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3\chapter{Channels}\label{s:channels}
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6
7Most modern concurrent programming languages do not subscribe to just one style of communication among threads and provide features that support multiple approaches.
8Channels are a concurrent-language feature used to perform \Newterm{message-passing concurrency}: a model of concurrency where threads communicate by sending data as messages (mostly non\-blocking) and synchronizing by receiving sent messages (blocking).
9This model is an alternative to shared-memory concurrency, where threads communicate directly by changing shared state.
10
11Channels were first introduced by Kahn~\cite{Kahn74} and extended by Hoare~\cite{CSP} (CSP).
12Both papers present a pseudo (unimplemented) concurrent language where processes communicate using input/output channels to send data.
13Both languages are highly restrictive.
14Kahn's language restricts a reading process to only wait for data on a single channel at a time and different writing processes cannot send data on the same channel.
15Hoare's language restricts both the sender and receiver to explicitly name the process that is the destination of a channel send or the source of a channel receive.
16These channel semantics remove the ability to have an anonymous sender or receiver.
17Additionally all channel operations in CSP are synchronous (no buffering).
18Advanced channels as a programming language feature has been popularized in recent years by the language Go~\cite{Go}, which encourages the use of channels as its fundamental concurrent feature.
19It was the popularity of Go channels that lead to their implementation in \CFA.
20Neither Go nor \CFA channels have the restrictions of the early channel-based concurrent systems.
21
22Other popular languages and libraries that provide channels include C++ Boost~\cite{boost:channel}, Rust~\cite{rust:channel}, Haskell~\cite{haskell:channel}, and OCaml~\cite{ocaml:channel}.
23Boost channels only support asynchronous (non-blocking) operations, and Rust channels are limited to only having one consumer per channel.
24Haskell channels are unbounded in size, and OCaml channels are zero-size.
25These restrictions in Haskell and OCaml are likely due to their functional approach, which results in them both using a list as the underlying data structure for their channel.
26These languages and libraries are not discussed further, as their channel implementation is not comparable to the bounded-buffer style channels present in Go and \CFA.
27
28\section{Producer-Consumer Problem}
29A channel is an abstraction for a shared-memory buffer, which turns the implementation of a channel into the producer-consumer problem.
30The producer-consumer problem, also known as the bounded-buffer problem, was introduced by Dijkstra~\cite[\S~4.1]{Dijkstra65}.
31In the problem, threads interact with a buffer in two ways: producing threads insert values into the buffer and consuming threads remove values from the buffer.
32In general, a buffer needs protection to ensure a producer only inserts into a non-full buffer and a consumer only removes from a non-empty buffer (synchronization).
33As well, a buffer needs protection from concurrent access by multiple producers or consumers attempting to insert or remove simultaneously (MX).
34
35\section{Channel Size}\label{s:ChannelSize}
36Channels come in three flavours of buffers:
37\begin{enumerate}
38\item
39Zero sized implies the communication is synchronous, \ie the producer must wait for the consumer to arrive or vice versa for a value to be communicated.
40\item
41Fixed sized (bounded) implies the communication is mostly asynchronous, \ie the producer can proceed up to the buffer size and vice versa for the consumer with respect to removal, at which point the producer/consumer would wait.
42\item
43Infinite sized (unbounded) implies the communication is asynchronous, \ie the producer never waits but the consumer waits when the buffer is empty.
44Since memory is finite, all unbounded buffers are ultimately bounded;
45this restriction must be part of its implementation.
46\end{enumerate}
47
48In general, the order values are processed by the consumer does not affect the correctness of the producer-consumer problem.
49For example, the buffer can be \gls{lifo}, \gls{fifo}, or prioritized with respect to insertion and removal.
50However, like MX, a buffer should ensure every value is eventually removed after some reasonable bounded time (no long-term starvation).
51The simplest way to prevent starvation is to implement the buffer as a queue, either with a cyclic array or linked nodes.
52
53\section{First-Come First-Served}
54As pointed out, a bounded buffer requires MX among multiple producers or consumers.
55This MX should be fair among threads, independent of the \gls{fifo} buffer being fair among values.
56Fairness among threads is called \gls{fcfs} and was defined by Lamport~\cite[p.~454]{Lamport74}.
57\gls{fcfs} is defined in relation to a doorway~\cite[p.~330]{Lamport86II}, which is the point at which an ordering among threads can be established.
58Given this doorway, a CS is said to be \gls{fcfs}, if threads access the shared resource in the order they proceed through the doorway.
59A consequence of \gls{fcfs} execution is the elimination of \Newterm{barging}, where barging means a thread arrives at a CS with waiting threads, and the MX protecting the CS allows the arriving thread to enter the CS ahead of one or more of the waiting threads.
60
61\gls{fcfs} is a fairness property that prevents unequal access to the shared resource and prevents starvation, however it comes at a cost.
62Implementing an algorithm with \gls{fcfs} can lead to \Newterm{double blocking}, where arriving threads block outside the doorway waiting for a thread in the lock entry-protocol and inside the doorway waiting for a thread in the CS.
63An analogue is boarding an airplane: first you wait to get through security to the departure gates (short term), and then wait again at the departure gate for the airplane (long term).
64As such, algorithms that are not \gls{fcfs} (barging) can be more performant by skipping the wait for the CS and entering directly;
65however, this performance gain comes by introducing unfairness with possible starvation for waiting threads.
66
67\section{Channel Implementation}\label{s:chan_impl}
68Currently, only the Go and Erlang programming languages provide user-level threading where the primary communication mechanism is channels.
69Both Go and Erlang have user-level threading and preemptive scheduling, and both use channels for communication.
70Go provides multiple homogeneous channels; each have a single associated type.
71Erlang, which is closely related to actor systems, provides one heterogeneous channel per thread (mailbox) with a typed receive pattern.
72Go encourages users to communicate via channels, but provides them as an optional language feature.
73On the other hand, Erlang's single heterogeneous channel is a fundamental part of the threading system design; using it is unavoidable.
74Similar to Go, \CFA's channels are offered as an optional language feature.
75
76While iterating on channel implementation, experiments were conducted that varied the producer-consumer algorithm and lock type used inside the channel.
77With the exception of non-\gls{fcfs} or non-\gls{fifo} algorithms, no algorithm or lock usage in the channel implementation was found to be consistently more performant that Go's choice of algorithm and lock implementation.
78Performance of channels can be improved by sharding the underlying buffer \cite{Dice11}.
79However, the \gls{fifo} property is lost, which is undesirable for user-facing channels.
80Therefore, the low-level channel implementation in \CFA is largely copied from the Go implementation, but adapted to the \CFA type and runtime systems.
81As such the research contributions added by \CFA's channel implementation lie in the realm of safety and productivity features.
82
83The Go channel implementation utilizes cooperation among threads to achieve good performance~\cite{go:chan}.
84This cooperation only occurs when producers or consumers need to block due to the buffer being full or empty.
85In these cases, a blocking thread stores their relevant data in a shared location and the signalling thread completes the blocking thread's operation before waking them;
86\ie the blocking thread has no work to perform after it unblocks because the signalling threads has done this work.
87This approach is similar to wait morphing for locks~\cite[p.~82]{Butenhof97} and improves performance in a few ways.
88First, each thread interacting with the channel only acquires and releases the internal channel lock once.
89As a result, contention on the internal lock is decreased; only entering threads compete for the lock since unblocking threads do not reacquire the lock.
90The other advantage of Go's wait-morphing approach is that it eliminates the bottleneck of waiting for signalled threads to run.
91Note that the property of acquiring/releasing the lock only once can also be achieved with a different form of cooperation, called \Newterm{baton passing}.
92Baton passing occurs when one thread acquires a lock but does not release it, and instead signals a thread inside the critical section, conceptually ``passing'' the mutual exclusion from the signalling thread to the signalled thread.
93The baton-passing approach has threads cooperate to pass mutual exclusion without additional lock acquires or releases;
94the wait-morphing approach has threads cooperate by completing the signalled thread's operation, thus removing a signalled thread's need for mutual exclusion after unblocking.
95While baton passing is useful in some algorithms, it results in worse channel performance than the Go approach.
96In the baton-passing approach, all threads need to wait for the signalled thread to reach the front of the ready queue, context switch, and run before other operations on the channel can proceed, since the signalled thread holds mutual exclusion;
97in the wait-morphing approach, since the operation is completed before the signal, other threads can continue to operate on the channel without waiting for the signalled thread to run.
98
99In this work, all channel sizes \see{Sections~\ref{s:ChannelSize}} are implemented with bounded buffers.
100However, only non-zero-sized buffers are analysed because of their complexity and higher usage.
101
102\section{Safety and Productivity}
103Channels in \CFA come with safety and productivity features to aid users.
104The features include the following.
105
106\begin{itemize}
107\item Toggle-able statistic collection on channel behaviour that count channel and blocking operations.
108Tracking blocking operations helps illustrate usage for tuning the channel size, where the aim is to reduce blocking.
109
110\item Deadlock detection on channel deallocation.
111If threads are blocked inside a channel when it terminates, this case is detected and the user is informed, as this can cause a deadlock.
112
113\item A @flush@ routine that delivers copies of an element to all waiting consumers, flushing the buffer.
114Programmers use this mechanism to broadcast a sentinel value to multiple consumers.
115Additionally, the @flush@ routine is more performant than looping around the @insert@ operation since it can deliver the elements without having to reacquire mutual exclusion for each element sent.
116
117\item Go-style @?<<?@ shorthand operator for inserting and removing.
118\begin{cfa}
119channel(int) chan;
120int i = 2;
121chan << i;                      $\C{// insert i into chan}$
122i << chan;              $\C{// remove element from chan into i}$
123\end{cfa}
124\end{itemize}
125
126\subsection{Toggle-able Statistics}
127As discussed, a channel is a concurrent layer over a bounded buffer.
128To achieve efficient buffering, users should aim for as few blocking operations on a channel as possible.
129Mechanisms to reduce blocking are: change the buffer size, shard a channel into multiple channels, or tweak the number of producer and consumer threads.
130For users to be able to make informed decisions when tuning channel usage, toggle-able channel statistics are provided.
131The statistics are toggled on during the \CFA build by defining the @CHAN_STATS@ macro, which guarantees zero cost when not using this feature.
132When statistics are turned on, four counters are maintained per channel, two for inserting (producers) and two for removing (consumers).
133The two counters per type of operation track the number of blocking operations and total operations.
134In the channel destructor, the counters are printed out aggregated and also per type of operation.
135An example use case is noting that producer inserts are blocking often while consumer removes do not block often.
136This information can be used to increase the number of consumers to decrease the blocking producer operations, thus increasing the channel throughput.
137Whereas, increasing the channel size in this scenario is unlikely to produce a benefit because the consumers can never keep up with the producers.
138
139\subsection{Deadlock Detection}
140The deadlock detection in the \CFA channels is fairly basic but detects a very common channel mistake during termination.
141That is, it detects the case where threads are blocked on the channel during channel deallocation.
142This case is guaranteed to deadlock since there are no other threads to supply or consume values needed by the waiting threads.
143Only if a user maintained a separate reference to the blocked threads and manually unblocks them outside the channel could the deadlock be avoid.
144However, without special semantics, this unblocking would generate other runtime errors where the unblocked thread attempts to access non-existing channel data or even a deallocated channel.
145More robust deadlock detection needs to be implemented separate from channels since it requires knowledge about the threading system and other channel/thread state.
146
147\subsection{Program Shutdown}
148Terminating concurrent programs is often one of the most difficult parts of writing concurrent code, particularly if graceful termination is needed.
149Graceful termination can be difficult to achieve with synchronization primitives that need to be handled carefully during shutdown.
150It is easy to deadlock during termination if threads are left behind on synchronization primitives.
151Additionally, most synchronization primitives are prone to \gls{toctou} issues where there is race between one thread checking the state of a concurrent object and another thread changing the state.
152\gls{toctou} issues with synchronization primitives often involve a race between one thread checking the primitive for blocked threads and another thread blocking on it.
153Channels are a particularly hard synchronization primitive to terminate since both sending and receiving to/from a channel can block.
154Thus, improperly handled \gls{toctou} issues with channels often result in deadlocks as threads performing the termination may end up unexpectedly blocking in their attempt to help other threads exit the system.
155
156\subsubsection{Go Channel Close}
157Go channels provide a set of tools to help with concurrent shutdown~\cite{go:chan} using a @close@ operation in conjunction with the \Go{select} statement.
158The \Go{select} statement is discussed in \ref{s:waituntil}, where \CFA's @waituntil@ statement is compared with the Go \Go{select} statement.
159
160The @close@ operation on a channel in Go changes the state of the channel.
161When a channel is closed, sends to the channel panic along with additional calls to @close@.
162Receives are handled differently.
163Receivers (consumers) never block on a closed channel and continue to remove elements from the channel.
164Once a channel is empty, receivers can continue to remove elements, but receive the zero-value version of the element type.
165To avoid unwanted zero-value elements, Go provides the ability to iterate over a closed channel to remove the remaining elements.
166These Go design choices enforce a specific interaction style with channels during termination: careful thought is needed to ensure additional @close@ calls do not occur and no sends occur after a channel is closed.
167These design choices fit Go's paradigm of error management, where users are expected to explicitly check for errors, rather than letting errors occur and catching them.
168If errors need to occur in Go, return codes are used to pass error information up call levels.
169Note that panics in Go can be caught, but it is not the idiomatic way to write Go programs.
170
171While Go's channel-closing semantics are powerful enough to perform any concurrent termination needed by a program, their lack of ease of use leaves much to be desired.
172Since both closing and sending panic once a channel is closed, a user often has to synchronize the senders (producers) before the channel can be closed to avoid panics.
173However, in doing so it renders the @close@ operation nearly useless, as the only utilities it provides are the ability to ensure receivers no longer block on the channel and receive zero-valued elements.
174This functionality is only useful if the zero-typed element is recognized as a sentinel value, but if another sentinel value is necessary, then @close@ only provides the non-blocking feature.
175To avoid \gls{toctou} issues during shutdown, a busy wait with a \Go{select} statement is often used to add or remove elements from a channel.
176Hence, due to Go's asymmetric approach to channel shutdown, separate synchronization between producers and consumers of a channel has to occur during shutdown.
177
178\subsubsection{\CFA Channel Close}
179\CFA channels have access to an extensive exception handling mechanism~\cite{Beach21}.
180As such \CFA uses an exception-based approach to channel shutdown that is symmetric for both producers and consumers, and supports graceful shutdown.
181
182Exceptions in \CFA support both termination and resumption.
183\Newterm{Termination exception}s perform a dynamic call that unwinds the stack preventing the exception handler from returning to the raise point, such as in \CC, Python and Java.
184\Newterm{Resumption exception}s perform a dynamic call that does not unwind the stack allowing the exception handler to return to the raise point.
185In \CFA, if a resumption exception is not handled, it is reraised as a termination exception.
186This mechanism is used to create a flexible and robust termination system for channels.
187
188When a channel in \CFA is closed, all subsequent calls to the channel raise a resumption exception at the caller.
189If the resumption is handled, the caller attempts to complete the channel operation.
190However, if the channel operation would block, a termination exception is thrown.
191If the resumption is not handled, the exception is rethrown as a termination.
192These termination exceptions allow for non-local transfer that is used to great effect to eagerly and gracefully shut down a thread.
193When a channel is closed, if there are any blocked producers or consumers inside the channel, they are woken up and also have a resumption thrown at them.
194The resumption exception, @channel_closed@, has internal fields to aid in handling the exception.
195The exception contains a pointer to the channel it is thrown from and a pointer to a buffer element.
196For exceptions thrown from @remove@, the buffer element pointer is null.
197For exceptions thrown from @insert@, the element pointer points to the buffer element that the thread attempted to insert.
198Utility routines @bool is_insert( channel_closed & e );@ and @bool is_remove( channel_closed & e );@ are provided for convenient checking of the element pointer.
199This element pointer allows the handler to know which operation failed and also allows the element to not be lost on a failed insert since it can be moved elsewhere in the handler.
200Furthermore, due to \CFA's powerful exception system, this data can be used to choose handlers based on which channel and operation failed.
201For example, exception handlers in \CFA have an optional predicate which can be used to trigger or skip handlers based on the content of the matching exception.
202It is worth mentioning that using exceptions for termination may incur a larger performance cost than the Go approach.
203However, this should not be an issue, since termination is rarely on the fast-path of an application.
204In contrast, ensuring termination can be easily implemented correctly is the aim of the exception approach.
205
206\section{\CFA / Go channel Examples}
207To highlight the differences between \CFA's and Go's close semantics, two examples are presented.
208The first example is a simple shutdown case, where there are producer threads and consumer threads operating on a channel for a fixed duration.
209Once the duration ends, producers and consumers terminate immediately leaving unprocessed elements in the channel.
210The second example extends the first by requiring the channel to be empty after shutdown.
211Both the first and second example are shown in Figure~\ref{f:ChannelTermination}.
212
213\begin{figure}
214\centering
215
216\begin{lrbox}{\myboxA}
217\begin{Golang}[aboveskip=0pt,belowskip=0pt]
218var channel chan int = make( chan int, 128 )
219var prodJoin chan int = make( chan int, 4 )
220var consJoin chan int = make( chan int, 4 )
221var cons_done, prod_done bool = false, false;
222func producer() {
223        for {
224                if prod_done { break }
225                channel <- 5
226        }
227        prodJoin <- 0 // synch with main thd
228}
229
230func consumer() {
231        for {
232                if cons_done { break }
233                <- channel
234        }
235        consJoin <- 0 // synch with main thd
236}
237
238
239func main() {
240        for j := 0; j < 4; j++ { go consumer() }
241        for j := 0; j < 4; j++ { go producer() }
242        time.Sleep( time.Second * 10 )
243        prod_done = true
244        for j := 0; j < 4 ; j++ { <- prodJoin }
245        cons_done = true
246        close(channel) // ensure no cons deadlock
247        @for elem := range channel {@
248                // process leftover values
249        @}@
250        for j := 0; j < 4; j++ { <- consJoin }
251}
252\end{Golang}
253\end{lrbox}
254
255\begin{lrbox}{\myboxB}
256\begin{cfa}[aboveskip=0pt,belowskip=0pt]
257channel( int ) chan{ 128 };
258thread Consumer {};
259thread Producer {};
260
261void main( Producer & this ) {
262        try {
263                for ()
264                        chan << 5;
265        } catch( channel_closed * ) {
266                // unhandled resume or full
267        }
268}
269void main( Consumer & this ) {
270        int i;
271        try {
272                for () { i << chan; }
273        @} catchResume( channel_closed * ) {@
274                // handled resume => consume from chan
275        } catch( channel_closed * ) {
276                // empty or unhandled resume
277        }
278}
279int main() {
280        Consumer c[4];
281        Producer p[4];
282        sleep( 10`s );
283        close( chan );
284}
285
286
287
288
289
290
291\end{cfa}
292\end{lrbox}
293
294\subfloat[Go style]{\label{l:go_chan_term}\usebox\myboxA}
295\hspace*{3pt}
296\vrule
297\hspace*{3pt}
298\subfloat[\CFA style]{\label{l:cfa_chan_term}\usebox\myboxB}
299\caption{Channel Termination Examples 1 and 2. Code specific to example 2 is highlighted.}
300\label{f:ChannelTermination}
301\end{figure}
302
303Figure~\ref{l:go_chan_term} shows the Go solution.
304Since some of the elements being passed through the channel are zero-valued, closing the channel in Go does not aid in communicating shutdown.
305Instead, a different mechanism to communicate with the consumers and producers needs to be used.
306Flag variables are common in Go-channel shutdown-code to avoid panics on a channel, meaning the channel shutdown has to be communicated with threads before it occurs.
307Hence, the two flags @cons_done@ and @prod_done@ are used to communicate with the producers and consumers, respectively.
308Furthermore, producers and consumers need to shutdown separately to ensure that producers terminate before the channel is closed to avoid panicking, and to avoid the case where all the consumers terminate first, which can result in a deadlock for producers if the channel is full.
309The producer flag is set first;
310then after all producers terminate, the consumer flag is set and the channel is closed leaving elements in the buffer.
311To purge the buffer, a loop is added (red) that iterates over the closed channel to process any remaining values.
312
313Figure~\ref{l:cfa_chan_term} shows the \CFA solution.
314Here, shutdown is communicated directly to both producers and consumers via the @close@ call.
315A @Producer@ thread knows to stop producing when the @insert@ call on a closed channel raises exception @channel_closed@.
316If a @Consumer@ thread ignores the first resumption exception from the @close@, the exception is reraised as a termination exception and elements are left in the buffer.
317If a @Consumer@ thread handles the resumptions exceptions (red), control returns to complete the remove.
318A @Consumer@ thread knows to stop consuming after all elements of a closed channel are removed and the consumer would block, which causes a termination raise of @channel_closed@.
319The \CFA semantics allow users to communicate channel shutdown directly through the channel, without having to share extra state between threads.
320Additionally, when the channel needs to be drained, \CFA provides users with easy options for processing the leftover channel values in the main thread or in the consumer threads.
321
322Figure~\ref{f:ChannelBarrierTermination} shows a final shutdown example using channels to implement a barrier.
323A Go and \CFA style solution are presented but both are implemented using \CFA syntax so they can be easily compared.
324Implementing a barrier is interesting because threads are both producers and consumers on the barrier-internal channels, @entryWait@ and @barWait@.
325The outline for the barrier implementation starts by initially filling the @entryWait@ channel with $N$ tickets in the barrier constructor, allowing $N$ arriving threads to remove these values and enter the barrier.
326After @entryWait@ is empty, arriving threads block when removing.
327However, the arriving threads that entered the barrier cannot leave the barrier until $N$ threads have arrived.
328Hence, the entering threads block on the empty @barWait@ channel until the $N$th arriving thread inserts $N-1$ elements into @barWait@ to unblock the $N-1$ threads calling @remove@.
329The race between these arriving threads blocking on @barWait@ and the $N$th thread inserting values into @barWait@ does not affect correctness;
330\ie an arriving thread may or may not block on channel @barWait@ to get its value.
331Finally, the last thread to remove from @barWait@ with ticket $N-2$, refills channel @entryWait@ with $N$ values to start the next group into the barrier.
332
333Now, the two channels makes termination synchronization between producers and consumers difficult.
334Interestingly, the shutdown details for this problem are also applicable to other problems with threads producing and consuming from the same channel.
335The Go-style solution cannot use the Go @close@ call since all threads are both potentially producers and consumers, causing panics on close to be unavoidable without complex synchronization.
336As such in Figure \ref{l:go_chan_bar}, a flush routine is needed to insert a sentinel value, @-1@, to inform threads waiting in the buffer they need to leave the barrier.
337This sentinel value has to be checked at two points along the fast-path and sentinel values daisy-chained into the buffers.
338Furthermore, an additional flag @done@ is needed to communicate to threads once they have left the barrier that they are done.
339Also note that in the Go version~\ref{l:go_chan_bar}, the size of the barrier channels has to be larger than in the \CFA version to ensure that the main thread does not block when attempting to clear the barrier.
340For The \CFA solution~\ref{l:cfa_chan_bar}, the barrier shutdown results in an exception being thrown at threads operating on it, to inform waiting threads they must leave the barrier.
341This avoids the need to use a separate communication method other than the barrier, and avoids extra conditional checks on the fast path of the barrier implementation.
342
343\begin{figure}
344\centering
345
346\begin{lrbox}{\myboxA}
347\begin{cfa}[aboveskip=0pt,belowskip=0pt]
348struct barrier {
349        channel( int ) barWait, entryWait;
350        int size;
351};
352void ?{}( barrier & this, int size ) with(this) {
353        barWait{size + 1};   entryWait{size + 1};
354        this.size = size;
355        for ( i; size )
356                insert( entryWait, i );
357}
358void wait( barrier & this ) with(this) {
359        int ticket = remove( entryWait );
360        @if ( ticket == -1 ) { insert( entryWait, -1 ); return; }@
361        if ( ticket == size - 1 ) {
362                for ( i; size - 1 )
363                        insert( barWait, i );
364                return;
365        }
366        ticket = remove( barWait );
367        @if ( ticket == -1 ) { insert( barWait, -1 ); return; }@
368        if ( size == 1 || ticket == size - 2 ) { // last ?
369                for ( i; size )
370                        insert( entryWait, i );
371        }
372}
373void flush(barrier & this) with(this) {
374        @insert( entryWait, -1 );   insert( barWait, -1 );@
375}
376enum { Threads = 4 };
377barrier b{Threads};
378@bool done = false;@
379thread Thread {};
380void main( Thread & this ) {
381        for () {
382          @if ( done ) break;@
383                wait( b );
384        }
385}
386int main() {
387        Thread t[Threads];
388        sleep(10`s);
389        done = true;
390        flush( b );
391} // wait for threads to terminate
392\end{cfa}
393\end{lrbox}
394
395\begin{lrbox}{\myboxB}
396\begin{cfa}[aboveskip=0pt,belowskip=0pt]
397struct barrier {
398        channel( int ) barWait, entryWait;
399        int size;
400};
401void ?{}( barrier & this, int size ) with(this) {
402        barWait{size};   entryWait{size};
403        this.size = size;
404        for ( i; size )
405                insert( entryWait, i );
406}
407void wait( barrier & this ) with(this) {
408        int ticket = remove( entryWait );
409
410        if ( ticket == size - 1 ) {
411                for ( i; size - 1 )
412                        insert( barWait, i );
413                return;
414        }
415        ticket = remove( barWait );
416
417        if ( size == 1 || ticket == size - 2 ) { // last ?
418                for ( i; size )
419                        insert( entryWait, i );
420        }
421}
422void flush(barrier & this) with(this) {
423        @close( barWait );   close( entryWait );@
424}
425enum { Threads = 4 };
426barrier b{Threads};
427
428thread Thread {};
429void main( Thread & this ) {
430        @try {@
431                for ()
432                        wait( b );
433        @} catch ( channel_closed * ) {}@
434}
435int main() {
436        Thread t[Threads];
437        sleep(10`s);
438
439        flush( b );
440} // wait for threads to terminate
441\end{cfa}
442\end{lrbox}
443
444\subfloat[Go style]{\label{l:go_chan_bar}\usebox\myboxA}
445\hspace*{3pt}
446\vrule
447\hspace*{3pt}
448\subfloat[\CFA style]{\label{l:cfa_chan_bar}\usebox\myboxB}
449\caption{Channel Barrier Termination}
450\label{f:ChannelBarrierTermination}
451\end{figure}
452
453\section{Performance}
454
455Given that the base implementation of the \CFA channels is very similar to the Go implementation, this section aims to show the performance of the two implementations are comparable.
456The microbenchmark for the channel comparison is similar to Figure~\ref{f:ChannelTermination}, where the number of threads and processors is set from the command line.
457The processors are divided equally between producers and consumers, with one producer or consumer owning each core.
458The number of cores is varied to measure how throughput scales.
459
460The results of the benchmark are shown in Figure~\ref{f:chanPerf}.
461The performance of Go and \CFA channels on this microbenchmark is comparable.
462Note that the performance should decline as the number of cores increases as the channel operations occur in a critical section, so increasing cores results in higher contention with no increase in parallelism.
463
464The performance of \CFA and Go's shutdown mechanisms is not measured, as shutdown is an exceptional case that does not occur frequently in most programs. Additionally, it is difficult to measure channel shutdown performance; threads need to be synchronized between each subsequent shutdown, which is likely more expensive than the shutdown mechanism itself.
465
466\begin{figure}
467        \centering
468        \subfloat[AMD Channel Benchmark]{
469                \resizebox{0.5\textwidth}{!}{\input{figures/nasus_Channel_Contention.pgf}}
470                \label{f:chanAMD}
471        }
472        \subfloat[Intel Channel Benchmark]{
473                \resizebox{0.5\textwidth}{!}{\input{figures/pyke_Channel_Contention.pgf}}
474                \label{f:chanIntel}
475        }
476        \caption{The channel contention benchmark comparing \CFA and Go channel throughput (higher is better).}
477        \label{f:chanPerf}
478\end{figure}
479
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