source: doc/proposals/concurrency/concurrency.tex @ efe4d73

aaron-thesisarm-ehcleanup-dtorsdeferred_resndemanglerjacob/cs343-translationjenkins-sandboxnew-astnew-ast-unique-exprnew-envno_listpersistent-indexerresolv-newwith_gc
Last change on this file since efe4d73 was efe4d73, checked in by Thierry Delisle <tdelisle@…>, 5 years ago

added all standard bib files (synched through rsync)

  • Property mode set to 100644
File size: 52.0 KB
Line 
1% requires tex packages: texlive-base texlive-latex-base tex-common texlive-humanities texlive-latex-extra texlive-fonts-recommended
2
3% inline code ©...© (copyright symbol) emacs: C-q M-)
4% red highlighting ®...® (registered trademark symbol) emacs: C-q M-.
5% blue highlighting ß...ß (sharp s symbol) emacs: C-q M-_
6% green highlighting ¢...¢ (cent symbol) emacs: C-q M-"
7% LaTex escape §...§ (section symbol) emacs: C-q M-'
8% keyword escape ¶...¶ (pilcrow symbol) emacs: C-q M-^
9% math escape $...$ (dollar symbol)
10
11\documentclass[twoside,11pt]{article}
12
13%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
14
15% Latex packages used in the document.
16\usepackage[T1]{fontenc}                                % allow Latin1 (extended ASCII) characters
17\usepackage{textcomp}
18\usepackage[latin1]{inputenc}
19\usepackage{fullpage,times,comment}
20\usepackage{epic,eepic}
21\usepackage{upquote}                                                                    % switch curled `'" to straight
22\usepackage{calc}
23\usepackage{xspace}
24\usepackage{graphicx}
25\usepackage{tabularx}
26\usepackage[acronym]{glossaries}
27\usepackage{varioref}                                                           % extended references
28\usepackage{inconsolata}
29\usepackage{listings}                                                                   % format program code
30\usepackage[flushmargin]{footmisc}                                              % support label/reference in footnote
31\usepackage{latexsym}                                   % \Box glyph
32\usepackage{mathptmx}                                   % better math font with "times"
33\usepackage[usenames]{color}
34\usepackage[pagewise]{lineno}
35\usepackage{fancyhdr}
36\renewcommand{\linenumberfont}{\scriptsize\sffamily}
37\input{common}                                          % bespoke macros used in the document
38\usepackage[dvips,plainpages=false,pdfpagelabels,pdfpagemode=UseNone,colorlinks=true,pagebackref=true,linkcolor=blue,citecolor=blue,urlcolor=blue,pagebackref=true,breaklinks=true]{hyperref}
39\usepackage{breakurl}
40
41\usepackage{tikz}
42\def\checkmark{\tikz\fill[scale=0.4](0,.35) -- (.25,0) -- (1,.7) -- (.25,.15) -- cycle;}
43
44\renewcommand{\UrlFont}{\small\sf}
45
46\setlength{\topmargin}{-0.45in}                                                 % move running title into header
47\setlength{\headsep}{0.25in}
48
49%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
50
51% Names used in the document.
52
53\newcommand{\Version}{1.0.0}
54\newcommand{\CS}{C\raisebox{-0.9ex}{\large$^\sharp$}\xspace}
55
56\newcommand{\Textbf}[2][red]{{\color{#1}{\textbf{#2}}}}
57\newcommand{\Emph}[2][red]{{\color{#1}\textbf{\emph{#2}}}}
58\newcommand{\R}[1]{\Textbf{#1}}
59\newcommand{\B}[1]{{\Textbf[blue]{#1}}}
60\newcommand{\G}[1]{{\Textbf[OliveGreen]{#1}}}
61\newcommand{\uC}{$\mu$\CC}
62\newcommand{\cit}{\textsuperscript{[Citation Needed]}\xspace}
63\newcommand{\code}[1]{\lstinline{#1}}
64\newcommand{\pseudo}[1]{\lstinline[language=Pseudo]{#1}}
65
66\input{glossary}
67
68\newsavebox{\LstBox}
69
70%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
71
72\setcounter{secnumdepth}{3}                             % number subsubsections
73\setcounter{tocdepth}{3}                                % subsubsections in table of contents
74% \linenumbers                                            % comment out to turn off line numbering
75\makeindex
76\pagestyle{fancy}
77\fancyhf{}
78\cfoot{\thepage}
79\rfoot{v\input{version}}
80
81%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
82
83\begin{document}
84% \linenumbers
85
86\title{Concurrency in \CFA}
87\author{Thierry Delisle \\
88Dept. of Computer Science, University of Waterloo, \\ Waterloo, Ontario, Canada
89}
90
91\maketitle
92
93% ### #     # ####### ######  #######
94%  #  ##    #    #    #     # #     #
95%  #  # #   #    #    #     # #     #
96%  #  #  #  #    #    ######  #     #
97%  #  #   # #    #    #   #   #     #
98%  #  #    ##    #    #    #  #     #
99% ### #     #    #    #     # #######
100
101\section{Introduction}
102This proposal provides a minimal core concurrency API that is both simple, efficient and can be reused to build higher-level features. The simplest possible 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 construct as the basis of the concurrency in \CFA.
103Indeed, for highly productive parallel programming high-level approaches are much more popular\cite{HPP:Study}. Examples are task based parallelism, message passing, implicit threading.
104
105There are actually two problems that need to be solved in the design of the concurrency for a 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.
106
107%  #####  ####### #     #  #####  #     # ######  ######  ####### #     #  #####  #     #
108% #     # #     # ##    # #     # #     # #     # #     # #       ##    # #     #  #   #
109% #       #     # # #   # #       #     # #     # #     # #       # #   # #         # #
110% #       #     # #  #  # #       #     # ######  ######  #####   #  #  # #          #
111% #       #     # #   # # #       #     # #   #   #   #   #       #   # # #          #
112% #     # #     # #    ## #     # #     # #    #  #    #  #       #    ## #     #    #
113%  #####  ####### #     #  #####   #####  #     # #     # ####### #     #  #####     #
114
115\section{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 rely on message passing or other paradigms that often closely relate to networking concepts. However, in imperative or OO languages, these approaches entail a clear distinction between concurrent and non-concurrent paradigms (i.e. message passing versus routine call). Which in turns mean that programmers need to learn two sets of designs patterns in order to be effective. Approaches based on shared memory are more closely related to non-concurrent paradigms since they often rely on non-concurrent constructs like routine calls and objects. At a lower level these can be implemented as locks and atomic operations. However, for productivity reasons it is desireable to have a higher-level construct to be the core concurrency paradigm\cite{HPP:Study}. This project proposes Monitors\cite{Hoare74} as the core concurrency construct.
117% \\
118
119Several 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 rely on message passing\cite{Thoth,Harmony,V-Kernel} or other paradigms that often closely relate to networking concepts. However, in imperative or OO languages, these approaches entail a clear distinction between concurrent and non-concurrent paradigms (i.e. message passing versus routine call). Which in turns mean that programmers need to learn two sets of designs patterns in order to be effective. Approaches based on shared memory are more closely related to non-concurrent paradigms since they often rely on non-concurrent 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 to be the core concurrency paradigm\cite{HPP:Study}. One of the most natural, elegant, and efficient mechanisms for synchronization and communication, especially for shared memory systems, is the \emph{monitor}.
120
121Monitors were first proposed by Brinch Hansen~\cite{Hansen73} and later described and extended by C.A.R.~Hoare~\cite{Hoare74}.
122Many 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.
123\\
124
125Finally, an approach that is worth mentionning because it is gaining in popularity is transactionnal memory\cite{Dice10}. However, the performance and feature set is currently too restrictive to be possible 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.
126
127% #     # ####### #     # ### ####### ####### ######   #####
128% ##   ## #     # ##    #  #     #    #     # #     # #     #
129% # # # # #     # # #   #  #     #    #     # #     # #
130% #  #  # #     # #  #  #  #     #    #     # ######   #####
131% #     # #     # #   # #  #     #    #     # #   #         #
132% #     # #     # #    ##  #     #    #     # #    #  #     #
133% #     # ####### #     # ###    #    ####### #     #  #####
134
135\subsection{Monitors}
136A 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 :
137\begin{lstlisting}
138        typedef /*some monitor type*/ monitor;
139        int f(monitor & m);
140
141        int main() {
142                monitor m;
143                f(m);
144        }
145\end{lstlisting}
146
147%  #####     #    #       #
148% #     #   # #   #       #
149% #        #   #  #       #
150% #       #     # #       #
151% #       ####### #       #
152% #     # #     # #       #
153%  #####  #     # ####### #######
154
155\subsubsection{Call semantics} \label{call}
156The above example of monitors already displays some of their intrinsic caracteristics. 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.
157\\
158
159Another aspect to consider is when a monitor acquires its mutual exclusion. Indeed, a monitor may need to be passed through multiple helper routines that do not acquire the monitor mutual exclusion on entry. Examples of this can be both generic helper routines (\code{swap}, \code{sort}, etc.) or specific helper routines like the following example :
160
161\begin{lstlisting}
162        mutex struct counter_t { /*...*/ };
163
164        void ?{}(counter_t & nomutex this);
165        int ++?(counter_t & mutex this);
166        void ?{}(Int * this, counter_t & mutex cnt);
167\end{lstlisting}
168*semantics of the declaration of \code{mutex struct counter_t} are discussed in details in section \ref{data}
169\\
170
171This example is of a monitor implementing an atomic counter. Here, the constructor uses the \code{nomutex} keyword to signify that it does not acquire the coroutine mutual exclusion when constructing. This is because object not yet constructed should never be shared and therefore do not require mutual exclusion. The prefix increment operator
172uses \code{mutex} to protect the incrementing process from race conditions. Finally, we have a conversion operator from \code{counter_t} to \code{Int}. This conversion may or may not require the \code{mutex} key word depending whether or not reading an \code{Int} is an atomic operation or not.
173\\
174
175Having 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. If there were a meaning to routine \code{void foo(counter_t & this)} then one could argue that it should be to 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 this is the more "normal" behavior, \code{nomutex} effectively stating explicitly that "this routine has nothing special". An other alternative is to make 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 more clearly self-documented but at the cost of extra typing. In the end, which solution should be picked is still up for debate. For the reminder of this proposal, the explicit approach will be used for the sake of clarity.
176\\
177
178Regardless of which keyword is kept, it is important to establish when mutex/nomutex may be used depending on type parameters.
179\begin{lstlisting}
180        int f1(monitor & mutex m);
181        int f2(const monitor & mutex m);
182        int f3(monitor ** mutex m);
183        int f4(monitor *[] mutex m);
184        int f5(graph(monitor*) & mutex m);
185\end{lstlisting}
186
187The problem is to indentify which object(s) should be acquired. Furthermore we also need to acquire each objects only once. In case of simple routines like \code{f1} and \code{f2} it is easy to identify an exhaustive list of objects to acquire on entering. Adding indirections (\code{f3}) still allows the compiler and programmer to indentify which object will be acquired. However, adding in arrays (\code{f4}) makes it much harder. Array lengths aren't 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 custom 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 (ignoring potential qualifiers and indirections).
188
189% ######     #    #######    #
190% #     #   # #      #      # #
191% #     #  #   #     #     #   #
192% #     # #     #    #    #     #
193% #     # #######    #    #######
194% #     # #     #    #    #     #
195% ######  #     #    #    #     #
196
197\subsubsection{Data semantics} \label{data}
198Once 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 appripriate protection. For example here is a more fleshed-out version of the counter showed in \ref{call}:
199\begin{lstlisting}
200        mutex struct counter_t {
201                int value;
202        };
203
204        void ?{}(counter_t & nomutex this) {
205                this.cnt = 0;
206        }
207
208        int ++?(counter_t & mutex this) {
209                return ++this->value;
210        }
211
212        void ?{}(int * this, counter_t & mutex cnt) {
213                *this = (int)cnt;
214        }
215\end{lstlisting}
216\begin{tabular}{ c c }
217Thread 1 & Thread 2 \\
218\begin{lstlisting}
219        void f(counter_t & mutex c) {
220                for(;;) {
221                        sout | (int)c | endl;
222                }
223        }
224\end{lstlisting} &\begin{lstlisting}
225        void g(counter_t & mutex c) {
226                for(;;) {
227                        ++c;
228                }
229        }
230
231\end{lstlisting}
232\end{tabular}
233\\
234
235
236This simple counter offers an example of monitor usage. Notice how the counter is used without any explicit synchronisation and yet supports thread-safe semantics for both reading and writting. \\
237
238These simple mutual exclusion semantics also naturally expand to multi-monitor calls.
239\begin{lstlisting}
240        int f(MonitorA & mutex a, MonitorB & mutex b);
241
242        MonitorA a;
243        MonitorB b;
244        f(a,b);
245\end{lstlisting}
246
247This code acquires both locks before entering the critical section. In practice, writing multi-locking routines that can not lead to deadlocks can be very tricky. Having language level support for such feature is therefore a significant asset for \CFA. However, this does have significant repercussions relating to scheduling (see \ref{insched} and \ref{extsched}). Furthermore, the ability to acquire multiple monitors at the same time does incur a significant pitfall even without looking into scheduling. For example :
248\begin{lstlisting}
249        void foo(A & mutex a, B & mutex a) {
250                //...
251        }
252
253        void bar(A & mutex a, B & nomutex a)
254                //...
255                foo(a, b);
256                //...
257        }
258
259        void baz(A & nomutex a, B & mutex a)
260                //...
261                foo(a, b);
262                //...
263        }
264\end{lstlisting}
265
266Recursive mutex routine calls are allowed in \CFA but if not done carefully it can lead to nested monitor call problems\cite{Lister77}. These problems which are a specific  implementation of the lock acquiring order problem. In the example above, the user uses implicit ordering in the case of function \code{bar} but explicit ordering in the case of \code{baz}. This subtle mistake can mean that calling these two functions concurrently will lead to deadlocks, depending on the implicit ordering matching the explicit ordering. As shown on several occasion\cit, there isn't really any solutions to this problem, users simply need to be carefull when acquiring multiple monitors at the same time.
267
268% ######  ####### #######    #    ### #        #####
269% #     # #          #      # #    #  #       #     #
270% #     # #          #     #   #   #  #       #
271% #     # #####      #    #     #  #  #        #####
272% #     # #          #    #######  #  #             #
273% #     # #          #    #     #  #  #       #     #
274% ######  #######    #    #     # ### #######  #####
275%
276%             ######  ####### #       #     # #     # ####### ######  #     #
277%             #     # #     # #        #   #  ##   ## #     # #     # #     #
278%             #     # #     # #         # #   # # # # #     # #     # #     #
279%  #####    ######  #     # #          #    #  #  # #     # ######  #######
280%             #       #     # #          #    #     # #     # #   #   #     #
281%             #       #     # #          #    #     # #     # #    #  #     #
282%             #       ####### #######    #    #     # ####### #     # #     #
283
284\subsubsection{Implementation Details: Interaction with polymorphism}
285At first glance, interaction between monitors and \CFA's concept of polymorphism seem complexe to support. However, it can be reasoned that entry-point locking can solve most of the issues that could be present with polymorphism.
286
287First 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. We must remember that monitors' 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 handle incomplete types (by definition) no \code{dtype} polymorphic routine can access shared data since the data would require knowledge about the type. Therefore the only concern when combining \code{dtype} polymorphism and monitors is to protect access to routines. With callsite-locking, this would require significant amount of work since any \code{dtype} routine could have to obtain some lock before calling a routine. However, with entry-point-locking calling a monitor routine becomes exactly the same as calling it from anywhere else.
288
289% ### #     # #######         #####   #####  #     # ####### ######
290%  #  ##    #    #           #     # #     # #     # #       #     #
291%  #  # #   #    #           #       #       #     # #       #     #
292%  #  #  #  #    #            #####  #       ####### #####   #     #
293%  #  #   # #    #    ###          # #       #     # #       #     #
294%  #  #    ##    #    ###    #     # #     # #     # #       #     #
295% ### #     #    #    ###     #####   #####  #     # ####### ######
296
297\subsection{Internal scheduling} \label{insched}
298Monitors should also be able to schedule what threads access it 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 wait for them to be signaled. Here is a simple example of such a technique :
299
300\begin{lstlisting}
301        mutex struct A {
302                condition e;
303        }
304
305        void foo(A & mutex a) {
306                //...
307                wait(a.e);
308                //...
309        }
310
311        void bar(A & mutex a) {
312                signal(a.e);
313        }
314\end{lstlisting}
315
316Here routine \code{foo} waits on the \code{signal} from \code{bar} before making further progress, effectively ensuring a basic ordering. This semantic can easily be extended to multi-monitor calls by offering the same guarantee.
317
318\begin{center}
319\begin{tabular}{ c @{\hskip 0.65in} c }
320Thread 1 & Thread 2 \\
321\begin{lstlisting}
322void foo(monitor & mutex a,
323         monitor & mutex b) {
324        //...
325        wait(a.e);
326        //...
327}
328
329foo(a, b);
330\end{lstlisting} &\begin{lstlisting}
331void bar(monitor & mutex a,
332         monitor & mutex b) {
333        signal(a.e);
334}
335
336
337
338bar(a, b);
339\end{lstlisting}
340\end{tabular}
341\end{center}
342
343A direct extension of the single monitor semantics would be 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. On the technical side, partially releasing lock is feasible but from the user perspective a choice must be made for the syntax of this feature. It is possible to do without any extra syntax by relying on order of acquisition (Note that here the use of helper routines is irrelevant, only routines the acquire mutual exclusion have an impact on internal scheduling):
344
345\begin{center}
346\begin{tabular}{|c|c|c|}
347Context 1 & Context 2 & Context 3 \\
348\hline
349\begin{lstlisting}
350condition e;
351
352void foo(monitor & mutex a,
353         monitor & mutex b) {
354        wait(e);
355}
356
357
358
359
360
361
362foo(a,b);
363\end{lstlisting} &\begin{lstlisting}
364condition e;
365
366void bar(monitor & mutex a,
367         monitor & nomutex b) {
368        foo(a,b);
369}
370
371void foo(monitor & mutex a,
372         monitor & mutex b) {
373        wait(e);
374}
375
376bar(a, b);
377\end{lstlisting} &\begin{lstlisting}
378condition e;
379
380void bar(monitor & mutex a,
381         monitor & nomutex b) {
382        foo(a,b);
383}
384
385void baz(monitor & nomutex a,
386         monitor & mutex b) {
387        wait(e);
388}
389
390bar(a, b);
391\end{lstlisting}
392\end{tabular}
393\end{center}
394
395This can be interpreted in two different ways :
396\begin{flushleft}
397\begin{enumerate}
398        \item \code{wait} atomically releases the monitors acquired by the inner-most routine, \underline{ignoring} nested calls.
399        \item \code{wait} atomically releases the monitors acquired by the inner-most routine, \underline{considering} nested calls.
400\end{enumerate}
401\end{flushleft}
402While the difference between these two is subtle, it has a significant impact. In the first case it means that the calls to \code{foo} would behave the same in Context 1 and 2. This semantic would also mean that the call to \code{wait} in routine \code{baz} would only release \code{monitor b}. While this may seem intuitive with these examples, it does have one significant implication, it creates a strong distinction between acquiring multiple monitors in sequence and acquiring the same monitors simulatenously, i.e. :
403
404\begin{center}
405\begin{tabular}{c @{\hskip 0.35in} c @{\hskip 0.35in} c}
406\begin{lstlisting}
407enterMonitor(a);
408enterMonitor(b);
409// do stuff
410leaveMonitor(b);
411leaveMonitor(a);
412\end{lstlisting} & != &\begin{lstlisting}
413enterMonitor(a);
414enterMonitor(a, b);
415// do stuff
416leaveMonitor(a, b);
417leaveMonitor(a);
418\end{lstlisting}
419\end{tabular}
420\end{center}
421
422This is not intuitive because even if both methods display the same monitors state both inside and outside the critical section respectively, the behavior is different. Furthermore, the actual acquiring order will be exaclty the same since acquiring a monitor from inside its mutual exclusion is a no-op. This means that even if the data and the actual control flow are the same using both methods, the behavior of the \code{wait} will be different. The alternative is option 2, that is releasing acquired monitors, \underline{considering} nesting. This solves the issue of having the two acquiring method differ at the cost of making routine \code{foo} behave differently depending on from which context it is called (Context 1 or 2). Indeed in Context 2, routine \code{foo} actually behaves like routine \code{baz} rather than having the same behavior than in Context 1. The fact that both implicit approaches can be unintuitive depending on the perspective may be a sign that the explicit approach is superior. For this reason this \CFA does not support implicit monitor releasing and uses explicit semantics.
423\\
424
425The following examples shows three alternatives of explicit wait semantics :
426\\
427
428\begin{center}
429\begin{tabular}{|c|c|c|}
430Case 1 & Case 2 & Case 3 \\
431Branding on construction & Explicit release list & Explicit ignore list \\
432\hline
433\begin{lstlisting}
434void foo(monitor & mutex a,
435         monitor & mutex b,
436           condition & c)
437{
438        // Releases monitors
439        // branded in ctor
440        wait(c);
441}
442
443monitor a;
444monitor b;
445condition1 c1 = {a};
446condition2 c2 = {a, b};
447
448//Will release only a
449foo(a,b,c1);
450
451//Will release a and b
452foo(a,b,c2);
453\end{lstlisting} &\begin{lstlisting}
454void foo(monitor & mutex a,
455         monitor & mutex b,
456           condition & c)
457{
458        // Releases monitor a
459        // Holds monitor b
460        waitRelease(c, [a]);
461}
462
463monitor a;
464monitor b;
465condition c;
466
467
468
469foo(a,b,c);
470
471
472
473\end{lstlisting} &\begin{lstlisting}
474void foo(monitor & mutex a,
475         monitor & mutex b,
476           condition & c)
477{
478        // Releases monitor a
479        // Holds monitor b
480        waitHold(c, [b]);
481}
482
483monitor a;
484monitor b;
485condition c;
486
487
488
489foo(a,b,c);
490
491
492
493\end{lstlisting}
494\end{tabular}
495\end{center}
496(Note : Case 2 and 3 use tuple semantics to pass a variable length list of elements.)
497\\
498
499All these cases have their pros and cons. Case 1 is more distinct because it means programmers need to be carefull about where the condition is initialized as well as where it is used. On the other hand, it is very clear and explicitly states which monitor is released and which monitor stays acquired. This is similar to Case 2, which releases only the monitors explictly listed. However, in Case 2, calling the \code{wait} routine instead of the \code{waitRelease} routine releases all the acquired monitor. The Case 3 is an improvement on that since it releases all the monitors except those specified. The result is that the \code{wait} routine can be written as follows :
500\begin{lstlisting}
501void wait(condition & cond) {
502        waitHold(cond, []);
503}
504\end{lstlisting}
505This alternative offers nice and consistent behavior between \code{wait} and \code{waitHold}. However, one large pitfall is that mutual exclusion can now be violated by calls to library code. Indeed, even if the following example seems benign there is one significant problem :
506\begin{lstlisting}
507monitor global;
508
509extern void doStuff(); //uses global
510
511void foo(monitor & mutex m) {
512        //...
513        doStuff(); //warning can release monitor m
514        //...
515}
516
517foo(global);
518\end{lstlisting}
519
520Indeed, if Case 2 or 3 are chosen it any code can violate the mutual exclusion of the calling code by issuing calls to \code{wait} or \code{waitHold} in a nested monitor context. Case 2 can be salvaged by removing the \code{wait} routine from the API but Case 3 cannot prevent users from calling \code{waitHold(someCondition, [])}. For this reason the syntax proposed in Case 3 is rejected. Note that the syntax proposed in case 1 and 2 are not exclusive. Indeed, by supporting two types of condition both cases can be supported :
521\begin{lstlisting}
522struct condition { /*...*/ };
523
524// Second argument is a variable length tuple.
525void wait(condition & cond, [...] monitorsToRelease);
526void signal(condition & cond);
527
528struct conditionN { /*...*/ };
529
530void ?{}(conditionN* this, /*list of N monitors to release*/);
531void wait(conditionN & cond);
532void signal(conditionN & cond);
533\end{lstlisting}
534
535Regardless of the option chosen for wait semantics, signal must be symmetrical. 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.
536
537Finally, an additionnal semantic which can be very usefull is the \code{signalBlock} 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.
538\\
539
540% ####### #     # #######         #####   #####  #     # ####### ######
541% #        #   #     #           #     # #     # #     # #       #     #
542% #         # #      #           #       #       #     # #       #     #
543% #####      #       #            #####  #       ####### #####   #     #
544% #         # #      #    ###          # #       #     # #       #     #
545% #        #   #     #    ###    #     # #     # #     # #       #     #
546% ####### #     #    #    ###     #####   #####  #     # ####### ######
547
548\subsection{External scheduling} \label{extsched}
549As one might expect, the alternative to Internal scheduling is to use External scheduling instead. This method is somewhat more robust to deadlocks since one of the threads keeps a relatively tight control on scheduling. Indeed, as the following examples will demonstrate, 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 what a simple use \code{accept} versus \code{wait}/\code{signal} and its advantages.
550
551\begin{center}
552\begin{tabular}{|c|c|}
553Internal Scheduling & External Scheduling \\
554\hline
555\begin{lstlisting}
556        _Monitor blarg {
557                condition c;
558        public:
559                void f() { signal(c)}
560                void g() { wait(c); }
561        private:
562        }
563\end{lstlisting}&\begin{lstlisting}
564        _Monitor blarg {
565
566        public:
567                void f();
568                void g() { _Accept(f); }
569        private:
570        }
571\end{lstlisting}
572\end{tabular}
573\end{center}
574
575In the case of internal scheduling, the call to \code{wait} only guarantees that \code{g} was 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.
576\\
577
578% #       ####### #######  #####  #######    ####### ######        #  #####
579% #       #     # #     # #     # #          #     # #     #       # #     #
580% #       #     # #     # #       #          #     # #     #       # #
581% #       #     # #     #  #####  #####      #     # ######        #  #####
582% #       #     # #     #       # #          #     # #     # #     #       #
583% #       #     # #     # #     # #          #     # #     # #     # #     #
584% ####### ####### #######  #####  #######    ####### ######   #####   #####
585
586\subsubsection{Loose object definitions}
587In \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 :
588
589\begin{lstlisting}
590        mutex struct A {};
591
592        void f(A & mutex a);
593        void g(A & mutex a) { accept(f); }
594\end{lstlisting}
595
596However, 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 :
597
598\begin{center}
599\begin{tabular}{l}
600\begin{lstlisting}[language=Pseudo]
601        if monitor is free :
602                enter
603        elif monitor accepts me :
604                enter
605        else :
606                block
607\end{lstlisting}
608\end{tabular}
609\end{center}
610
611For the \pseudo{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 \pseudo{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 :
612
613\begin{center}
614{\resizebox{0.4\textwidth}{!}{\input{monitor}}}
615\end{center}
616
617There 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.
618The alternative would be to have a picture more like this one:
619
620\begin{center}
621{\resizebox{0.4\textwidth}{!}{\input{ext_monitor}}}
622\end{center}
623
624Not 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.
625
626At 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.
627
628In either cases here are a few alternatives for the different syntaxes this syntax : \\
629\begin{center}
630{\renewcommand{\arraystretch}{1.5}
631\begin{tabular}[t]{l @{\hskip 0.35in} l}
632\hline
633\multicolumn{2}{ c }{\code{accept} on type}\\
634\hline
635Alternative 1 & Alternative 2 \\
636\begin{lstlisting}
637mutex struct A
638accept( void f(A & mutex a) )
639{};
640\end{lstlisting} &\begin{lstlisting}
641mutex struct A {}
642accept( void f(A & mutex a) );
643
644\end{lstlisting} \\
645Alternative 3 & Alternative 4 \\
646\begin{lstlisting}
647mutex struct A {
648        accept( void f(A & mutex a) )
649};
650
651\end{lstlisting} &\begin{lstlisting}
652mutex struct A {
653        accept :
654                void f(A & mutex a) );
655};
656\end{lstlisting}\\
657\hline
658\multicolumn{2}{ c }{\code{accept} on routine}\\
659\hline
660\begin{lstlisting}
661mutex struct A {};
662
663void f(A & mutex a)
664
665accept( void f(A & mutex a) )
666void g(A & mutex a) {
667        /*...*/
668}
669\end{lstlisting}&\\
670\end{tabular}
671}
672\end{center}
673
674An 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.
675
676% #     # #     # #       ####### ###    #     # ####### #     #
677% ##   ## #     # #          #     #     ##   ## #     # ##    #
678% # # # # #     # #          #     #     # # # # #     # # #   #
679% #  #  # #     # #          #     #     #  #  # #     # #  #  #
680% #     # #     # #          #     #     #     # #     # #   # #
681% #     # #     # #          #     #     #     # #     # #    ##
682% #     #  #####  #######    #    ###    #     # ####### #     #
683
684\subsubsection{Multi-monitor scheduling}
685
686External 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 :
687\begin{lstlisting}
688        accept( void f(mutex struct A & mutex this))
689        mutex struct A {};
690
691        mutex struct B {};
692
693        void g(A & mutex a, B & mutex b) {
694                accept(f); //ambiguous, which monitor
695        }
696\end{lstlisting}
697
698The obvious solution is to specify the correct monitor as follows :
699
700\begin{lstlisting}
701        accept( void f(mutex struct A & mutex this))
702        mutex struct A {};
703
704        mutex struct B {};
705
706        void g(A & mutex a, B & mutex b) {
707                accept( f, b );
708        }
709\end{lstlisting}
710
711This 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.
712
713\begin{lstlisting}
714        accept( void f(mutex struct A & mutex, mutex struct A & mutex))
715        mutex struct A {};
716
717        mutex struct B {};
718
719        void g(A & mutex a, B & mutex b) {
720                accept( f, b, a );
721        }
722\end{lstlisting}
723
724Note 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.
725
726% ######  ####### #######    #    ### #        #####
727% #     # #          #      # #    #  #       #     #
728% #     # #          #     #   #   #  #       #
729% #     # #####      #    #     #  #  #        #####
730% #     # #          #    #######  #  #             #
731% #     # #          #    #     #  #  #       #     #
732% ######  #######    #    #     # ### #######  #####
733%
734%                #####  #     # ####### #     # #######  #####
735%             #     # #     # #       #     # #       #     #
736%             #     # #     # #       #     # #       #
737%    #####    #     # #     # #####   #     # #####    #####
738%             #   # # #     # #       #     # #             #
739%             #    #  #     # #       #     # #       #     #
740%                #### #  #####  #######  #####  #######  #####
741
742
743\subsubsection{Implementation Details: External scheduling queues}
744To 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.
745
746\subsection{Other concurrency tools}
747TO BE CONTINUED...
748
749\newpage
750% ######     #    ######     #    #       #       ####### #       ###  #####  #     #
751% #     #   # #   #     #   # #   #       #       #       #        #  #     # ##   ##
752% #     #  #   #  #     #  #   #  #       #       #       #        #  #       # # # #
753% ######  #     # ######  #     # #       #       #####   #        #   #####  #  #  #
754% #       ####### #   #   ####### #       #       #       #        #        # #     #
755% #       #     # #    #  #     # #       #       #       #        #  #     # #     #
756% #       #     # #     # #     # ####### ####### ####### ####### ###  #####  #     #
757\section{Parallelism}
758Historically, computer performance was about processor speeds and instructions count. However, with heat dissipation being an ever growing challenge, parallelism has become the new source of greatest performance \cite{Sutter05, Sutter05b}. In this decade, it is not longer reasonnable to create 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}. 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 which all have strengths and weaknesses.
759
760\subsection{User-level threads}
761A 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 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 complexities are hidden, users still have to think about data races, deadlocks and synchronization issues. This can be somewhat alleviated by a concurrency toolkit with strong garantees but the parallelism toolkit offers very little to reduce complexity in itself.
762
763Examples of languages that support are Java\cite{Java}, Haskell\cite{Haskell} and \uC\cite{uC++book}.
764
765\subsection{Jobs and thread pools}
766The approach on the opposite end of the spectrum is to base parallelism on \glspl{job}. Indeed, \glspl{job} offer limited flexibility but at the benefit of a simpler user interface. In \gls{job} based systems users express parallelism as units of work and the dependency graph (either explicit or implicit) that tie them together. This means users need not to worry about concurrency but significantly limits the interaction that can occur between different jobs. Indeed, any \gls{job} that blocks also blocks the underlying \gls{kthread}, this effectively mean the CPU utilization, and therefore throughput, will suffer noticeably.
767The golden standard of this implementation is Intel's TBB library\cite{TBB}.
768
769\subsection{Fibers : user-level threads without preemption}
770Finally, in the middle of the flexibility versus complexity spectrum lay \glspl{fiber} which offer \glspl{uthread} without the complexity of preemption. This means users don't have to worry about other \glspl{fiber} suddenly executing between two instructions which signficantly reduces complexity. However, any call to IO or other concurrency primitives can lead to context switches. Furthermore, users can also block \glspl{fiber} in the middle of their execution without blocking a full processor core. This means users still have to worry about mutual exclusion, deadlocks and race conditions in their code, raising the complexity significantly.
771An example of a language that uses fibers is Go\cite{Go}
772
773\subsection{Paradigm performance}
774While the choice between the three paradigms listed above may have significant performance implication, it is difficult to pin the performance implications of chosing a model at the language level. Indeed, in many situations one of these paradigms will show better performance but it all strongly depends on the usage. Having mostly indepent units of work to execute almost guarantess that the \gls{job} based system will have the best performance. However, add interactions between jobs and the processor utilisation might suffer. User-level threads may allow maximum ressource utilisation but context switches will be more expansive and it is also harder for users to get perfect tunning. As with every example, fibers sit somewhat in the middle of the spectrum. Furthermore, if the units of uninterrupted work are large enough the paradigm choice will be largely amorticised by the actual work done.
775
776%  #####  #######    #          ####### ######  ######
777% #     # #         # #            #    #     # #     #
778% #       #        #   #           #    #     # #     #
779% #       #####   #     # #####    #    ######  ######
780% #       #       #######          #    #     # #     #
781% #     # #       #     #          #    #     # #     #
782%  #####  #       #     #          #    ######  ######
783
784\section{\CFA 's Thread Building Blocks}
785As 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, it is possible to deconstruct the three paradigms details aboved in order to get simple building blocks. Here is a table showing the core caracteristics of the mentionned paradigms :
786\begin{center}
787\begin{tabular}[t]{| r | c | c |}
788\cline{2-3}
789\multicolumn{1}{ c| }{} & Has a stack & Preemptive \\
790\hline
791\Glspl{job} & X & X \\
792\hline
793\Glspl{fiber} & \checkmark & X \\
794\hline
795\Glspl{uthread} & \checkmark & \checkmark \\
796\hline
797\end{tabular}
798\end{center}
799
800As shown in section \ref{cfaparadigms} these different blocks being available in \CFA it is trivial to reproduce any of these paradigm.
801
802% ####### #     # ######  #######    #    ######   #####
803%    #    #     # #     # #         # #   #     # #     #
804%    #    #     # #     # #        #   #  #     # #
805%    #    ####### ######  #####   #     # #     #  #####
806%    #    #     # #   #   #       ####### #     #       #
807%    #    #     # #    #  #       #     # #     # #     #
808%    #    #     # #     # ####### #     # ######   #####
809
810\subsection{Thread Interface}
811The 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 comparatievely to \glspl{kthread}). A thread can be declared using a struct declaration prefix with the \code{thread} as follows :
812
813\begin{lstlisting}
814        thread struct foo {};
815\end{lstlisting}
816
817Obviously, for this thread implementation to be usefull it must run some user code. Several other threading interfaces use some function pointer representation as the interface of threads (for example : \Csharp \cite{Csharp} and Scala \cite{Scala}). However, we consider that statically tying a \code{main} routine to a thread superseeds this approach. Since the \code{main} routine is definetely a special routine in \CFA, we can reuse the existing syntax for declaring routines with unordinary name, i.e. operator overloading. As such the \code{main} routine of a thread can be defined as such :
818\begin{lstlisting}
819        thread struct foo {};
820
821        void ?main(thread foo* this) {
822                /*... Some useful code ...*/
823        }
824\end{lstlisting}
825
826With these semantics it is trivial to write a thread type that takes a function pointer as parameter and executes it on its stack asynchronously :
827\begin{lstlisting}
828        typedef void (*voidFunc)(void);
829
830        thread struct FuncRunner {
831                voidFunc func;
832        };
833
834        //ctor
835        void ?{}(thread FuncRunner* this, voidFunc inFunc) {
836                func = inFunc;
837        }
838
839        //main
840        void ?main(thread FuncRunner* this) {
841                this->func();
842        }
843\end{lstlisting}
844
845% In this example \code{func} is a function pointer stored in \acrfull{tls}, which is \CFA is both easy to use and completly typesafe.
846
847Of 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 not needed. 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.
848\begin{lstlisting}
849thread struct FuncRunner; //FuncRunner declared above
850
851void world() {
852        sout | "World!" | endl;
853}
854
855void main() {
856        FuncRunner run = {world};
857        //Thread run forks here
858
859        //Print to "Hello " and "World!" will be run concurrently
860        sout | "Hello " | endl;
861
862        //Implicit join at end of scope
863}
864\end{lstlisting}
865This semantic has several advantages over explicit semantics : typesafety is guaranteed, any thread will always be started and stopped exaclty once and users can't make any progamming errors. Furthermore it naturally follows the memory allocation semantics which means users don't need to learn multiple semantics.
866
867These semantics also naturally scale to multiple threads meaning basic synchronisation is very simple :
868\begin{lstlisting}
869        thread struct MyThread {
870                //...
871        };
872
873        //ctor
874        void ?{}(thread MyThread* this) {}
875
876        //main
877        void ?main(thread MyThread* this) {
878                //...
879        }
880
881        void foo() {
882                MyThread thrds[10];
883                //Start 10 threads at the beginning of the scope
884
885                DoStuff();
886
887                //Wait for the 10 threads to finish
888        }
889\end{lstlisting}
890
891\newpage
892\large{\textbf{WORK IN PROGRESS}}
893\subsection{The \CFA Kernel : Processors, Clusters and Threads}\label{kernel}
894
895
896\subsection{Paradigms}\label{cfaparadigms}
897Given 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.
898
899% \subsection{High-level options}\label{tasks}
900%
901% \subsubsection{Thread interface}
902% constructors destructors
903%       initializer lists
904% monitors
905%
906% \subsubsection{Futures}
907%
908% \subsubsection{Implicit threading}
909% 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.
910%
911% \begin{center}
912% \begin{tabular}[t]{|c|c|c|}
913% Sequential & System Parallel & Language Parallel \\
914% \begin{lstlisting}
915% void big_sum(int* a, int* b,
916%                int* out,
917%                size_t length)
918% {
919%       for(int i = 0; i < length; ++i ) {
920%               out[i] = a[i] + b[i];
921%       }
922% }
923%
924%
925%
926%
927%
928% int* a[10000];
929% int* b[10000];
930% int* c[10000];
931% //... fill in a and b ...
932% big_sum(a, b, c, 10000);
933% \end{lstlisting} &\begin{lstlisting}
934% void big_sum(int* a, int* b,
935%                int* out,
936%                size_t length)
937% {
938%       range ar(a, a + length);
939%       range br(b, b + length);
940%       range or(out, out + length);
941%       parfor( ai, bi, oi,
942%       [](int* ai, int* bi, int* oi) {
943%               oi = ai + bi;
944%       });
945% }
946%
947% int* a[10000];
948% int* b[10000];
949% int* c[10000];
950% //... fill in a and b ...
951% big_sum(a, b, c, 10000);
952% \end{lstlisting}&\begin{lstlisting}
953% void big_sum(int* a, int* b,
954%                int* out,
955%                size_t length)
956% {
957%       for (ai, bi, oi) in (a, b, out) {
958%               oi = ai + bi;
959%       }
960% }
961%
962%
963%
964%
965%
966% int* a[10000];
967% int* b[10000];
968% int* c[10000];
969% //... fill in a and b ...
970% big_sum(a, b, c, 10000);
971% \end{lstlisting}
972% \end{tabular}
973% \end{center}
974%
975% \subsection{Machine setup}\label{machine}
976% Threads are all good and well but wee still some OS support to fully utilize available hardware.
977%
978% \textbf{\large{Work in progress...}} Do wee need something beyond specifying the number of kernel threads?
979
980%    #    #       #
981%   # #   #       #
982%  #   #  #       #
983% #     # #       #
984% ####### #       #
985% #     # #       #
986% #     # ####### #######
987\section{Putting it all together}
988
989
990
991
992
993
994
995
996
997
998% ####### #     # ####### #     # ######  #######
999% #       #     #    #    #     # #     # #
1000% #       #     #    #    #     # #     # #
1001% #####   #     #    #    #     # ######  #####
1002% #       #     #    #    #     # #   #   #
1003% #       #     #    #    #     # #    #  #
1004% #        #####     #     #####  #     # ######
1005\section{Future work}
1006Concurrency 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.
1007\subsection{Transactions}
1008
1009% ####### #     # ######
1010% #       ##    # #     #
1011% #       # #   # #     #
1012% #####   #  #  # #     #
1013% #       #   # # #     #
1014% #       #    ## #     #
1015% ####### #     # ######
1016\section*{Acknowledgements}
1017
1018\clearpage
1019\printglossary[type=\acronymtype]
1020\printglossary
1021
1022\clearpage
1023\bibliographystyle{plain}
1024\bibliography{cw92,distSharedMem,lfp92,mlw92,parallel,parallelIO,partheory,pl,pldi92,ps,realtime,techreportsPAB,visual,local}
1025
1026
1027\end{document}
Note: See TracBrowser for help on using the repository browser.