {
     40                        this.fn = fn1 + fn2;
     41                        fn2 = fn1;
     42                        fn1 = this.fn;
     43                        suspend(this);  // return to last resume
     44                }
     45        }
     46
     47        int next(Fibonacci & this) {
     48                resume(this); // transfer to last suspend
     49                return this.fn;
     50        }
     51
     52        void main() { // regular program main
     53                Fibonacci f1, f2;
     54                for ( int i = 1; i <= 10; i += 1 ) {
     55                        sout | next( f1 ) | next( f2 ) | endl;
     56                }
     57        }
     58\end{cfacode}
    14359
    14460\subsection{Construction}
    145 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 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.
    146 
    147 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.
     61One 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. 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.
     62
     63The 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. Like for regular objects, constructors can still leak coroutines before they are ready. There are several solutions to this problem but the chosen options effectively forces the design of the coroutine.
    14864
    14965Furthermore, \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:
    … …  
    16278}
    16379\end{cfacode}
    164 
    16580The generated C code\footnote{Code trimmed down for brevity} creates a local thunk to hold type information:
    16681
    … …  
    18095}
    18196\end{ccode}
    182 The problem in this example is a storage management issue, the function pointer \code{_thunk0} is only valid until the end of the block. This extra challenge limits which solutions are viable because storing the function pointer for too long causes undefined behavior; i.e. the stack based thunk being destroyed before it was used. This challenge is an extension of challenges that come with second-class routines. Indeed, GCC nested routines also have the limitation that the routines cannot be passed outside of the scope of the functions these were declared in. The case of coroutines and threads is simply an extension of this problem to multiple call-stacks.
     97The problem in this example is a race condition between the start of the execution of \code{noop} on the other thread and the stack frame of \code{bar} being destroyed. This extra challenge limits which solutions are viable because storing the function pointer for too long only increases the chances that the race will end in undefined behavior; i.e. the stack based thunk being destroyed before it was used. This challenge is an extension of challenges that come with second-class routines. Indeed, GCC nested routines also have the limitation that the routines cannot be passed outside of the scope of the functions these were declared in. The case of coroutines and threads is simply an extension of this problem to multiple call-stacks.
    18398
    18499\subsection{Alternative: Composition}
    185 One solution to this challenge is to use composition/containement, where uses add insert a coroutine field which contains the necessary information to manage the coroutine.
    186 
    187 \begin{cfacode}
    188 struct Fibonacci {
    189         int fn; //used for communication
    190         coroutine c; //composition
    191 };
    192 
    193 void ?{}(Fibonacci & this) {
    194         this.fn = 0;
    195         (this.c){}; //Call constructor to initialize coroutine
    196 }
    197 \end{cfacode}
    198 There are two downsides to this approach. The first, which is relatively minor, made aware of the main routine pointer. This information must either be store in the coroutine runtime data or in its static type structure. When using composition, all coroutine handles have the same static type structure which means the pointer to the main needs to be part of the runtime data. This requirement means the coroutine data must be made larger to store a value that is actually a compile time constant (address of the main routine). The second problem, which is both subtle and significant, is that now users can get the initialisation order of coroutines wrong. Indeed, every field of a \CFA struct is constructed but in declaration order, unless users explicitly write otherwise. This semantics means that users who forget to initialize the coroutine handle may resume the coroutine with an uninitilized object. For coroutines, this is unlikely to be a problem, for threads however, this is a significant problem. Figure \ref{fig:fmt-line} shows the \code{Format} coroutine which rearranges text in order to group characters into blocks of fixed size. This is a good example where the control flow is made much simpler from being able to resume the coroutine from the constructor and highlights the idea that interesting control flow can occor in the constructor.
    199 \begin{figure}
    200 \label{fig:fmt-line}
    201 \caption{Formatting text into lines of 5 blocks of 4 characters.}
    202 \begin{cfacode}[tabsize=3]
    203 //format characters into blocks of 4 and groups of 5 blocks per line
    204 coroutine Format {
    205         char ch;                                                                        //used for communication
    206         int g, b;                                                               //global because used in destructor
    207 };
    208 
    209 void  ?{}(Format & fmt) {
    210         resume( fmt );                                                  //prime (start) coroutine
    211 }
    212 
    213 void ^?{}(Format & fmt) with fmt {
    214         if ( fmt.g != 0 || fmt.b != 0 )
    215         sout | endl;
    216 }
    217 
    218 void main(Format & fmt) with fmt {
    219         for ( ;; ) {                                                    //for as many characters
    220                 for(g = 0; g < 5; g++) {                //groups of 5 blocks
    221                         for(b = 0; b < 4; fb++) {       //blocks of 4 characters
    222                                 suspend();
    223                                 sout | ch;                                      //print character
    224                         }
    225                         sout | "  ";                                    //print block separator
    226                 }
    227                 sout | endl;                                            //print group separator
    228         }
    229 }
    230 
    231 void prt(Format & fmt, char ch) {
    232         fmt.ch = ch;
    233         resume(fmt);
    234 }
    235 
    236 int main() {
    237         Format fmt;
    238         char ch;
    239         Eof: for ( ;; ) {                                               //read until end of file
    240                 sin | ch;                                                       //read one character
    241                 if(eof(sin)) break Eof;                 //eof ?
    242                 prt(fmt, ch);                                           //push character for formatting
    243         }
    244 }
    245 \end{cfacode}
    246 \end{figure}
    247 
     100One solution to this challenge would be to use composition/containement,
     101
     102\begin{cfacode}
     103        struct Fibonacci {
     104              int fn; // used for communication
     105              coroutine c; //composition
     106        };
     107
     108        void ?{}(Fibonacci & this) {
     109              this.fn = 0;
     110                (this.c){};
     111        }
     112\end{cfacode}
     113There are two downsides to this approach. The first, which is relatively minor, is that the base class needs to be made aware of the main routine pointer, regardless of whether a parameter or a virtual pointer is used, this means the coroutine data must be made larger to store a value that is actually a compile time constant (address of the main routine). The second problem, which is both subtle and significant, is that now users can get the initialisation order of there coroutines wrong. Indeed, every field of a \CFA struct is constructed but in declaration order, unless users explicitly write otherwise. This semantics means that users who forget to initialize a the coroutine may resume the coroutine with an uninitilized object. For coroutines, this is unlikely to be a problem, for threads however, this is a significant problem.
    248114
    249115\subsection{Alternative: Reserved keyword}
    … …  
    251117
    252118\begin{cfacode}
    253 coroutine Fibonacci {
    254         int fn; //used for communication
    255 };
    256 \end{cfacode}
    257 This mean the compiler can solve problems by injecting code where needed. The downside of this approach is that it makes coroutine a special case in the language. Users who would want 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 both be constructed by users without using the language support. The reserved keywords are only present to improve ease of use for the common cases.
     119        coroutine Fibonacci {
     120              int fn; // used for communication
     121        };
     122\end{cfacode}
     123This mean the compiler can solve problems by injecting code where needed. The downside of this approach is that it makes coroutine a special case in the language. Users who would want 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 \CFA.
     124While this is ultimately the option used for idiomatic \CFA code, coroutines and threads can both be constructed by users without using the language support. The reserved keywords are only present to improve ease of use for the common cases.
    258125
    259126\subsection{Alternative: Lamda Objects}
    … …  
    292159      coroutine_desc * get_coroutine(T & this);
    293160};
    294 
    295 forall( dtype T | is_coroutine(T) ) void suspend(T &);
    296 forall( dtype T | is_coroutine(T) ) void resume (T &);
    297 \end{cfacode}
    298 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.
     161\end{cfacode}
     162This ensures an object is not a coroutine until \code{resume} (or \code{prime}) 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 foot print 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.
    299163
    300164\begin{center}
    … …  
    322186\end{center}
    323187
    324 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.
     188The combination of these two approaches allows users new to concurrency to have a easy and concise method while more advanced users can expose themselves to otherwise hidden pitfalls at the benefit of tighter control on memory layout and initialization.
    325189
    326190\section{Thread Interface}\label{threads}
    … …  
    341205\end{cfacode}
    342206
    343 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
     207Obviously, 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 possible naturally extend 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
    344208\begin{cfacode}
    345209        thread foo {};
    … …  
    350214\end{cfacode}
    351215
    352 In this example, threads of type \code{foo} start execution in the \code{void main(foo &)} routine, which prints \code{"Hello World!"}. While this thesis encourages this approach to enforce strongly-typed programming, users may prefer to use the routine-based thread semantics for the sake of simplicity. With these semantics it is trivial to write a thread type that takes a function pointer as a parameter and executes it on its stack asynchronously
    353 \begin{cfacode}
    354         typedef void (*voidFunc)(int);
     216In this example, threads of type \code{foo} start execution in the \code{void main(foo*)} routine which prints \code{"Hello World!"}. While this proposoal encourages this approach to enforce strongly-typed programming, users may prefer to use the routine based thread semantics for the sake of simplicity. With these semantics it is trivial to write a thread type that takes a function pointer as parameter and executes it on its stack asynchronously
     217\begin{cfacode}
     218        typedef void (*voidFunc)(void);
    355219
    356220        thread FuncRunner {
    357221                voidFunc func;
    358                 int arg;
    359222        };
    360223
    361         void ?{}(FuncRunner & this, voidFunc inFunc, int arg) {
     224        //ctor
     225        void ?{}(FuncRunner & this, voidFunc inFunc) {
    362226                this.func = inFunc;
    363227        }
    364228
     229        //main
    365230        void main(FuncRunner & this) {
    366                 this.func( this.arg );
    367         }
    368 \end{cfacode}
    369 
    370 An consequence of the strongly typed approach to main is that memory layout of parameters and return values to/from a thread are now explicitly specified in the \acrshort{api}.
    371 
    372 Of course for threads to be useful, it must be possible to start and stop threads and wait for them to complete execution. While using an \acrshort{api} such as \code{fork} and \code{join} is relatively common in the literature, such an interface is unnecessary. Indeed, the simplest approach is to use \acrshort{raii} principles and have threads \code{fork} after the constructor has completed and \code{join} before the destructor runs.
     231                this.func();
     232        }
     233\end{cfacode}
     234
     235An advantage of the overloading approach to main is to clearly highlight where and what memory is required to pass parameters and return values to/from a thread.
     236
     237Of course for threads to be useful, it must be possible to start and stop threads and wait for them to complete execution. While using an \acrshort{api} such as \code{fork} and \code{join} is relatively common in the literature, such an interface is unnecessary. Indeed, the simplest approach is to use \acrshort{raii} principles and have threads \code{fork} once the constructor has completed and \code{join} before the destructor runs.
    373238\begin{cfacode}
    374239thread World;
    … …  
    389254\end{cfacode}
    390255
    391 This semantic has several advantages over explicit semantics: a thread is always started and stopped exaclty once and users cannot make any progamming errors and it naturally scales to multiple threads meaning basic synchronisation is very simple
     256This semantic has several advantages over explicit semantics typesafety is guaranteed, a thread is always started and stopped exaclty once and users cannot make any progamming errors. Another advantage of this semantic is that it naturally scale to multiple threads meaning basic synchronisation is very simple
    392257
    393258\begin{cfacode}
    … …  
    411276\end{cfacode}
    412277
    413 However, one of the drawbacks of this approach is that threads now always form a lattice, that is they are always destroyed in 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
     278However, one of the apparent drawbacks of this system is that threads now always form a lattice, that is they are always destroyed in opposite order of construction because of block structure. However, storage allocation is not limited to blocks; dynamic allocation can create threads that outlive the scope in which the thread is created much like dynamically allocating memory lets objects outlive the scope in which they are created
    414279
    415280\begin{cfacode}
    … …  
    418283};
    419284
     285//main
    420286void main(MyThread & this) {
    421287        //...
    … …  
    425291        MyThread * long_lived;
    426292        {
     293                MyThread short_lived;
    427294                //Start a thread at the beginning of the scope
    428                 MyThread short_lived;
     295
     296                DoStuff();
    429297
    430298                //create another thread that will outlive the thread in this scope
    431299                long_lived = new MyThread;
    432300
    433                 DoStuff();
    434 
    435301                //Wait for the thread short_lived to finish
    436302        }
    437303        DoMoreStuff();
    438304
    439         //Now wait for the long_lived to finish
     305        //Now wait for the short_lived to finish
    440306        delete long_lived;
    441307}
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