Changeset 27dde72 for doc/proposals/concurrency/thesis.tex
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- May 29, 2017, 1:39:37 PM (7 years ago)
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doc/proposals/concurrency/thesis.tex
reb182b0 r27dde72 20 20 \usepackage{epic,eepic} 21 21 \usepackage{upquote} % switch curled `'" to straight 22 \usepackage{dirtytalk} 22 23 \usepackage{calc} 23 24 \usepackage{xspace} … … 61 62 \newcommand{\uC}{$\mu$\CC} 62 63 \newcommand{\cit}{\textsuperscript{[Citation Needed]}\xspace} 63 \newcommand{\code}[1]{\lstinline[language=CFA]{#1}}64 \newcommand{\pscode}[1]{\lstinline[language=pseudo]{#1}}65 64 \newcommand{\TODO}{{\Textbf{TODO}}} 66 65 … … 71 70 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 72 71 73 \setcounter{secnumdepth}{3} 74 \setcounter{tocdepth}{3} 75 % \linenumbers 72 \setcounter{secnumdepth}{3} % number subsubsections 73 \setcounter{tocdepth}{3} % subsubsections in table of contents 74 % \linenumbers % comment out to turn off line numbering 76 75 \makeindex 77 76 \pagestyle{fancy} 78 77 \fancyhf{} 79 78 \cfoot{\thepage} 80 \rfoot{v\input{ version}}79 \rfoot{v\input{build/version}} 81 80 82 81 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% … … 92 91 \maketitle 93 92 94 % ### # # ####### ###### ####### 95 % # ## # # # # # # 96 % # # # # # # # # # 97 % # # # # # ###### # # 98 % # # # # # # # # # 99 % # # ## # # # # # 100 % ### # # # # # ####### 93 \tableofcontents 101 94 102 \chapter{Introduction} 103 This proposal provides a minimal core concurrency API that is both simple, efficient and can be reused to build higher-level features. The simplest possible concurrency core is a thread and a lock but this low-level approach is hard to master. An easier approach for users is to support higher-level constructs as the basis of the concurrency in \CFA. Indeed, for highly productive parallel programming, high-level approaches are much more popular~\cite{HPP:Study}. Examples are task based, message passing and implicit threading. 95 \input{intro} 104 96 105 There are actually two problems that need to be solved in the design of the concurrency for a programming language: which concurrency tools are available to the users and which parallelism tools are available. While these two concepts are often seen together, they are in fact distinct concepts that require different sorts of tools~\cite{Buhr05a}. Concurrency tools need to handle mutual exclusion and synchronization, while parallelism tools are more about performance, cost and resource utilization. 97 \input{basics} 106 98 107 % ##### ####### # # ##### # # ###### ###### ####### # # ##### # # 108 % # # # # ## # # # # # # # # # # ## # # # # # 109 % # # # # # # # # # # # # # # # # # # # # 110 % # # # # # # # # # ###### ###### ##### # # # # # 111 % # # # # # # # # # # # # # # # # # # # 112 % # # # # # ## # # # # # # # # # # ## # # # 113 % ##### ####### # # ##### ##### # # # # ####### # # ##### # 99 \input{concurrency} 114 100 115 \chapter{Concurrency} 116 Several tool can be used to solve concurrency challenges. Since these challenges always 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 that closely relate to networking concepts (channels\cit 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). Which in turn means that, in order to be effective, programmers need to learn two sets of designs patterns. This distinction can be hidden away in library code, but effective use of the librairy still has to take both paradigms into account. Approaches based on shared memory are more closely related to non-concurrent paradigms since they often rely on basic constructs like routine calls and objects. At a lower level these can be implemented as locks and atomic operations. 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}. An approach that is worth mentionning because it is gaining in popularity is transactionnal memory~\cite{Dice10}[Check citation]. While this approach is even pursued by system languages like \CC\cit, the performance and feature set is currently too restrictive to add such a paradigm to a language like C or \CC\cit, which is why it was rejected as the core paradigm for concurrency in \CFA. One 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. 101 \input{parallelism} 117 102 118 % # # ####### # # ### ####### ####### ###### #####119 % ## ## # # ## # # # # # # # # #120 % # # # # # # # # # # # # # # # #121 % # # # # # # # # # # # # ###### #####122 % # # # # # # # # # # # # # #123 % # # # # # ## # # # # # # # #124 % # # ####### # # ### # ####### # # #####125 126 \section{Monitors}127 A monitor is a set of routines that ensure mutual exclusion when accessing shared state. This concept is generally associated with Object-Oriented Languages like Java~\cite{Java} or \uC~\cite{uC++book} but does not strictly require OOP semantics. The only requirements is the ability to declare a handle to a shared object and a set of routines that act on it :128 \begin{cfacode}129 typedef /*some monitor type*/ monitor;130 int f(monitor & m);131 132 int main() {133 monitor m;134 f(m);135 }136 \end{cfacode}137 138 % ##### # # #139 % # # # # # #140 % # # # # #141 % # # # # #142 % # ####### # #143 % # # # # # #144 % ##### # # ####### #######145 146 \subsection{Call semantics} \label{call}147 The above monitor example displays some of the intrinsic characteristics. Indeed, 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.148 149 Another 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 be both generic helper routines (\code{swap}, \code{sort}, etc.) or specific helper routines like the following to implement an atomic counter :150 151 \begin{cfacode}152 monitor counter_t { /*...see section $\ref{data}$...*/ };153 154 void ?{}(counter_t & nomutex this); //constructor155 size_t ++?(counter_t & mutex this); //increment156 157 //need for mutex is platform dependent here158 void ?{}(size_t * this, counter_t & mutex cnt); //conversion159 \end{cfacode}160 161 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 constructed 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} key word depending on whether or not reading an \code{size_t} is an atomic operation or not.162 163 Having both \code{mutex} and \code{nomutex} keywords could be argued to be redundant based on the meaning of a routine having neither of these keywords. For example, given a routine without quualifiers \code{void foo(counter_t & this)} then one could argue that it should default to the safest option \code{mutex}. On the other hand, the option of having routine \code{void foo(counter_t & this)} mean \code{nomutex} is unsafe by default and may easily cause subtle errors. It can be argued that \code{nomutex} is the more "normal" behaviour, the \code{nomutex} keyword effectively stating explicitly that "this routine has nothing special". Another alternative is to make having exactly one of these keywords mandatory, which would provide the same semantics but without the ambiguity of supporting routine \code{void foo(counter_t & this)}. Mandatory keywords would also have the added benefice of being self-documented but at the cost of extra typing. However, 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.164 165 166 The next semantic decision is to establish when \code{mutex} may be used as a type qualifier. Consider the following declarations:167 \begin{cfacode}168 int f1(monitor & mutex m);169 int f2(const monitor & mutex m);170 int f3(monitor ** mutex m);171 int f4(monitor *[] mutex m);172 int f5(graph(monitor*) & mutex m);173 \end{cfacode}174 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 we only acquire objects once becomes also none trivial. This can be extended to absurd limits like \code{f5}, which uses a graph of monitors. To keep everyone as sane as possible~\cite{Chicken}, this projects imposes the requirement that a routine may only acquire one monitor per parameter and it must be the type of the parameter with 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.175 176 Finally, for convenience, monitors support multiple acquireing, that is acquireing a monitor while already holding it does not cause a deadlock. It simply increments an internal counter which is then used to release the monitor after the number of acquires and releases match up.177 178 % ###### # ####### #179 % # # # # # # #180 % # # # # # # #181 % # # # # # # #182 % # # ####### # #######183 % # # # # # # #184 % ###### # # # # #185 186 \subsection{Data semantics} \label{data}187 Once the call semantics are established, the next step is to establish data semantics. Indeed, until now a monitor is used simply as a generic handle but in most cases monitors contian shared data. This data should be intrinsic to the monitor declaration to prevent any accidental use of data without its appropriate protection. For example, here is a complete version of the counter showed in section \ref{call}:188 \begin{cfacode}189 monitor counter_t {190 int value;191 };192 193 void ?{}(counter_t & this) {194 this.cnt = 0;195 }196 197 int ++?(counter_t & mutex this) {198 return ++this.value;199 }200 201 //need for mutex is platform dependent here202 void ?{}(int * this, counter_t & mutex cnt) {203 *this = (int)cnt;204 }205 \end{cfacode}206 207 This simple counter is used as follows:208 \begin{center}209 \begin{tabular}{c @{\hskip 0.35in} c @{\hskip 0.35in} c}210 \begin{cfacode}211 //shared counter212 counter_t cnt;213 214 //multiple threads access counter215 thread 1 : cnt++;216 thread 2 : cnt++;217 thread 3 : cnt++;218 ...219 thread N : cnt++;220 \end{cfacode}221 \end{tabular}222 \end{center}223 224 Notice how the counter is used without any explicit synchronisation and yet supports thread-safe semantics for both reading and writting. Unlike object-oriented monitors, where calling a mutex member \emph{implicitly} acquires mutual-exclusion, \CFA uses an explicit mechanism to acquire mutual-exclusion. A consequence of this approach is that it extends to multi-monitor calls.225 \begin{cfacode}226 int f(MonitorA & mutex a, MonitorB & mutex b);227 228 MonitorA a;229 MonitorB b;230 f(a,b);231 \end{cfacode}232 This code acquires both locks before entering the critical section, called \emph{\gls{group-acquire}}. 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 routines using the same monitors as arguments. However, since \CFA monitors use multi-acquisition locks, users can effectively force the acquiring order. For example, notice which routines use \code{mutex}/\code{nomutex} and how this affects aquiring order :233 \begin{cfacode}234 void foo(A & mutex a, B & mutex b) { //acquire a & b235 //...236 }237 238 void bar(A & mutex a, B & /*nomutex*/ b) { //acquire a239 //...240 foo(a, b); //acquire b241 //...242 }243 244 void baz(A & /*nomutex*/ a, B & mutex b) { //acquire b245 //...246 foo(a, b); //acquire a247 //...248 }249 \end{cfacode}250 251 The multi-acquisition 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. such use leads to nested monitor call problems~\cite{Lister77}, which is a more specific variation of 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 on several occasion\cit, solving this problem requires :252 \begin{enumerate}253 \item Dynamically tracking of the monitor-call order.254 \item Implement rollback semantics.255 \end{enumerate}256 257 While the first requirement is already a significant constraint on the system, implementing a general rollback semantics in a C-like language is prohibitively complex \cit. In \CFA, users simply need to be carefull when acquiring multiple monitors at the same time.258 259 % ###### ####### ####### # ### # #####260 % # # # # # # # # # #261 % # # # # # # # # #262 % # # ##### # # # # # #####263 % # # # # ####### # # #264 % # # # # # # # # # #265 % ###### ####### # # # ### ####### #####266 %267 % ###### ####### # # # # # ####### ###### # #268 % # # # # # # # ## ## # # # # # #269 % # # # # # # # # # # # # # # # # #270 % ##### ###### # # # # # # # # # ###### #######271 % # # # # # # # # # # # # #272 % # # # # # # # # # # # # #273 % # ####### ####### # # # ####### # # # #274 275 \subsection{Implementation Details: Interaction with polymorphism}276 At first glance, interaction between monitors and \CFA's concept of polymorphism seems complex to support. However, it is shown that entry-point locking can solve most of the issues.277 278 Before looking into complex control flow, it is important to present the difference between the two acquiring options : \gls{callsite-locking} and \gls{entry-point-locking}, i.e. acquiring the monitors before making a mutex call or as the first instruction of the mutex call. For example:279 280 \begin{center}281 \begin{tabular}{|c|c|c|}282 Code & \gls{callsite-locking} & \gls{entry-point-locking} \\283 \CFA & pseudo-code & pseudo-code \\284 \hline285 \begin{cfacode}[tabsize=3]286 void foo(monitor& mutex a){287 288 289 290 //Do Work291 //...292 293 }294 295 void main() {296 monitor a;297 298 299 300 foo(a);301 302 }303 \end{cfacode} & \begin{pseudo}[tabsize=3]304 foo(& a) {305 306 307 308 //Do Work309 //...310 311 }312 313 main() {314 monitor a;315 //calling routine316 //handles concurrency317 acquire(a);318 foo(a);319 release(a);320 }321 \end{pseudo} & \begin{pseudo}[tabsize=3]322 foo(& a) {323 //called routine324 //handles concurrency325 acquire(a);326 //Do Work327 //...328 release(a);329 }330 331 main() {332 monitor a;333 334 335 336 foo(a);337 338 }339 \end{pseudo}340 \end{tabular}341 \end{center}342 343 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. Since a monitor's main purpose is to ensure mutual exclusion when accessing shared data, this implies that mutual exclusion is only required for routines that do in fact access shared data. However, since \code{dtype} polymorphism always handles incomplete types (by definition), no \code{dtype} polymorphic routine can access shared data since the data requires knowledge about the type. Therefore, the only concern when combining \code{dtype} polymorphism and monitors is to protect access to routines. \Gls{callsite-locking} would require a significant amount of work, since any \code{dtype} routine may have to obtain some lock before calling a routine, depending on whether or not the type passed is a monitor. However, with \gls{entry-point-locking} calling a monitor routine becomes exactly the same as calling it from anywhere else. Note that the \code{mutex} keyword relies on the resolver, which mean that in cases where generic monitor routines is actually desired, writing mutex routine is possible with the proper trait.344 345 346 % ### # # ####### ##### ##### # # ####### ######347 % # ## # # # # # # # # # # #348 % # # # # # # # # # # # #349 % # # # # # ##### # ####### ##### # #350 % # # # # # ### # # # # # # #351 % # # ## # ### # # # # # # # # #352 % ### # # # ### ##### ##### # # ####### ######353 354 \section{Internal scheduling} \label{insched}355 In addition to mutual exclusion, the monitors at the core of \CFA's concurrency can also be used to achieve synchronisation. With monitors, this is generally achieved with internal or external scheduling as in\cit. Since internal scheduling of single monitors is mostly a solved problem, this proposal concentraits on extending internal scheduling to multiple monitors at once. Indeed, like the \gls{group-acquire} semantics, internal scheduling extends to multiple monitors at once in a way that is natural to the user but requires additional complexity on the implementation side.356 357 First, Here is a simple example of such a technique :358 359 \begin{cfacode}360 monitor A {361 condition e;362 }363 364 void foo(A & mutex a) {365 // ...366 // We need someone else to do something now367 wait(a.e);368 // ...369 }370 371 void bar(A & mutex a) {372 // Do the thing foo is waiting on373 // ...374 // Signal foo it's done375 signal(a.e);376 }377 \end{cfacode}378 379 Note that in \CFA, \code{condition} have no particular need to be stored inside a monitor, beyond any software engineering reasons. Here routine \code{foo} waits for the \code{signal} from \code{bar} before making further progress, effectively ensuring a basic ordering. An important aspect to take into account here is that \CFA does not allow barging, which means that once function \code{bar} releases the monitor, foo is guaranteed to resume immediately after (unless some other function 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 a barging prevention or barging avoidance is more involved without language support.380 381 Supporting barging prevention as well as extending internal scheduling to multiple monitors is the main source of complexity in the design of \CFA concurrency.382 383 \subsection{Internal Scheduling - multi monitor}384 It easier to understand the problem of multi monitor scheduling using a series of pseudo code though experiment. Note that in the following snippets of pseudo-code waiting and signalling is done without the use of a condition variable. While \CFA requires condition variables to use signalling, the variable itself only really holds the data needed for the implementation of internal schedulling. Some languages like JAVA\cit simply define an implicit condition variable for every monitor while other languages like \uC use explicit condition variables. Since the following pseudo-codes are simple and focused experiments, all condition variables are implicit.385 386 \begin{multicols}{2}387 \begin{pseudo}388 acquire A389 wait A390 release A391 \end{pseudo}392 393 \columnbreak394 395 \begin{pseudo}396 acquire A397 signal A398 release A399 \end{pseudo}400 \end{multicols}401 402 The previous example shows the simple case of having two threads (one for each column) and a single monitor A. One thread acquires before waiting and the other acquires before signalling. There are a few important things to note here. First, both \code{wait} and \code{signal} must be called with the proper monitor(s) already acquired. This can be hidden on the user side but is a logical requirement for barging prevention. Secondly, as stated above, while it is argued that not all problems regarding single monitors are solved, this paper only regards challenges of \gls{group-acquire} and considers other problems related to monitors as solved.403 404 An important note about this example is that signalling a monitor is 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.405 406 A direct extension of the previous example is the \gls{group-acquire} version :407 408 \begin{multicols}{2}409 \begin{pseudo}410 acquire A & B411 wait A & B412 release A & B413 \end{pseudo}414 415 \columnbreak416 417 \begin{pseudo}418 acquire A & B419 signal A & B420 release A & B421 \end{pseudo}422 \end{multicols}423 424 This version uses \gls{group-acquire} (denoted using the \& symbol), but the presence of multiple monitors does not add a particularly new meaning. Synchronization will happen between the two threads in exactly the same way and order. The only difference is that mutual exclusion will cover more monitors. On the implementation side, handling multiple monitors at once does add a degree of complexity but it is not significant compared to the next few examples.425 426 For the sake of completeness, here is another example of the single-monitor case, this time with nesting.427 428 \begin{multicols}{2}429 \begin{pseudo}430 acquire A431 acquire B432 wait B433 release B434 release A435 \end{pseudo}436 437 \columnbreak438 439 \begin{pseudo}440 441 acquire B442 signal B443 release B444 445 \end{pseudo}446 \end{multicols}447 448 While these cases can cause some deadlock issues, we consider that these issues are only a symptom of the fact that locks, and by extension monitors, are not perfectly composable. However, for monitors as for locks, it is possible to write program that using nesting without encountering any problems if they are nested carefully.449 450 The next example is where \gls{group-acquire} adds a significant layer of complexity to the internal signalling semantics.451 452 \begin{multicols}{2}453 \begin{pseudo}454 acquire A455 // Code Section 1456 acquire A & B457 // Code Section 2458 wait A & B459 // Code Section 3460 release A & B461 // Code Section 4462 release A463 \end{pseudo}464 465 \columnbreak466 467 \begin{pseudo}468 acquire A469 // Code Section 5470 acquire A & B471 // Code Section 6472 signal A & B473 // Code Section 7474 release A & B475 // Code Section 8476 release A477 \end{pseudo}478 \end{multicols}479 480 It is particularly important to pay attention to code sections 8 and 3 which are where the existing semantics of internal scheduling are undefined. The root of the problem is that \gls{group-acquire} is used in a context where one of the monitors is already acquired. As mentionned in previous sections, monitors support multiple acquiring which means the that nesting \gls{group-acquire} can be done safely. However, in the context of internal scheduling it is important to define the behaviour of the previous pseudo-code. When the signaller thread reaches the location where it should "release A \& B", it actually only needs to release the monitor B. Since the other thread is waiting on monitor B, the signaller thread cannot simply release the monitor into the wild. This would mean that the waiting thread would have to reacquire the monitor and would therefore open the door to barging threads. Since the signalling thread still needs the monitor A, simply transferring ownership to the waiting thread is not an option because it would pottentially violate mutual exclusion. We are therefore left with three options :481 482 \subsubsection{Delaying signals}483 The first more 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 the correct time to transfer ownership when the last lock is no longer needed is what fits most closely to the behaviour of single monitor scheduling. However, this solution can become much more complicated depending on the content of the code section 8. Indeed, nothing prevents a user from signalling monitor A on a different condition variable. In that case, if monitor B is transferred with monitor A, then it means the system needs to handle threads having ownership on more monitors than expected and how to tie monitors together. On the other hand if the signalling thread only transfers monitor A then somehow both monitors A and B have to be transferred to the waiting thread from two different threads. While this solution may work, it was not fully explored because there is no apparent upper bound on the complexity of ownership transfer.484 485 \subsubsection{Dependency graphs}486 In the previous pseudo-code, there is a solution which would statisfy both barging prevention and mutual exclusion. If ownership of both monitors is transferred to the waiter when the signaller releases A and then the waiter transfers back ownership of A when it releases it then the problem is solved. This is the second 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.487 488 \begin{multicols}{2}489 \begin{pseudo}490 acquire A491 acquire B492 acquire C493 wait A & B & C494 release C495 release B496 release A497 \end{pseudo}498 499 \columnbreak500 501 \begin{pseudo}502 acquire A503 acquire B504 acquire C505 signal A & B & C506 release C507 release B508 release A509 \end{pseudo}510 \end{multicols}511 512 \subsubsection{Partial signalling}513 Finally, the solution that was chosen for \CFA is to use partial signalling. Consider the following case :514 515 \begin{multicols}{2}516 \begin{pseudo}[numbers=left]517 acquire A518 acquire A & B519 wait A & B520 release A & B521 release A522 \end{pseudo}523 524 \columnbreak525 526 \begin{pseudo}[numbers=left, firstnumber=6]527 acquire A528 acquire A & B529 signal A & B530 release A & B531 // ... More code532 release A533 \end{pseudo}534 \end{multicols}535 536 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 in to only two actions, passing monitors to the next owner when they should be release and conditionnaly waking threads if all conditions are met. Contrary to the other solutions, this solution quickly hits an upper bound on complexity of implementation.537 538 % Hard extension :539 540 % Incorrect options for the signal :541 542 % \begin{description}543 % \item[-] Release B and baton pass after Code Section 8 : Passing b without having it544 % \item[-] Keep B during Code Section 8 : Can lead to deadlocks since we secretly keep a lock longer than specified by the user545 % \item[-] Instead of release B transfer A and B to waiter then try to reacquire A before running Code Section 8 : This allows barging546 % \end{description}547 548 % Since we don't want barging we need to pass A \& B and somehow block and get A back.549 550 % \begin{center}551 % \begin{tabular}{ c @{\hskip 0.65in} c }552 % \begin{lstlisting}[language=Pseudo]553 % acquire A554 % acquire B555 % acquire C556 % wait A & B & C557 % 1: release C558 % 2: release B559 % 3: release A560 % \end{lstlisting}&\begin{lstlisting}[language=Pseudo]561 % acquire A562 % acquire B563 % acquire C564 % signal A & B & C565 % 4: release C566 % 5: release B567 % 6: release A568 % \end{lstlisting}569 % \end{tabular}570 % \end{center}571 572 % To prevent barging :573 574 % \begin{description}575 % \item[-] When the signaller hits 4 : pass A, B, C to waiter576 % \item[-] When the waiter hits 2 : pass A, B to signaller577 % \item[-] When the signaller hits 5 : pass A to waiter578 % \end{description}579 580 581 % \begin{center}582 % \begin{tabular}{ c @{\hskip 0.65in} c }583 % \begin{lstlisting}[language=Pseudo]584 % acquire A585 % acquire C586 % acquire B587 % wait A & B & C588 % 1: release B589 % 2: release C590 % 3: release A591 % \end{lstlisting}&\begin{lstlisting}[language=Pseudo]592 % acquire B593 % acquire A594 % acquire C595 % signal A & B & C596 % 4: release C597 % 5: release A598 % 6: release B599 % \end{lstlisting}600 % \end{tabular}601 % \end{center}602 603 % To prevent barging : When the signaller hits 4 : pass A, B, C to waiter. When the waiter hits 1 it must release B,604 605 % \begin{description}606 % \item[-]607 % \item[-] When the waiter hits 1 : pass A, B to signaller608 % \item[-] When the signaller hits 5 : pass A, B to waiter609 % \item[-] When the waiter hits 2 : pass A to signaller610 % \end{description}611 612 % Monitors also need to schedule waiting threads internally as a mean of synchronization. Internal scheduling is one of the simple examples of such a feature. It allows users to declare condition variables and have threads wait and signaled from them. Here is a simple example of such a technique :613 614 % \begin{lstlisting}615 % mutex struct A {616 % condition e;617 % }618 619 % void foo(A & mutex a) {620 % //...621 % wait(a.e);622 % //...623 % }624 625 % void bar(A & mutex a) {626 % signal(a.e);627 % }628 % \end{lstlisting}629 630 % Note that in \CFA, \code{condition} have no particular need to be stored inside a monitor, beyond any software engineering reasons. Here routine \code{foo} waits for the \code{signal} from \code{bar} before making further progress, effectively ensuring a basic ordering.631 632 % As for simple mutual exclusion, these semantics must also be extended to include \gls{group-acquire} :633 % \begin{center}634 % \begin{tabular}{ c @{\hskip 0.65in} c }635 % Thread 1 & Thread 2 \\636 % \begin{lstlisting}637 % void foo(A & mutex a,638 % A & mutex b) {639 % //...640 % wait(a.e);641 % //...642 % }643 644 % foo(a, b);645 % \end{lstlisting} &\begin{lstlisting}646 % void bar(A & mutex a,647 % A & mutex b) {648 % signal(a.e);649 % }650 651 652 653 % bar(a, b);654 % \end{lstlisting}655 % \end{tabular}656 % \end{center}657 658 % To define the semantics of internal scheduling, it is important to look at nesting and \gls{group-acquire}. Indeed, beyond concerns about lock ordering, without scheduling the two following pseudo codes are mostly equivalent. In fact, if we assume monitors are ordered alphabetically, these two pseudo codes would probably lead to exactly the same implementation :659 660 % \begin{table}[h!]661 % \centering662 % \begin{tabular}{c c}663 % \begin{lstlisting}[language=pseudo]664 % monitor A, B, C665 666 % acquire A667 % acquire B & C668 669 % //Do stuff670 671 % release B & C672 % release A673 % \end{lstlisting} &\begin{lstlisting}[language=pseudo]674 % monitor A, B, C675 676 % acquire A677 % acquire B678 % acquire C679 % //Do stuff680 % release C681 % release B682 % release A683 % \end{lstlisting}684 % \end{tabular}685 % \end{table}686 687 % Once internal scheduling is introduce however, semantics of \gls{group-acquire} become relevant. For example, let us look into the semantics of the following pseudo-code :688 689 % \begin{lstlisting}[language=Pseudo]690 % 1: monitor A, B, C691 % 2: condition c1692 % 3:693 % 4: acquire A694 % 5: acquire A & B & C695 % 6: signal c1696 % 7: release A & B & C697 % 8: release A698 % \end{lstlisting}699 700 % Without \gls{group-acquire} signal simply baton passes the monitor lock on the next release. In the case above, we therefore need to indentify the next release. If line 8 is picked at the release point, then the signal will attempt to pass A \& B \& C, without having ownership of B \& C. Since this violates mutual exclusion, we conclude that line 7 is the only valid location where signalling can occur. The traditionnal meaning of signalling is to transfer ownership of the monitor(s) and immediately schedule the longest waiting task. However, in the discussed case, the signalling thread expects to maintain ownership of monitor A. This can be expressed in two differents ways : 1) the thread transfers ownership of all locks and reacquires A when it gets schedulled again or 2) it transfers ownership of all three monitors and then expects the ownership of A to be transferred back.701 702 % However, the question is does these behavior motivate supporting acquireing non-disjoint set of monitors. Indeed, if the previous example was modified to only acquire B \& C at line 5 (an release the accordingly) then in respects to scheduling, we could add the simplifying constraint that all monitors in a bulk will behave the same way, simplifying the problem back to a single monitor problem which has already been solved. For this constraint to be acceptble however, we need to demonstrate that in does not prevent any meaningful possibilities. And, indeed, we can look at the two previous interpretation of the above pseudo-code and conclude that supporting the acquiring of non-disjoint set of monitors does not add any expressiveness to the language.703 704 % Option 1 reacquires the lock after the signal statement, this can be rewritten as follows without the need for non-disjoint sets :705 % \begin{lstlisting}[language=Pseudo]706 % monitor A, B, C707 % condition c1708 709 % acquire A & B & C710 % signal c1711 % release A & B & C712 % acquire A713 714 % release A715 % \end{lstlisting}716 717 % This pseudo code has almost exaclty the same semantics as the code acquiring intersecting sets of monitors.718 719 % Option 2 uses two-way lock ownership transferring instead of reacquiring monitor A. Two-way monitor ownership transfer is normally done using signalBlock semantics, which immedietely transfers ownership of a monitor before getting the ownership back when the other thread no longer needs the monitor. While the example pseudo-code for Option 2 seems toe transfer ownership of A, B and C and only getting A back, this is not a requirement. Getting back all 3 monitors and releasing B and C differs only in performance. For this reason, the second option could arguably be rewritten as :720 721 % \begin{lstlisting}[language=Pseudo]722 % monitor A, B, C723 % condition c1724 725 % acquire A726 % acquire B & C727 % signalBlock c1728 % release B & C729 % release A730 % \end{lstlisting}731 732 % Obviously, the difference between these two snippets of pseudo code is that the first one transfers ownership of A, B and C while the second one only transfers ownership of B and C. However, this limitation can be removed by allowing user to release extra monitors when using internal scheduling, referred to as extended internal scheduling (pattent pending) from this point on. Extended internal scheduling means the two following pseudo-codes are functionnaly equivalent :733 % \begin{table}[h!]734 % \centering735 % \begin{tabular}{c @{\hskip 0.65in} c}736 % \begin{lstlisting}[language=pseudo]737 % monitor A, B, C738 % condition c1739 740 % acquire A741 % acquire B & C742 % signalBlock c1 with A743 % release B & C744 % release A745 % \end{lstlisting} &\begin{lstlisting}[language=pseudo]746 % monitor A, B, C747 % condition c1748 749 % acquire A750 % acquire A & B & C751 % signal c1752 % release A & B & C753 % release A754 % \end{lstlisting}755 % \end{tabular}756 % \end{table}757 758 % It must be stated that the extended internal scheduling only makes sense when using wait and signalBlock, since they need to prevent barging, which cannot be done in the context of signal since the ownership transfer is strictly one-directionnal.759 760 % One critic that could arise is that extended internal schedulling is not composable since signalBlock must be explicitly aware of which context it is in. However, this argument is not relevant since acquire A, B and C in a context where a subset of them is already acquired cannot be achieved without spurriously releasing some locks or having an oracle aware of all monitors. Therefore, composability of internal scheduling is no more an issue than composability of monitors in general.761 762 % The main benefit of using extended internal scheduling is that it offers the same expressiveness as intersecting monitor set acquiring but greatly simplifies the selection of a leader (or representative) for a group of monitor. Indeed, when using intersecting sets, it is not obvious which set intersects with other sets which means finding a leader representing only the smallest scope is a hard problem. Where as when using disjoint sets, any monitor that would be intersecting must be specified in the extended set, the leader can be chosen as any monitor in the primary set.763 764 % We need to make sure the semantics for internally scheduling N monitors are a natural extension of the single monitor semantics. For this reason, we introduce the concept of \gls{mon-ctx}. In terms of context internal scheduling means "releasing a \gls{mon-ctx} and waiting for an other thread to acquire the same \gls{mon-ctx} and baton-pass it back to the initial thread". This definitions requires looking into what a \gls{mon-ctx} is and what the semantics of waiting and baton-passing are.765 766 % \subsubsection{Internal scheduling: Context} \label{insched-context}767 % Monitor scheduling operations are defined in terms of the context they are in. In languages that only supports operations on a single monitor at once, the context is completly defined by which most recently acquired monitors. Indeed, acquiring several monitors will form a stack of monitors which will be released in FILO order. In \CFA, a \gls{mon-ctx} cannot be simply defined by the last monitor that was acquired since \gls{group-acquire} means multiple monitors can be "the last monitor acquired". The \gls{mon-ctx} is therefore defined as the last set of monitors to have been acquired. This means taht when any new monitor is acquired, the group it belongs to is the new \gls{mon-ctx}. Correspondingly, if any monitor is released, the \gls{mon-ctx} reverts back to the context that was used prior to the monitor being acquired. In the most common case, \gls{group-acquire} means every monitor of a group will be acquired in released at the same time. However, since every monitor has its own recursion level, \gls{group-acquire} does not prevent users from reacquiring certain monitors while acquireing new monitors in the same operation. For example :768 769 % \begin{lstlisting}770 % //Forward declarations771 % monitor a, b, c772 % void foo( monitor & mutex a,773 % monitor & mutex b);774 % void bar( monitor & mutex a,775 % monitor & mutex b);776 % void baz( monitor & mutex a,777 % monitor & mutex b,778 % monitor & mutex c);779 780 % //Routines defined inline to illustrate context changed compared to the stack781 782 % //main thread783 % foo(a, b) {784 % //thread calls foo785 % //acquiring context a & b786 787 % baz(a, b) {788 % //thread calls baz789 % //no context change790 791 % bar(a, b, c) {792 % //thread calls bar793 % //acquiring context a & b & c794 795 % //Do stuff796 797 % return;798 % //call to bar returns799 % }800 % //context back to a & b801 802 % return;803 % //call to baz returns804 % }805 % //no context change806 807 % return;808 % //call to foo returns809 % }810 % //context back to initial state811 812 % \end{lstlisting}813 814 % As illustrated by the previous example, context changes can be caused by only one of the monitors comming into context or going out of context.815 816 % \subsubsection{Internal scheduling: Waiting} \label{insched-wait}817 818 % \subsubsection{Internal scheduling: Baton Passing} \label{insched-signal}819 % Baton passing in internal scheduling is done in terms of \code{signal} and \code{signalBlock}\footnote{Arguably, \code{signal_now} is a more evocative name and \code{signal} could be changed appropriately. }. While \code{signalBlock} is the more straight forward way of baton passing, transferring ownership immediately, it must rely on \code{signal} which is why t is discussed first.820 % \code{signal} has for effect to transfer the current context to another thread when the context would otherwise be released. This means that instead of releasing the concerned monitors, the first thread on the condition ready-queue is scheduled to run. The monitors are not released and when the signalled thread runs, it assumes it regained ownership of all the monitors it had in its context.821 822 % \subsubsection{Internal scheduling: Implementation} \label{insched-impl}823 % Too implement internal scheduling, three things are need : a data structure for waiting tasks, a data structure for signalled task and a leaving procedure to run the signalled task. In the case of both data structures, it is desireable to have to use intrusive data structures in order to prevent the need for any dynamic allocation. However, in both cases being able to queue several items in the same position in a queue is non trivial, even more so in the presence of concurrency. However, within a given \gls{mon-ctx}, all monitors have exactly the same behavior in regards to scheduling. Therefore, the problem of queuing multiple monitors at once can be ignored by choosing one monitor to represent every monitor in a context. While this could prove difficult in other situations, \gls{group-acquire} requires that the monitors be sorted according to some stable predicate. Since monitors are sorted in all contexts, the representative can simply be the first in the list. Choosing a representative means a simple intrusive queue inside the condition is sufficient to implement the data structure for both waiting and signalled monitors.824 825 % Since \CFA monitors don't have a complete image of the \gls{mon-ctx}, choosing the representative and maintaning the current context information cannot easily be done by any single monitors. However, as discussed in section [Missing section here], monitor mutual exclusion is implemented using an raii object which is already in charge of sorting monitors. This object has a complete picture of the \gls{mon-ctx} which means it is well suited to choose the reprensentative and detect context changes.826 827 % \newpage828 % \begin{lstlisting}829 % void ctor( monitor ** _monitors, int _count ) {830 % bool ctx_changed = false;831 % for( mon in _monitors ) {832 % ctx_changed = acquire( mon ) || ctx_changed;833 % }834 835 % if( ctx_changed ) {836 % set_representative();837 % set_context();838 % }839 % }840 841 % void dtor( monitor ** _monitors, int _count ) {842 % if( context_will_exit( _monitors, count ) ) {843 % baton_pass();844 % return;845 % }846 847 % for( mon in _monitors ) {848 % release( mon );849 % }850 % }851 852 % \end{lstlisting}853 854 855 856 % A direct extension of the single monitor semantics is to release all locks when waiting and transferring ownership of all locks when signalling. However, for the purpose of synchronization it may be usefull to only release some of the locks but keep others. It is possible to support internal scheduling and \gls{group-acquire} without any extra syntax by relying on order of acquisition. Here is an example of the different contexts in which internal scheduling can be used. (Note that here the use of helper routines is irrelevant, only routines acquire mutual exclusion have an impact on internal scheduling):857 858 % \begin{table}[h!]859 % \centering860 % \begin{tabular}{|c|c|c|}861 % Context 1 & Context 2 & Context 3 \\862 % \hline863 % \begin{lstlisting}864 % condition e;865 866 % //acquire a & b867 % void foo(monitor & mutex a,868 % monitor & mutex b) {869 870 % wait(e); //release a & b871 % }872 873 874 875 876 877 878 % foo(a,b);879 % \end{lstlisting} &\begin{lstlisting}880 % condition e;881 882 % //acquire a883 % void bar(monitor & mutex a,884 % monitor & nomutex b) {885 % foo(a,b);886 % }887 888 % //acquire a & b889 % void foo(monitor & mutex a,890 % monitor & mutex b) {891 % wait(e); //release a & b892 % }893 894 % bar(a, b);895 % \end{lstlisting} &\begin{lstlisting}896 % condition e;897 898 % //acquire a899 % void bar(monitor & mutex a,900 % monitor & nomutex b) {901 % baz(a,b);902 % }903 904 % //acquire b905 % void baz(monitor & nomutex a,906 % monitor & mutex b) {907 % wait(e); //release b908 % }909 910 % bar(a, b);911 % \end{lstlisting}912 % \end{tabular}913 % \end{table}914 915 % Context 1 is the simplest way of acquiring more than one monitor (\gls{group-acquire}), using a routine with multiple parameters having the \code{mutex} keyword. Context 2 also uses \gls{group-acquire} as well in routine \code{foo}. However, the routine is called by routine \code{bar}, which only acquires monitor \code{a}. Since monitors can be acquired multiple times this does not cause a deadlock by itself but it does force the acquiring order to \code{a} then \code{b}. Context 3 also forces the acquiring order to be \code{a} then \code{b} but does not use \gls{group-acquire}. The previous example tries to illustrate the semantics that must be established to support releasing monitors in a \code{wait} statement. In all cases, the behavior of the wait statment is to release all the locks that were acquired my the inner-most monitor call. That is \code{a & b} in context 1 and 2 and \code{b} only in context 3. Here are a few other examples of this behavior.916 917 918 % \begin{center}919 % \begin{tabular}{|c|c|c|}920 % \begin{lstlisting}921 % condition e;922 923 % //acquire b924 % void foo(monitor & nomutex a,925 % monitor & mutex b) {926 % bar(a,b);927 % }928 929 % //acquire a930 % void bar(monitor & mutex a,931 % monitor & nomutex b) {932 933 % wait(e); //release a934 % //keep b935 % }936 937 % foo(a, b);938 % \end{lstlisting} &\begin{lstlisting}939 % condition e;940 941 % //acquire a & b942 % void foo(monitor & mutex a,943 % monitor & mutex b) {944 % bar(a,b);945 % }946 947 % //acquire b948 % void bar(monitor & mutex a,949 % monitor & nomutex b) {950 951 % wait(e); //release b952 % //keep a953 % }954 955 % foo(a, b);956 % \end{lstlisting} &\begin{lstlisting}957 % condition e;958 959 % //acquire a & b960 % void foo(monitor & mutex a,961 % monitor & mutex b) {962 % bar(a,b);963 % }964 965 % //acquire none966 % void bar(monitor & nomutex a,967 % monitor & nomutex b) {968 969 % wait(e); //release a & b970 % //keep none971 % }972 973 % foo(a, b);974 % \end{lstlisting}975 % \end{tabular}976 % \end{center}977 % Note the right-most example is actually a trick pulled on the reader. Monitor state information is stored in thread local storage rather then in the routine context, which means that helper routines and other \code{nomutex} routines are invisible to the runtime system in regards to concurrency. This means that in the right-most example, the routine parameters are completly unnecessary. However, calling this routine from outside a valid monitor context is undefined.978 979 % These semantics imply that in order to release of subset of the monitors currently held, users must write (and name) a routine that only acquires the desired subset and simply calls wait. While users can use this method, \CFA offers the \code{wait_release}\footnote{Not sure if an overload of \code{wait} would work...} which will release only the specified monitors. In the center previous examples, the code in the center uses the \code{bar} routine to only release monitor \code{b}. Using the \code{wait_release} helper, this can be rewritten without having the name two routines :980 % \begin{center}981 % \begin{tabular}{ c c c }982 % \begin{lstlisting}983 % condition e;984 985 % //acquire a & b986 % void foo(monitor & mutex a,987 % monitor & mutex b) {988 % bar(a,b);989 % }990 991 % //acquire b992 % void bar(monitor & mutex a,993 % monitor & nomutex b) {994 995 % wait(e); //release b996 % //keep a997 % }998 999 % foo(a, b);1000 % \end{lstlisting} &\begin{lstlisting}1001 % =>1002 % \end{lstlisting} &\begin{lstlisting}1003 % condition e;1004 1005 % //acquire a & b1006 % void foo(monitor & mutex a,1007 % monitor & mutex b) {1008 % wait_release(e,b); //release b1009 % //keep a1010 % }1011 1012 % foo(a, b);1013 % \end{lstlisting}1014 % \end{tabular}1015 % \end{center}1016 1017 % Regardless of the context in which the \code{wait} statement is used, \code{signal} must be called holding the same set of monitors. In all cases, signal only needs a single parameter, the condition variable that needs to be signalled. But \code{signal} needs to be called from the same monitor(s) that call to \code{wait}. Otherwise, mutual exclusion cannot be properly transferred back to the waiting monitor.1018 1019 % Finally, an additional semantic which can be very usefull is the \code{signal_block} routine. This routine behaves like signal for all of the semantics discussed above, but with the subtelty that mutual exclusion is transferred to the waiting task immediately rather than wating for the end of the critical section.1020 % \\1021 1022 % ####### # # ####### ##### ##### # # ####### ######1023 % # # # # # # # # # # # # #1024 % # # # # # # # # # # #1025 % ##### # # ##### # ####### ##### # #1026 % # # # # ### # # # # # # #1027 % # # # # ### # # # # # # # # #1028 % ####### # # # ### ##### ##### # # ####### ######1029 \section{External scheduling} \label{extsched}1030 An alternative to internal scheduling is to use external scheduling instead. This method is more constrained and explicit which may help 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 (ex: \uC) or in terms of data (ex: Go). Of course, both of these paradigms have their own strenghts and weaknesses but for this project control flow semantics where 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 following example shows a simple use \code{accept} versus \code{wait}/\code{signal} and its advantages.1031 1032 \begin{center}1033 \begin{tabular}{|c|c|}1034 Internal Scheduling & External Scheduling \\1035 \hline1036 \begin{lstlisting}1037 _Monitor blarg {1038 condition c;1039 public:1040 void f() { signal(c)}1041 void g() { wait(c); }1042 private:1043 }1044 \end{lstlisting}&\begin{lstlisting}1045 _Monitor blarg {1046 1047 public:1048 void f() { /*...*/ }1049 void g() { _Accept(f); }1050 private:1051 }1052 \end{lstlisting}1053 \end{tabular}1054 \end{center}1055 1056 In the case of internal scheduling, the call to \code{wait} only guarantees that \code{g} is the last routine to access the monitor. This intails that the routine \code{f} may have acquired mutual exclusion several times while routine \code{h} was waiting. On the other hand, external scheduling guarantees that while routine \code{h} was waiting, no routine other than \code{g} could acquire the monitor.1057 \\1058 1059 % # ####### ####### ##### ####### ####### ###### # #####1060 % # # # # # # # # # # # # # # #1061 % # # # # # # # # # # # # #1062 % # # # # # ##### ##### # # ###### # #####1063 % # # # # # # # # # # # # # #1064 % # # # # # # # # # # # # # # # #1065 % ####### ####### ####### ##### ####### ####### ###### ##### #####1066 1067 \subsection{Loose object definitions}1068 In \uC, monitor declarations include an exhaustive list of monitor operations. Since \CFA is not object oriented it becomes both more difficult to implement but also less clear for the user :1069 1070 \begin{lstlisting}1071 mutex struct A {};1072 1073 void f(A & mutex a);1074 void g(A & mutex a) { accept(f); }1075 \end{lstlisting}1076 1077 However, external scheduling is an example where implementation constraints become visible from the interface. Indeed, ince 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 :1078 1079 \begin{center}1080 \begin{tabular}{l}1081 \begin{lstlisting}[language=Pseudo]1082 if monitor is free :1083 enter1084 elif monitor accepts me :1085 enter1086 else :1087 block1088 \end{lstlisting}1089 \end{tabular}1090 \end{center}1091 1092 For the \pscode{monitor is free} condition 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 :1093 1094 \begin{center}1095 {\resizebox{0.4\textwidth}{!}{\input{monitor}}}1096 \end{center}1097 1098 There are other alternatives to these pictures but in the case of this picture implementing a fast accept check is relatively easy. Indeed simply updating a bitmask when the acceptor queue changes is enough to have a check that executes in a single instruction, even with a fairly large number of acceptor. However, this relies on the fact that all the acceptable routines are declared with the monitor type. For OO languages this doesn't compromise much since monitors already have an exhaustive list of member routines. However, for \CFA this isn't the case, routines can be added to a type anywhere after its declaration. Its 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.1099 The alternative would be to have a picture more like this one:1100 1101 \begin{center}1102 {\resizebox{0.4\textwidth}{!}{\input{ext_monitor}}}1103 \end{center}1104 1105 Not storing the queues inside the monitor means that the storage can vary between routines, allowing for more flexibility and extensions. Storing an array of function-pointers would solve the issue of uniquely identifying acceptable routines. However, the single instruction bitmask compare has been replaced by dereferencing a pointer followed by a linear search. Furthermore, supporting nested external scheduling may now require additionnal searches on calls to accept to check if a routine is already queued in.1106 1107 At this point we must make a decision 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.1108 1109 In either cases here are a few alternatives for the different syntaxes this syntax : \\1110 \begin{center}1111 {\renewcommand{\arraystretch}{1.5}1112 \begin{tabular}[t]{l @{\hskip 0.35in} l}1113 \hline1114 \multicolumn{2}{ c }{\code{accept} on type}\\1115 \hline1116 Alternative 1 & Alternative 2 \\1117 \begin{lstlisting}1118 mutex struct A1119 accept( void f(A & mutex a) )1120 {};1121 \end{lstlisting} &\begin{lstlisting}1122 mutex struct A {}1123 accept( void f(A & mutex a) );1124 1125 \end{lstlisting} \\1126 Alternative 3 & Alternative 4 \\1127 \begin{lstlisting}1128 mutex struct A {1129 accept( void f(A & mutex a) )1130 };1131 1132 \end{lstlisting} &\begin{lstlisting}1133 mutex struct A {1134 accept :1135 void f(A & mutex a) );1136 };1137 \end{lstlisting}\\1138 \hline1139 \multicolumn{2}{ c }{\code{accept} on routine}\\1140 \hline1141 \begin{lstlisting}1142 mutex struct A {};1143 1144 void f(A & mutex a)1145 1146 accept( void f(A & mutex a) )1147 void g(A & mutex a) {1148 /*...*/1149 }1150 \end{lstlisting}&\\1151 \end{tabular}1152 }1153 \end{center}1154 1155 An other aspect to consider is what happens if multiple overloads of the same routine are used. For the time being it is assumed that multiple overloads of the same routine should be scheduled regardless of the overload used. However, this could easily be extended in the future.1156 1157 % # # # # # ####### ### # # ####### # #1158 % ## ## # # # # # ## ## # # ## #1159 % # # # # # # # # # # # # # # # # # #1160 % # # # # # # # # # # # # # # # #1161 % # # # # # # # # # # # # # #1162 % # # # # # # # # # # # # ##1163 % # # ##### ####### # ### # # ####### # #1164 1165 \subsection{Multi-monitor scheduling}1166 1167 External scheduling, like internal scheduling, becomes orders of magnitude more complex when we start introducing multi-monitor syntax. Even in the simplest possible case some new semantics need to be established :1168 \begin{lstlisting}1169 accept( void f(mutex struct A & mutex this))1170 mutex struct A {};1171 1172 mutex struct B {};1173 1174 void g(A & mutex a, B & mutex b) {1175 accept(f); //ambiguous, which monitor1176 }1177 \end{lstlisting}1178 1179 The obvious solution is to specify the correct monitor as follows :1180 1181 \begin{lstlisting}1182 accept( void f(mutex struct A & mutex this))1183 mutex struct A {};1184 1185 mutex struct B {};1186 1187 void g(A & mutex a, B & mutex b) {1188 accept( f, b );1189 }1190 \end{lstlisting}1191 1192 This is unambiguous. Both locks will be acquired and kept, when routine \code{f} is called the lock for monitor \code{a} will be temporarily transferred from \code{g} to \code{f} (while \code{g} still holds lock \code{b}). This behavior can be extended to multi-monitor accept statment as follows.1193 1194 \begin{lstlisting}1195 accept( void f(mutex struct A & mutex, mutex struct A & mutex))1196 mutex struct A {};1197 1198 mutex struct B {};1199 1200 void g(A & mutex a, B & mutex b) {1201 accept( f, b, a );1202 }1203 \end{lstlisting}1204 1205 Note that the set of monitors passed to the \code{accept} statement must be entirely contained in the set of monitor already acquired in the routine. \code{accept} used in any other context is Undefined Behaviour.1206 1207 % ###### ####### ####### # ### # #####1208 % # # # # # # # # # #1209 % # # # # # # # # #1210 % # # ##### # # # # # #####1211 % # # # # ####### # # #1212 % # # # # # # # # # #1213 % ###### ####### # # # ### ####### #####1214 %1215 % ##### # # ####### # # ####### #####1216 % # # # # # # # # # #1217 % # # # # # # # # #1218 % ##### # # # # ##### # # ##### #####1219 % # # # # # # # # # #1220 % # # # # # # # # # #1221 % #### # ##### ####### ##### ####### #####1222 1223 1224 \subsection{Implementation Details: External scheduling queues}1225 To support multi-monitor external scheduling means that some kind of entry-queues must be used that is aware of both monitors. However, acceptable routines must be aware of the entry queues which means they must be stored inside at least one of the monitors that will be acquired. This in turn adds the requirement a systematic algorithm of disambiguating which queue is relavant regardless of user ordering. The proposed algorithm is to fall back on monitors lock ordering and specify that the monitor that is acquired first is the lock with the relevant entry queue. This assumes that the lock acquiring order is static for the lifetime of all concerned objects but that is a reasonnable constraint. This algorithm choice has two consequences, the entry queue of the highest priority monitor is no longer a true FIFO queue and the queue of the lowest priority monitor is both required and probably unused. The queue can no longer be a FIFO queue because instead of simply containing the waiting threads in order arrival, they also contain the second mutex. Therefore, another thread with the same highest priority monitor but a different lowest priority monitor may arrive first but enter the critical section after a thread with the correct pairing. Secondly, since it may not be known at compile time which monitor will be the lowest priority monitor, every monitor needs to have the correct queues even though it is probable that half the multi-monitor queues will go unused for the entire duration of the program.1226 1227 \section{Other concurrency tools}1228 TO BE CONTINUED...1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 % ###### # ###### # # # ####### # ### ##### # #1240 % # # # # # # # # # # # # # # # ## ##1241 % # # # # # # # # # # # # # # # # # #1242 % ###### # # ###### # # # # ##### # # ##### # # #1243 % # ####### # # ####### # # # # # # # #1244 % # # # # # # # # # # # # # # # #1245 % # # # # # # # ####### ####### ####### ####### ### ##### # #1246 \chapter{Parallelism}1247 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.1248 1249 \section{Paradigm}1250 \subsection{User-level threads}1251 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 expensives costs of using 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.1252 1253 Examples of languages that support \glspl{uthread} are Erlang~\cite{Erlang} and \uC~\cite{uC++book}.1254 1255 \subsection{Fibers : user-level threads without preemption}1256 A popular varient of \glspl{uthread} is what is often reffered to as \glspl{fiber}. However, \glspl{fiber} do not present meaningful semantical differences with \glspl{uthread}. 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 ignore fibers.1257 1258 An example of a language that uses fibers is Go~\cite{Go}1259 1260 \subsection{Jobs and thread pools}1261 The approach on the opposite end of the spectrum is to base parallelism on \glspl{pool}. Indeed, \glspl{pool} offer limited flexibility but at the benefit of a simpler user interface. In \gls{pool} based systems, users express parallelism as units of work and a dependency graph (either explicit or implicit) that tie them together. This approach means users need not worry about concurrency but significantly limits the interaction that can occur among jobs. Indeed, any \gls{job} that blocks also blocks the underlying worker, which effectively means the CPU utilization, and therefore throughput, suffers noticeably. It can be argued that a solution to this problem is to use more workers than available cores. However, unless the number of jobs and the number of workers are comparable, having a significant amount of blocked jobs always results in idles cores.1262 1263 The gold standard of this implementation is Intel's TBB library~\cite{TBB}.1264 1265 \subsection{Paradigm performance}1266 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. However, interactions between jobs can easily exacerbate contention. User-level threads allow fine-grain context switching, which results in better resource utilisation, but context switches will be more expansive and the extra control means users need to tweak more variables to get the desired performance. Furthermore, if the units of uninterrupted work are large enough the paradigm choice is largely amorticised by the actual work done.1267 1268 % ##### ####### # ####### ###### ######1269 % # # # # # # # # # #1270 % # # # # # # # # #1271 % # ##### # # ##### # ###### ######1272 % # # ####### # # # # #1273 % # # # # # # # # # #1274 % ##### # # # # ###### ######1275 1276 \section{\CFA 's Thread Building Blocks}1277 As a system-level language, \CFA should offer both performance and flexibilty as its primary goals, simplicity and user-friendliness being a secondary concern. Therefore, the core of parallelism in \CFA should prioritize power and efficiency. With this said, deconstructing popular paradigms in order to get simple building blocks yields \glspl{uthread} as the core parallelism block. \Glspl{pool} and other parallelism paradigms can then be built on top of the underlying threading model.1278 1279 \subsection{Coroutines : A stepping stone}\label{coroutine}1280 While the main focus of this proposal is concurrency and paralellism, it is important to adress coroutines which are actually a significant underlying aspect of the concurrency system. Indeed, while having nothing todo with parallelism and arguably very little to do with concurrency, coroutines need to deal with context-switchs and 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.1281 1282 The core API of coroutines revolve around two features : independent stacks and \code{suspend}/\code{resume}.1283 Here is an example of a solution to the fibonnaci problem using \CFA coroutines :1284 \begin{lstlisting}1285 struct Fibonacci {1286 int fn; // used for communication1287 coroutine_descriptor c;1288 };1289 1290 void ?{}(Fibonacci* this) {1291 this->fn = 0;1292 }1293 1294 coroutine_descriptor* get_¶coroutine¶(Fibonacci* this) {1295 return &this->c;1296 }1297 1298 void co_main(Fibonacci* this) {1299 int fn1, fn2; // retained between resumes1300 this->fn = 0;1301 fn1 = this->fn;1302 suspend(this); // return to last resume1303 1304 this->fn = 1;1305 fn2 = fn1;1306 fn1 = this->fn;1307 suspend(this); // return to last resume1308 1309 for ( ;; ) {1310 this->fn = fn1 + fn2;1311 fn2 = fn1;1312 fn1 = this->fn;1313 suspend(this); // return to last resume1314 }1315 }1316 1317 int next(Fibonacci* this) {1318 resume(this); // transfer to last suspend1319 return this.fn;1320 }1321 1322 void main() {1323 Fibonacci f1, f2;1324 for ( int i = 1; i <= 10; i += 1 ) {1325 sout | next(&f1) | '§\verb+ +§' | next(&f2) | endl;1326 }1327 }1328 \end{lstlisting}1329 1330 \subsubsection{Construction}1331 One important design challenge for coroutines and threads (shown in section \ref{threads}) is that the runtime system needs to run some code after the user-constructor runs. In the case of the coroutines this challenge is simpler since there is no loss of determinism brough by preemption or scheduling, however, the underlying challenge remains the same for coroutines and threads.1332 1333 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 the main is called and to be able to resume the coroutine from the main (Obviously we only solve cases where these two statements don't conflict). There are several solutions to this problem but the chosen options effectively forces the design of the coroutine.1334 1335 Furthermore, \CFA faces an extra challenge which is that polymorphique routines rely on invisible thunks when casted to non-polymorphic routines and these thunks have function scope, for example :1336 1337 TODO : Simple case where a thunk would be created.1338 1339 1340 1341 \subsubsection{Alternative: Inheritance}1342 One solution to this challenge would be to use inheritence,1343 1344 \begin{lstlisting}1345 struct Fibonacci {1346 int fn; // used for communication1347 coroutine c;1348 };1349 1350 void ?{}(Fibonacci* this) {1351 this->fn = 0;1352 (&this->c){};1353 }1354 \end{lstlisting}1355 1356 There are two downsides to the 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 we use a parameter or a virtual pointer, this means the coroutine data must be made larger to store a value that is actually a compile time constant (The address of the main routine). The second problem which is both subtle but significant, is that now can get the initialisation order of there coroutines wrong. Indeed, every field of a \CFA struct will be constructed but in the order of declaration, unless users explicitly write otherwise. This means that users who forget to initialize a the coroutine at the right time may resume the coroutine at with an uninitilized object. For coroutines, this is unlikely to be a problem, for threads however, this is a significant problem.1357 1358 \subsubsection{Alternative: Reserved keyword}1359 The next alternative is to use language support to annotate coroutines as follows :1360 1361 \begin{lstlisting}1362 coroutine struct Fibonacci {1363 int fn; // used for communication1364 };1365 \end{lstlisting}1366 1367 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 \CFA.1368 1369 \subsubsection{Alternative: Lamda Objects}1370 1371 Boost does not use objects...1372 TO BE CONTINUED...1373 1374 \subsubsection{Trait based coroutines}1375 1376 Finally the approach chosen, which is the one closest to \CFA idioms, is to use trait-based lazy coroutines, the approach shown in section \ref{coroutine}. This approach defines a coroutine as anything that satisfies the \code{is_coroutine} and is used as a coroutine is a coroutine. This entails the an object is not a coroutine until \code{resume} (and \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.1377 1378 % ####### # # ###### ####### # ###### #####1379 % # # # # # # # # # # # #1380 % # # # # # # # # # # #1381 % # ####### ###### ##### # # # # #####1382 % # # # # # # ####### # # #1383 % # # # # # # # # # # # #1384 % # # # # # ####### # # ###### #####1385 1386 \subsection{Thread Interface}\label{threads}1387 The basic building blocks of \CFA are \glspl{cfathread}. By default these are implemented as \glspl{uthread}, and as such, offer a flexible and lightweight threading interface (lightweight compared to \glspl{kthread}). A thread can be declared using a struct declaration with prefix \code{thread} as follows :1388 1389 \begin{lstlisting}1390 trait is_¶thread¶(dtype T) {1391 void co_main(T* this);1392 coroutine* get_coroutine(T* this);1393 };1394 1395 thread struct foo {};1396 \end{lstlisting}1397 1398 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), the existing syntax for declaring routines names with special semantics can be extended, i.e. operator overloading. As such the \code{main} routine of a thread can be defined as :1399 \begin{lstlisting}1400 thread struct foo {};1401 1402 void ?main(foo* this) {1403 sout | "Hello World!" | endl;1404 }1405 \end{lstlisting}1406 1407 In this example, threads of type \code{foo} will start there execution in the \code{void ?main(foo*)} routine which in this case prints \code{"Hello World!"}. While this proposoal encourages this approach which is enforces strongly type 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 :1408 \begin{lstlisting}1409 typedef void (*voidFunc)(void);1410 1411 thread struct FuncRunner {1412 voidFunc func;1413 };1414 1415 //ctor1416 void ?{}(FuncRunner* this, voidFunc inFunc) {1417 func = inFunc;1418 }1419 1420 //main1421 void t_main(FuncRunner* this) {1422 this->func();1423 }1424 \end{lstlisting}1425 1426 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} once the constructor has completed and \code{join} before the destructor runs.1427 \begin{lstlisting}1428 thread struct World; //FuncRunner declared above1429 1430 void ?main(thread World* this) {1431 sout | "World!" | endl;1432 }1433 1434 void main() {1435 World w;1436 //Thread run forks here1437 1438 //Print to "Hello " and "World!" will be run concurrently1439 sout | "Hello " | endl;1440 1441 //Implicit join at end of scope1442 }1443 \end{lstlisting}1444 This 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. However, 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. While this seems like a significant limitation, existing \CFA semantics can solve this problem. Indeed, by using dynamic allocation to create threads will naturally let threads outlive the scope in which the thread was created much like dynamically allocating memory will let objects outlive the scope in which thy were created :1445 1446 \begin{lstlisting}1447 thread struct MyThread {1448 //...1449 };1450 1451 //ctor1452 void ?{}(MyThread* this,1453 bool is_special = false) {1454 //...1455 }1456 1457 //main1458 void ?main(MyThread* this) {1459 //...1460 }1461 1462 void foo() {1463 MyThread* special_thread;1464 {1465 MyThread thrds = {false};1466 //Start a thread at the beginning of the scope1467 1468 DoStuff();1469 1470 //create a other thread that will outlive the thread in this scope1471 special_thread = new MyThread{true};1472 1473 //Wait for the thread to finish1474 }1475 DoMoreStuff();1476 1477 //Now wait for the special1478 }1479 \end{lstlisting}1480 1481 Another advantage of this semantic is that it naturally scale to multiple threads meaning basic synchronisation is very simple :1482 1483 \begin{lstlisting}1484 thread struct MyThread {1485 //...1486 };1487 1488 //ctor1489 void ?{}(MyThread* this) {}1490 1491 //main1492 void ?main(MyThread* this) {1493 //...1494 }1495 1496 void foo() {1497 MyThread thrds[10];1498 //Start 10 threads at the beginning of the scope1499 1500 DoStuff();1501 1502 //Wait for the 10 threads to finish1503 }1504 \end{lstlisting}1505 1506 \newpage1507 \bf{WORK IN PROGRESS}1508 \subsection{The \CFA Kernel : Processors, Clusters and Threads}\label{kernel}1509 1510 1511 \subsection{Paradigms}\label{cfaparadigms}1512 Given these building blocks we can then reproduce the all three of the popular paradigms. Indeed, we get \glspl{uthread} as the default paradigm in \CFA. However, disabling \glspl{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.1513 1514 % \subsection{High-level options}\label{tasks}1515 %1516 % \subsubsection{Thread interface}1517 % constructors destructors1518 % initializer lists1519 % monitors1520 %1521 % \subsubsection{Futures}1522 %1523 % \subsubsection{Implicit threading}1524 % Finally, 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 system level.1525 %1526 % \begin{center}1527 % \begin{tabular}[t]{|c|c|c|}1528 % Sequential & System Parallel & Language Parallel \\1529 % \begin{lstlisting}1530 % void big_sum(int* a, int* b,1531 % int* out,1532 % size_t length)1533 % {1534 % for(int i = 0; i < length; ++i ) {1535 % out[i] = a[i] + b[i];1536 % }1537 % }1538 %1539 %1540 %1541 %1542 %1543 % int* a[10000];1544 % int* b[10000];1545 % int* c[10000];1546 % //... fill in a and b ...1547 % big_sum(a, b, c, 10000);1548 % \end{lstlisting} &\begin{lstlisting}1549 % void big_sum(int* a, int* b,1550 % int* out,1551 % size_t length)1552 % {1553 % range ar(a, a + length);1554 % range br(b, b + length);1555 % range or(out, out + length);1556 % parfor( ai, bi, oi,1557 % [](int* ai, int* bi, int* oi) {1558 % oi = ai + bi;1559 % });1560 % }1561 %1562 % int* a[10000];1563 % int* b[10000];1564 % int* c[10000];1565 % //... fill in a and b ...1566 % big_sum(a, b, c, 10000);1567 % \end{lstlisting}&\begin{lstlisting}1568 % void big_sum(int* a, int* b,1569 % int* out,1570 % size_t length)1571 % {1572 % for (ai, bi, oi) in (a, b, out) {1573 % oi = ai + bi;1574 % }1575 % }1576 %1577 %1578 %1579 %1580 %1581 % int* a[10000];1582 % int* b[10000];1583 % int* c[10000];1584 % //... fill in a and b ...1585 % big_sum(a, b, c, 10000);1586 % \end{lstlisting}1587 % \end{tabular}1588 % \end{center}1589 %1590 % \subsection{Machine setup}\label{machine}1591 % Threads are all good and well but wee still some OS support to fully utilize available hardware.1592 %1593 % \textbf{\large{Work in progress...}} Do wee need something beyond specifying the number of kernel threads?1594 1595 % # # #1596 % # # # #1597 % # # # #1598 % # # # #1599 % ####### # #1600 % # # # #1601 % # # ####### #######1602 103 \chapter{Putting it all together} 1603 1604 1605 1606 1607 104 1608 105 \chapter{Conclusion} 1609 106 1610 1611 1612 1613 1614 1615 % ####### # # ####### # # ###### #######1616 % # # # # # # # # #1617 % # # # # # # # # #1618 % ##### # # # # # ###### #####1619 % # # # # # # # # #1620 % # # # # # # # # #1621 % # ##### # ##### # # ######1622 107 \chapter{Future work} 1623 108 Concurrency and parallelism is still a very active field that strongly benefits from hardware advances. As such certain features that aren't necessarily mature enough in their current state could become relevant in the lifetime of \CFA. 1624 109 \subsection{Transactions} 1625 110 1626 % ####### # # ######1627 % # ## # # #1628 % # # # # # #1629 % ##### # # # # #1630 % # # # # # #1631 % # # ## # #1632 % ####### # # ######1633 111 \section*{Acknowledgements} 1634 112
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