Concurrent computing: Difference between revisions
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=={{header|APL}}== |
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{{works with|Dyalog APL}} |
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Dyalog APL supports the <code>&</code> operator, which runs a function on its own thread. |
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<lang APL>{⎕←⍵}&¨'Enjoy' 'Rosetta' 'Code'</lang> |
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{{out}} |
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(Example) |
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<pre>Enjoy |
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Code |
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Rosetta</pre> |
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=={{header|Astro}}== |
=={{header|Astro}}== |
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Revision as of 12:20, 16 June 2021
You are encouraged to solve this task according to the task description, using any language you may know.
- Task
Using either native language concurrency syntax or freely available libraries, write a program to display the strings "Enjoy" "Rosetta" "Code", one string per line, in random order.
Concurrency syntax must use threads, tasks, co-routines, or whatever concurrency is called in your language.
Ada
<lang ada>with Ada.Text_IO, Ada.Numerics.Float_Random;
procedure Concurrent_Hello is
type Messages is (Enjoy, Rosetta, Code);
task type Writer (Message : Messages);
task body Writer is
Seed : Ada.Numerics.Float_Random.Generator;
begin
Ada.Numerics.Float_Random.Reset (Seed); -- time-dependent, see ARM A.5.2
delay Duration (Ada.Numerics.Float_Random.Random (Seed));
Ada.Text_IO.Put_Line (Messages'Image(Message));
end Writer;
Taks: array(Messages) of access Writer -- 3 Writer tasks will immediately run
:= (new Writer(Enjoy), new Writer(Rosetta), new Writer(Code));
begin
null; -- the "environment task" doesn't need to do anything
end Concurrent_Hello;</lang>
Note that random generator object is local to each task. It cannot be accessed concurrently without mutual exclusion. In order to get different initial states of local generators Reset is called (see ARM A.5.2).
ALGOL 68
<lang algol68>main:(
PROC echo = (STRING string)VOID:
printf(($gl$,string));
PAR(
echo("Enjoy"),
echo("Rosetta"),
echo("Code")
)
)</lang>
APL
Dyalog APL supports the & operator, which runs a function on its own thread.
<lang APL>{⎕←⍵}&¨'Enjoy' 'Rosetta' 'Code'</lang>
- Output:
(Example)
Enjoy Code Rosetta
Astro
<lang python>let words = ["Enjoy", "Rosetta", "Code"]
for word in words:
(word) |> async (w) =>
sleep(random())
print(w)</lang>
BaCon
BaCon is a BASIC-to-C compiler. Assuming GCC compiler in this demonstration. Based on the C OpenMP source.
<lang freebasic>' Concurrent computing using the OpenMP extension in GCC. Requires BaCon 3.6 or higher.
' Specify compiler flag PRAGMA OPTIONS -fopenmp
' Sepcify linker flag PRAGMA LDFLAGS -lgomp
' Declare array with text DECLARE str$[] = { "Enjoy", "Rosetta", "Code" }
' Indicate MP optimization for FOR loop PRAGMA omp parallel for num_threads(3)
' The actual FOR loop FOR i = 0 TO 2
PRINT str$[i]
NEXT </lang>
- Output:
prompt$ bacon concurrent-computing Converting 'concurrent-computing.bac'... done, 11 lines were processed in 0.002 seconds. Compiling 'concurrent-computing.bac'... cc -fopenmp -c concurrent-computing.bac.c cc -o concurrent-computing concurrent-computing.bac.o -lbacon -lm -lgomp Done, program 'concurrent-computing' ready. prompt$ ./concurrent-computing Code Enjoy Rosetta
BBC BASIC
The BBC BASIC interpreter is single-threaded so the only way of achieving 'concurrency' (short of using assembler code) is to use timer events: <lang bbcbasic> INSTALL @lib$+"TIMERLIB"
tID1% = FN_ontimer(100, PROCtask1, 1)
tID2% = FN_ontimer(100, PROCtask2, 1)
tID3% = FN_ontimer(100, PROCtask3, 1)
ON ERROR PRINT REPORT$ : PROCcleanup : END
ON CLOSE PROCcleanup : QUIT
REPEAT
WAIT 0
UNTIL FALSE
END
DEF PROCtask1
PRINT "Enjoy"
ENDPROC
DEF PROCtask2
PRINT "Rosetta"
ENDPROC
DEF PROCtask3
PRINT "Code"
ENDPROC
DEF PROCcleanup
PROC_killtimer(tID1%)
PROC_killtimer(tID2%)
PROC_killtimer(tID3%)
ENDPROC</lang>
C
<lang c>#include <stdio.h>
- include <unistd.h>
- include <pthread.h>
pthread_mutex_t condm = PTHREAD_MUTEX_INITIALIZER; pthread_cond_t cond = PTHREAD_COND_INITIALIZER; int bang = 0;
- define WAITBANG() do { \
pthread_mutex_lock(&condm); \
while( bang == 0 ) \
{ \
pthread_cond_wait(&cond, &condm); \
} \
pthread_mutex_unlock(&condm); } while(0);\
void *t_enjoy(void *p) {
WAITBANG();
printf("Enjoy\n");
pthread_exit(0);
}
void *t_rosetta(void *p) {
WAITBANG();
printf("Rosetta\n");
pthread_exit(0);
}
void *t_code(void *p) {
WAITBANG();
printf("Code\n");
pthread_exit(0);
}
typedef void *(*threadfunc)(void *); int main() {
int i;
pthread_t a[3];
threadfunc p[3] = {t_enjoy, t_rosetta, t_code};
for(i=0;i<3;i++)
{
pthread_create(&a[i], NULL, p[i], NULL);
}
sleep(1);
bang = 1;
pthread_cond_broadcast(&cond);
for(i=0;i<3;i++)
{
pthread_join(a[i], NULL);
}
}</lang>
Note: since threads are created one after another, it is likely that the execution of their code follows the order of creation. To make this less evident, I've added the bang idea using condition: the thread really executes their code once the gun bang is heard. Nonetheless, I still obtain the same order of creation (Enjoy, Rosetta, Code), and maybe it is because of the order locks are acquired. The only way to obtain randomness seems to be to add random wait in each thread (or wait for special cpu load condition)
OpenMP
Compile with gcc -std=c99 -fopenmp:
<lang C>#include <stdio.h>
- include <omp.h>
int main() { const char *str[] = { "Enjoy", "Rosetta", "Code" }; #pragma omp parallel for num_threads(3) for (int i = 0; i < 3; i++) printf("%s\n", str[i]); return 0; }</lang>
C#
With Threads
<lang csharp> static Random tRand = new Random();
static void Main(string[] args) { Thread t = new Thread(new ParameterizedThreadStart(WriteText)); t.Start("Enjoy");
t = new Thread(new ParameterizedThreadStart(WriteText)); t.Start("Rosetta");
t = new Thread(new ParameterizedThreadStart(WriteText)); t.Start("Code");
Console.ReadLine(); }
private static void WriteText(object p) { Thread.Sleep(tRand.Next(1000, 4000)); Console.WriteLine(p); } </lang>
An example result:
Enjoy Code Rosetta
With Tasks
<lang csharp>using System; using System.Threading.Tasks;
public class Program {
static async Task Main() {
Task t1 = Task.Run(() => Console.WriteLine("Enjoy"));
Task t2 = Task.Run(() => Console.WriteLine("Rosetta"));
Task t3 = Task.Run(() => Console.WriteLine("Code"));
await Task.WhenAll(t1, t2, t3); }
}</lang>
With a parallel loop
<lang csharp>using System; using System.Threading.Tasks;
public class Program {
static void Main() => Parallel.ForEach(new[] {"Enjoy", "Rosetta", "Code"}, s => Console.WriteLine(s));
}</lang>
C++
The following example compiles with GCC 4.7.
g++ -std=c++11 -D_GLIBCXX_USE_NANOSLEEP -o concomp concomp.cpp
<lang cpp>#include <thread>
- include <iostream>
- include <vector>
- include <random>
- include <chrono>
int main() {
std::random_device rd; std::mt19937 eng(rd()); // mt19937 generator with a hardware random seed. std::uniform_int_distribution<> dist(1,1000); std::vector<std::thread> threads;
for(const auto& str: {"Enjoy\n", "Rosetta\n", "Code\n"}) {
// between 1 and 1000ms per our distribution
std::chrono::milliseconds duration(dist(eng));
threads.emplace_back([str, duration](){
std::this_thread::sleep_for(duration);
std::cout << str;
});
}
for(auto& t: threads) t.join();
return 0;
}</lang>
Output:
Enjoy Code Rosetta
<lang cpp>#include <iostream>
- include <ppl.h> // MSVC++
void a(void) { std::cout << "Eat\n"; } void b(void) { std::cout << "At\n"; } void c(void) { std::cout << "Joe's\n"; }
int main() {
// function pointers Concurrency::parallel_invoke(&a, &b, &c);
// C++11 lambda functions
Concurrency::parallel_invoke(
[]{ std::cout << "Enjoy\n"; },
[]{ std::cout << "Rosetta\n"; },
[]{ std::cout << "Code\n"; }
);
return 0;
}</lang> Output:
Joe's Eat At Enjoy Code Rosetta
Cind
<lang cind> execute() {
{# host.println("Enjoy");
# host.println("Rosetta");
# host.println("Code"); }
} </lang>
Clojure
A simple way to obtain concurrency is using the future function, which evaluates its body on a separate thread. <lang clojure>(doseq [text ["Enjoy" "Rosetta" "Code"]]
(future (println text)))</lang>
Using the new (2013) core.async library, "go blocks" can execute asynchronously, sharing threads from a pool. This works even in ClojureScript (the JavaScript target of Clojure) on a single thread. The timeout call is there just to shuffle things up: note this delay doesn't block a thread. <lang clojure>(require '[clojure.core.async :refer [go <! timeout]]) (doseq [text ["Enjoy" "Rosetta" "Code"]]
(go (<! (timeout (rand-int 1000))) ; wait a random fraction of a second, (println text)))</lang>
CoffeeScript
Using Bash (or an equivalent shell)
JavaScript, which CoffeeScript compiles to, is single-threaded. This approach launches multiple process to achieve concurrency on Node.js:
<lang coffeescript>{ exec } = require 'child_process'
for word in [ 'Enjoy', 'Rosetta', 'Code' ]
exec "echo #{word}", (err, stdout) ->
console.log stdout</lang>
Using Node.js
As stated above, CoffeeScript is single-threaded. This approach launches multiple Node.js processes to achieve concurrency.
<lang coffeescript># The "master" file.
{ fork } = require 'child_process' path = require 'path' child_name = path.join __dirname, 'child.coffee' words = [ 'Enjoy', 'Rosetta', 'Code' ]
fork child_name, [ word ] for word in words</lang>
<lang coffeescript># child.coffee
console.log process.argv[ 2 ]</lang>
Common Lisp
Concurrency and threads are not part of the Common Lisp standard. However, most implementations provide some interface for concurrency. Bordeaux Threads, used here, provides a compatibility layer for many implementations. (Binding out to *standard-output* before threads are created is needed as each thread gets its own binding for *standard-output*.)
<lang lisp>(defun concurrency-example (&optional (out *standard-output*))
(let ((lock (bordeaux-threads:make-lock)))
(flet ((writer (string)
#'(lambda ()
(bordeaux-threads:acquire-lock lock t)
(write-line string out)
(bordeaux-threads:release-lock lock))))
(bordeaux-threads:make-thread (writer "Enjoy"))
(bordeaux-threads:make-thread (writer "Rosetta"))
(bordeaux-threads:make-thread (writer "Code")))))</lang>
Crystal
Crystal requires the use of channels to ensure that the main fiber doesn't exit before any of the new fibers are done, since each fiber sleeping could return control to the main fiber. <lang ruby>require "channel" require "fiber" require "random"
done = Channel(Nil).new
"Enjoy Rosetta Code".split.map do |x|
spawn do sleep Random.new.rand(0..500).milliseconds puts x done.send nil end
end
3.times do
done.receive
end</lang>
D
<lang d>import std.stdio, std.random, std.parallelism, core.thread, core.time;
void main() {
foreach (s; ["Enjoy", "Rosetta", "Code"].parallel(1)) {
Thread.sleep(uniform(0, 1000).dur!"msecs");
s.writeln;
}
}</lang>
Alternative version
<lang d>import tango.core.Thread; import tango.io.Console; import tango.math.Random;
void main() {
(new Thread( { Thread.sleep(Random.shared.next(1000) / 1000.0); Cout("Enjoy").newline; } )).start;
(new Thread( { Thread.sleep(Random.shared.next(1000) / 1000.0); Cout("Rosetta").newline; } )).start;
(new Thread( { Thread.sleep(Random.shared.next(1000) / 1000.0); Cout("Code").newline; } )).start;
}</lang>
Dart
Future
Using Futures, called Promises in Javascript <lang javascript>import 'dart:math' show Random;
main(){ enjoy() .then( (e) => print(e) ); rosetta() .then( (r) => print(r) ); code() .then( (c) => print(c) ); }
// Create random number generator var rng = Random();
// Each function returns a future that starts after a delay // Like using setTimeout with a Promise in Javascript enjoy() => Future.delayed( Duration( milliseconds: rng.nextInt( 10 ) ), () => "Enjoy"); rosetta() => Future.delayed( Duration( milliseconds: rng.nextInt( 10 ) ), () => "Rosetta"); code() => Future.delayed( Duration( milliseconds: rng.nextInt( 10 ) ), () => "Code");
</lang>
Isolate
Using Isolates, similar to threads but each has its own memory, so they are more like Rust threads than C++ <lang javascript>import 'dart:isolate' show Isolate, ReceivePort; import 'dart:io' show exit, sleep; import 'dart:math' show Random;
main() { // Create ReceivePort to receive done messages // Called a channel in other languages var receiver = ReceivePort();
// Create job counter var job_count = 3;
// Create job pool var jobs = [ enjoy, rosetta, code ];
// Create random number generator var rng = Random();
for ( var job in jobs ) { // Sleep for random duration up to half a second var sleep_time = Duration( milliseconds: rng.nextInt( 500 ) );
// Spawn Isolate to do work // When finished the second argument will be sent to the receiver via the SendPort specified in onExit Isolate.spawn( job, sleep_time, onExit: receiver.sendPort );
}
// Do something in main isolate print("from main isolate\n");
// Register a listener on the ReceivePort, it gets called whenver something is sent on its SendPort // We'll ignore the message with _ because we don't care about the data, just the event receiver.listen( (_) { // Decrement job counter job_count -= 1; // If jobs are all finished if ( job_count == 0 ) { print("\nall jobs finished!"); exit(0); } });
}
enjoy ( duration ) { sleep( duration ) ; print("Enjoy"); }
rosetta ( duration ) { sleep( duration ); print("Rosetta");
}
code ( duration ) { sleep( duration ); print("Code"); }
</lang>
Delphi
<lang Delphi>program ConcurrentComputing;
{$APPTYPE CONSOLE}
uses SysUtils, Classes, Windows;
type
TRandomThread = class(TThread) private FString: string; protected procedure Execute; override; public constructor Create(const aString: string); overload; end;
constructor TRandomThread.Create(const aString: string); begin
inherited Create(False); FreeOnTerminate := True; FString := aString;
end;
procedure TRandomThread.Execute; begin
Sleep(Random(5) * 100); Writeln(FString);
end;
var
lThreadArray: Array[0..2] of THandle;
begin
Randomize;
lThreadArray[0] := TRandomThread.Create('Enjoy').Handle;
lThreadArray[1] := TRandomThread.Create('Rosetta').Handle;
lThreadArray[2] := TRandomThread.Create('Stone').Handle;
WaitForMultipleObjects(Length(lThreadArray), @lThreadArray, True, INFINITE);
end.</lang>
dodo0
<lang dodo0>fun parprint -> text, return (
fork() -> return, throw
println(text, return)
| x
return()
) | parprint
parprint("Enjoy") -> parprint("Rosetta") -> parprint("Code") ->
exit()</lang>
E
<lang e>def base := timer.now() for string in ["Enjoy", "Rosetta", "Code"] {
timer <- whenPast(base + entropy.nextInt(1000), fn { println(string) })
}</lang>
Nondeterminism from preemptive concurrency rather than a random number generator:
<lang e>def seedVat := <import:org.erights.e.elang.interp.seedVatAuthor>(<unsafe>) for string in ["Enjoy", "Rosetta", "Code"] {
seedVat <- (`
fn string {
println(string)
currentVat <- orderlyShutdown("done")
}
`) <- get(0) <- (string)
}</lang>
EchoLisp
<lang scheme> (lib 'tasks) ;; use the tasks library
(define (tprint line ) ;; task definition (writeln _TASK line) #f )
(for-each task-run ;; run three // tasks
(map (curry make-task tprint) '(Enjoy Rosetta code )))
→ #task:id:66:running Rosetta #task:id:67:running code #task:id:65:running Enjoy
</lang>
Egel
<lang Egel> import "prelude.eg" import "io.ego"
using System using IO
def main =
let _ = par (par [_ -> print "enjoy\n"]
[_ -> print "rosetta\n"])
[_ -> print "code\n"] in nop
</lang>
Elixir
<lang Elixir>defmodule Concurrent do
def computing(xs) do
Enum.each(xs, fn x ->
spawn(fn ->
Process.sleep(:rand.uniform(1000))
IO.puts x
end)
end)
Process.sleep(1000)
end
end
Concurrent.computing ["Enjoy", "Rosetta", "Code"]</lang>
- Output:
Rosetta Code Enjoy
Erlang
hw.erl <lang erlang>-module(hw). -export([start/0]).
start() ->
[ spawn(fun() -> say(self(), X) end) || X <- ['Enjoy', 'Rosetta', 'Code'] ], wait(2), ok.
say(Pid,Str) ->
io:fwrite("~s~n",[Str]),
Pid ! done.
wait(N) ->
receive
done -> case N of
0 -> 0;
_N -> wait(N-1)
end
end.</lang>
running it <lang erlang>|erlc hw.erl |erl -run hw start -run init stop -noshell</lang>
Euphoria
<lang euphoria>procedure echo(sequence s)
puts(1,s) puts(1,'\n')
end procedure
atom task1,task2,task3
task1 = task_create(routine_id("echo"),{"Enjoy"}) task_schedule(task1,1)
task2 = task_create(routine_id("echo"),{"Rosetta"}) task_schedule(task2,1)
task3 = task_create(routine_id("echo"),{"Code"}) task_schedule(task3,1)
task_yield()</lang>
Output:
Code Rosetta Enjoy
F#
We define a parallel version of Seq.iter by using asynchronous workflows:
<lang fsharp>module Seq =
let piter f xs =
seq { for x in xs -> async { f x } }
|> Async.Parallel
|> Async.RunSynchronously
|> ignore
let main() = Seq.piter
(System.Console.WriteLine:string->unit)
["Enjoy"; "Rosetta"; "Code";]
main()</lang>
With version 4 of the .NET framework and F# PowerPack 2.0 installed, it is possible to use the predefined PSeq.iter instead.
Factor
<lang factor>USE: concurrency.combinators
{ "Enjoy" "Rosetta" "Code" } [ print ] parallel-each</lang>
Forth
Many Forth implementations come with a simple cooperative task scheduler. Typically each task blocks on I/O or explicit use of the pause word. There is also a class of variables called "user" variables which contain task-specific data, such as the current base and stack pointers.
<lang forth>require tasker.fs require random.fs
- task ( str len -- )
64 NewTask 2 swap pass ( str len -- ) 10 0 do 100 random ms pause 2dup cr type loop 2drop ;
- main
s" Enjoy" task s" Rosetta" task s" Code" task begin pause single-tasking? until ;
main</lang>
Fortran
Fortran doesn't have threads but there are several compilers that support OpenMP, e.g. gfortran and Intel. The following code has been tested with thw Intel 11.1 compiler on WinXP.
<lang Fortran>program concurrency
implicit none character(len=*), parameter :: str1 = 'Enjoy' character(len=*), parameter :: str2 = 'Rosetta' character(len=*), parameter :: str3 = 'Code' integer :: i real :: h real, parameter :: one_third = 1.0e0/3 real, parameter :: two_thirds = 2.0e0/3
interface
integer function omp_get_thread_num
end function omp_get_thread_num
end interface
interface
integer function omp_get_num_threads
end function omp_get_num_threads
end interface
! Use OpenMP to create a team of threads
!$omp parallel do private(i,h)
do i=1,20
! First time through the master thread output the number of threads
! in the team
if (omp_get_thread_num() == 0 .and. i == 1) then
write(*,'(a,i0,a)') 'Using ',omp_get_num_threads(),' threads'
end if
! Randomize the order
call random_number(h)
!$omp critical
if (h < one_third) then
write(*,'(a)') str1
else if (h < two_thirds) then
write(*,'(a)') str2
else
write(*,'(a)') str3
end if
!$omp end critical
end do
!$omp end parallel do
end program concurrency</lang>
FreeBASIC
<lang freebasic>' FB 1.05.0 Win64 ' Compiled with -mt switch (to use threadsafe runtiume) ' The 'ThreadCall' functionality in FB is based internally on LibFFi (see [1] for license)
Sub thread1()
Print "Enjoy"
End Sub
Sub thread2()
Print "Rosetta"
End Sub
Sub thread3()
Print "Code"
End Sub
Print "Press any key to print next batch of 3 strings or ESC to quit" Print
Do
Dim t1 As Any Ptr = ThreadCall thread1 Dim t2 As Any Ptr = ThreadCall thread2 Dim t3 As Any Ptr = ThreadCall thread3 ThreadWait t1 ThreadWait t2 ThreadWait t3 Print Sleep
Loop While Inkey <> Chr(27)</lang>
Sample output
- Output:
Press any key to print next batch of 3 strings or ESC to quit Enjoy Code Rosetta Enjoy Rosetta Code
Go
Channel
Simple and direct solution: Start three goroutines, give each one a word. Each sleeps, then returns the word on a channel. The main goroutine prints words as they return. The print loop represents a checkpoint -- main doesn't exit until all words have been returned and printed.
This solution also shows a good practice for generating random numbers in concurrent goroutines. While certainly not needed for this RC task, in the more general case where you have a number of goroutines concurrently needing random numbers, the goroutines can suffer congestion if they compete heavily for the sole default library source. This can be relieved by having each goroutine create its own non-sharable source. Also particularly in cases where there might be a large number of concurrent goroutines, the source provided in subrepository rand package (exp/rand) can be a better choice than the standard library generator. The subrepo generator requires much less memory for "state" and is much faster to seed.
<lang go>package main
import (
"fmt" "golang.org/x/exp/rand" "time"
)
func main() {
words := []string{"Enjoy", "Rosetta", "Code"}
seed := uint64(time.Now().UnixNano())
q := make(chan string)
for i, w := range words {
go func(w string, seed uint64) {
r := rand.New(rand.NewSource(seed))
time.Sleep(time.Duration(r.Int63n(1e9)))
q <- w
}(w, seed+uint64(i))
}
for i := 0; i < len(words); i++ {
fmt.Println(<-q)
}
}</lang>
Afterfunc
time.Afterfunc combines the sleep and the goroutine start. log.Println serializes output in the case goroutines attempt to print concurrently. sync.WaitGroup is used directly as a checkpoint. <lang go>package main
import (
"log" "math/rand" "os" "sync" "time"
)
func main() {
words := []string{"Enjoy", "Rosetta", "Code"}
rand.Seed(time.Now().UnixNano())
l := log.New(os.Stdout, "", 0)
var q sync.WaitGroup
q.Add(len(words))
for _, w := range words {
w := w
time.AfterFunc(time.Duration(rand.Int63n(1e9)), func() {
l.Println(w)
q.Done()
})
}
q.Wait()
}</lang>
Select
This solution might stretch the intent of the task a bit. It is concurrent but not parallel. Also it doesn't sleep and doesn't call the random number generator explicity. It works because the select statement is specified to make a "pseudo-random fair choice" among multiple channel operations. <lang go>package main
import "fmt"
func main() {
w1 := make(chan bool, 1)
w2 := make(chan bool, 1)
w3 := make(chan bool, 1)
for i := 0; i < 3; i++ {
w1 <- true
w2 <- true
w3 <- true
fmt.Println()
for i := 0; i < 3; i++ {
select {
case <-w1:
fmt.Println("Enjoy")
case <-w2:
fmt.Println("Rosetta")
case <-w3:
fmt.Println("Code")
}
}
}
}</lang> Output:
Code Rosetta Enjoy Enjoy Rosetta Code Rosetta Enjoy Code
Groovy
<lang groovy>'Enjoy Rosetta Code'.tokenize().collect { w ->
Thread.start {
Thread.sleep(1000 * Math.random() as int)
println w
}
}.each { it.join() }</lang>
Haskell
Note how the map treats the list of processes just like any other data.
<lang haskell>import Control.Concurrent
main = mapM_ forkIO [process1, process2, process3] where
process1 = putStrLn "Enjoy" process2 = putStrLn "Rosetta" process3 = putStrLn "Code"</lang>
A more elaborated example using MVars and a random running time per thread.
<lang haskell>import Control.Concurrent import System.Random
concurrent :: IO () concurrent = do
var <- newMVar [] -- use an MVar to collect the results of each thread
mapM_ (forkIO . task var) ["Enjoy", "Rosetta", "Code"] -- run 3 threads
putStrLn "Press Return to show the results." -- while we wait for the user,
-- the threads run
_ <- getLine
takeMVar var >>= mapM_ putStrLn -- read the results and show them on screen
where
-- "task" is a thread
task v s = do
randomRIO (1,10) >>= \r -> threadDelay (r * 100000) -- wait a while
val <- takeMVar v -- read the MVar and block other threads from reading it
-- until we write another value to it
putMVar v (s : val) -- append a text string to the MVar and block other
-- threads from writing to it unless it is read first</lang>
Icon and Unicon
The following code uses features exclusive to Unicon <lang unicon>procedure main()
L:=[ thread write("Enjoy"), thread write("Rosetta"), thread write("Code") ]
every wait(!L)
end</lang>
J
Example:
<lang j> smoutput&>({~?~@#);:'Enjoy Rosetta Code' Rosetta Code Enjoy </lang>
NOTES AND CAUTIONS:
1) While J's syntax and semantics is highly parallel, it is a deterministic sort of parallelism (analogous to the design of modern GPUs) and not the stochastic parallelism which is implied in this task specification (and which is usually obtained by timeslicing threads of control). The randomness implemented here is orthogonal to the parallelism in the display (and you could remove smoutput& without altering the appearence, in this trivial example).
2) The current release of J (and the past implementations) do not implement hardware based concurrency. This is partially an economic issue (since all of the current and past language implementations have been distributed for free, with terms which allow free distribution), and partially a hardware maturity issue (historically, most CPU multi-core development has been optimized for stochastic parallelism with minimal cheap support for large scale deterministic parallelism and GPUs have not been capable of supporting the kind of generality needed by J).
This state of affairs is likely to change, eventually (most likely this will be after greater than factor of 2 speedups from hardware parallelism are available for the J users in cases which are common and important enough to support the implementation). But, for now, J's parallelism is entirely conceptual.
Java
Uses CyclicBarrier to force all threads to wait until they're at the same point before executing the println, increasing the odds they'll print in a different order (otherwise, while the they may be executing in parallel, the threads are started sequentially and with such a short run-time, will usually output sequentially as well).
<lang java5>import java.util.concurrent.CyclicBarrier;
public class Threads {
public static class DelayedMessagePrinter implements Runnable
{
private CyclicBarrier barrier;
private String msg;
public DelayedMessagePrinter(CyclicBarrier barrier, String msg)
{
this.barrier = barrier;
this.msg = msg;
}
public void run()
{
try
{ barrier.await(); }
catch (Exception e)
{ }
System.out.println(msg);
}
}
public static void main(String[] args)
{
CyclicBarrier barrier = new CyclicBarrier(3);
new Thread(new DelayedMessagePrinter(barrier, "Enjoy")).start();
new Thread(new DelayedMessagePrinter(barrier, "Rosetta")).start();
new Thread(new DelayedMessagePrinter(barrier, "Code")).start();
}
}</lang>
JavaScript
JavaScript now enjoys access to a concurrency library thanks to Web Workers. The Web Workers specification defines an API for spawning background scripts. This first code is the background script and should be in the concurrent_worker.js file. <lang javascript>self.addEventListener('message', function (event) {
self.postMessage(event.data); self.close();
}, false);</lang> This second block creates the workers, sends them a message and creates an event listener to handle the response. <lang javascript>var words = ["Enjoy", "Rosetta", "Code"]; var workers = [];
for (var i = 0; i < words.length; i++) {
workers[i] = new Worker("concurrent_worker.js");
workers[i].addEventListener('message', function (event) {
console.log(event.data);
}, false);
workers[i].postMessage(words[i]);
}</lang>
Julia
<lang julia>words = ["Enjoy", "Rosetta", "Code"]
function sleepprint(s)
sleep(rand()) println(s)
end
@sync for word in words
@async sleepprint(word)
end</lang>
Kotlin
<lang scala>// version 1.1.2
import java.util.concurrent.CyclicBarrier
class DelayedMessagePrinter(val barrier: CyclicBarrier, val msg: String) : Runnable {
override fun run() {
barrier.await()
println(msg)
}
}
fun main(args: Array<String>) {
val msgs = listOf("Enjoy", "Rosetta", "Code")
val barrier = CyclicBarrier(msgs.size)
for (msg in msgs) Thread(DelayedMessagePrinter(barrier, msg)).start()
}</lang>
- Output:
Sample output:
Code Rosetta Enjoy
LFE
<lang lisp>
- This is a straight port of the Erlang version.
- You can run this under the LFE REPL as follows
- (slurp "concurrent-computing.lfe")
- (start)
(defmodule concurrent-computing
(export (start 0)))
(defun start ()
(lc ((<- word '("Enjoy" "Rosetta" "Code")))
(spawn (lambda () (say (self) word))))
(wait 2)
'ok)
(defun say (pid word)
(lfe_io:format "~p~n" (list word)) (! pid 'done))
(defun wait (n)
(receive
('done (case n
(0 0)
(_n (wait (- n 1)))))))
</lang>
Logtalk
Works when using SWI-Prolog, XSB, or YAP as the backend compiler. <lang logtalk>:- object(concurrency).
:- initialization(output).
output :-
threaded((
write('Enjoy'),
write('Rosetta'),
write('Code')
)).
- - end_object.</lang>
Lua
<lang lua>co = {} co[1] = coroutine.create( function() print "Enjoy" end ) co[2] = coroutine.create( function() print "Rosetta" end ) co[3] = coroutine.create( function() print "Code" end )
math.randomseed( os.time() ) h = {} i = 0 repeat
j = math.random(3)
if h[j] == nil then
coroutine.resume( co[j] )
h[j] = true
i = i + 1
end
until i == 3</lang>
M2000 Interpreter
Each thread executed in same scope where created. We can use static variables, which are at thread level, so in this example we have three A$,one for each thread. Each thread can use Thread This to send command, or using a known handler (number which return to k) to execute commands to other threads. Commands are HOLD,RESTART, ERASE, INTERVAL, EXECUTE.
Each thread has own stack of values, which deleted when erased. We can Push values to top of stack, or use Data to push to end of stack. A Read statement read from top of stack. In the example we Flush module's stack (modules use parent stack, functions get own stack), we place with Data strings and we read it using Read M$. We place the M$ to Static A$ (this can be done one time, because if A$ as static exist then interpreter skip expression without execute it).
All threads of a module erased when a module exit. Any block of code inside { } in Thread run without concurrency, when we use Thread.Plan Concurrent (when a thread runs we can't change Plan). Other plan is the sequential. Interval can be set to milliseconds.
Threads actually runs in Wait loop. We can use Main.Task as a loop which is thread also. Threads can be run when we wait for input in m2000 console, or for events from M2000 GUI forms, also. Events always run in sequential form.
<lang M2000 Interpreter> Thread.Plan Concurrent Module CheckIt {
Flush \\ empty stack of values
Data "Enjoy", "Rosetta", "Code"
For i=1 to 3 {
Thread {
Print A$
Thread This Erase
} As K
Read M$
Thread K Execute Static A$=M$
Thread K Interval Random(500,1000)
Threads
}
Rem : Wait 3000 ' we can use just a wait loop, or the main.task loop
\\ main.task exit if all threads erased
Main.Task 30 {
}
\\ when module exit all threads from this module get a signal to stop. \\ we can use Threads Erase to erase all threads. \\ Also if we press Esc we do the same } CheckIt
\\ we can define again the module, and now we get three time each name, but not every time three same names. \\ if we change to Threads.Plan Sequential we get always the three same names \\ Also in concurrent plan we can use a block to ensure that statements run without other thread executed in parallel.
Module CheckIt {
Flush \\ empty stack of values
Data "Enjoy", "Rosetta", "Code"
For i=1 to 3 {
Thread {
Print A$
Print A$
Print A$
Thread This Erase
} As K
Read M$
Thread K Execute Static A$=M$
Thread K Interval Random(500,530)
Threads
}
Rem : Wait 3000 ' we can use just a wait loop, or the main.task loop
\\ main.task exit if all threads erased
Main.Task 30 {
}
\\ when module exit all threads from this module get a signal to stop. \\ we can use Threads Erase to erase all threads. \\ Also if we press Esc we do the same } CheckIt
</lang>
Mathematica / Wolfram Language
Parallelization requires Mathematica 7 or later <lang Mathematica>ParallelDo[
Pause[RandomReal[]];
Print[s],
{s, {"Enjoy", "Rosetta", "Code"}}
]</lang>
Mercury
<lang>:- module concurrent_computing.
- - interface.
- - import_module io.
- - pred main(io::di, io::uo) is cc_multi.
- - implementation.
- - import_module thread.
main(!IO) :-
spawn(io.print_cc("Enjoy\n"), !IO),
spawn(io.print_cc("Rosetta\n"), !IO),
spawn(io.print_cc("Code\n"), !IO).</lang>
Neko
<lang ActionScript>/**
Concurrent computing, in Neko
- /
var thread_create = $loader.loadprim("std@thread_create", 2);
var subtask = function(message) {
$print(message, "\n");
}
/* The thread functions happen so fast as to look sequential */ thread_create(subtask, "Enjoy"); thread_create(subtask, "Rosetta"); thread_create(subtask, "Code");
/* slow things down */ var sys_sleep = $loader.loadprim("std@sys_sleep", 1); var random_new = $loader.loadprim("std@random_new", 0); var random_int = $loader.loadprim("std@random_int", 2);
var randomsleep = function(message) {
var r = random_new(); var sleep = random_int(r, 3); sys_sleep(sleep); $print(message, "\n");
}
$print("\nWith random delays\n"); thread_create(randomsleep, "Enjoy"); thread_create(randomsleep, "Rosetta"); thread_create(randomsleep, "Code");
/* Let the threads complete */ sys_sleep(4);</lang>
- Output:
prompt$ nekoc threading.neko prompt$ neko threading Enjoy Rosetta Code With random delays Rosetta Enjoy Code
Nim
Compile with nim --threads:on c concurrent:
<lang nim>const str = ["Enjoy", "Rosetta", "Code"]
var thr: array[3, Thread[int32]]
proc f(i:int32) {.thread.} =
echo str[i]
for i in 0..thr.high:
createThread(thr[i], f, int32(i))
joinThreads(thr)</lang>
OpenMP
Compile with nim --passC:"-fopenmp" --passL:"-fopenmp" c concurrent:
<lang nim>const str = ["Enjoy", "Rosetta", "Code"]
for i in 0||2:
echo str[i]</lang>
Thread Pools
Compile with nim --threads:on c concurrent:
<lang nim>import threadpool
const str = ["Enjoy", "Rosetta", "Code"]
proc f(i: int) {.thread.} =
echo str[i]
for i in 0..str.high:
spawn f(i)
sync()</lang>
Objeck
<lang objeck> bundle Default {
class MyThread from Thread {
New(name : String) {
Parent(name);
}
method : public : Run(param : Base) ~ Nil {
string := param->As(String);
string->PrintLine();
}
}
class Concurrent {
New() {
}
function : Main(args : System.String[]) ~ Nil {
t0 := MyThread->New("t0");
t1 := MyThread->New("t1");
t2 := MyThread->New("t2");
t0->Execute("Enjoy"->As(Base));
t1->Execute("Rosetta"->As(Base));
t2->Execute("Code"->As(Base));
}
}
} </lang>
OCaml
<lang ocaml>#directory "+threads"
- load "unix.cma"
- load "threads.cma"
let sleepy_print msg =
Unix.sleep (Random.int 4); print_endline msg
let threads =
List.map (Thread.create sleepy_print) ["Enjoy"; "Rosetta"; "Code"]
let () =
Random.self_init (); List.iter (Thread.join) threads</lang>
Oforth
Oforth uses tasks to implement concurrent computing. A task is scheduled using #& on a function, method, block, ...
<lang Oforth>#[ "Enjoy" println ] &
- [ "Rosetta" println ] &
- [ "Code" println ] &</lang>
mapParallel method can be used to map a runnable on each element of a collection and returns a collection of results. Here, we println the string and return string size.
<lang Oforth>[ "Enjoy", "Rosetta", "Code" ] mapParallel(#[ dup . size ])</lang>
ooRexx
<lang ooRexx> -- this will launch 3 threads, with each thread given a message to print out. -- I've added a stoplight to make each thread wait until given a go signal, -- plus some sleeps to give the threads a chance to randomize the execution -- order a little. launcher = .launcher~new launcher~launch
- class launcher
-- the launcher method. Guarded is the default, but let's make this -- explicit here
- method launch guarded
runner1 = .runner~new(self, "Enjoy") runner2 = .runner~new(self, "Rosetta") runner3 = .runner~new(self, "Code")
-- let's give the threads a chance to settle in to the -- starting line call syssleep 1
guard off -- release the launcher lock. This is the starter's gun
-- this is a guarded method that the runners will call. They -- will block until the launch method releases the object guard
- method block guarded
- class runner
- method init
use arg launcher, text reply -- this creates the new thread
call syssleep .5 -- try to mix things up by sleeping launcher~block -- wait for the go signal call syssleep .5 -- add another sleep here say text
</lang>
Oz
The randomness comes from the unpredictability of thread scheduling (this is how I understand this exercise).
<lang oz>for Msg in ["Enjoy" "Rosetta" "Code"] do
thread
{System.showInfo Msg}
end
end </lang>
PARI/GP
Here is a GP implementation using the bill-mt branch: <lang parigp>inline(func); func(n)=print(["Enjoy","Rosetta","Code"][n]); parapply(func,[1..3]);</lang>
This is a PARI implementation which uses fork() internally. Note that the C solutions can be used instead if desired; this program demonstrates the native PARI capabilities instead.
For serious concurrency, see Appendix B of the User's Guide to the PARI Library which discusses a solution using tls on pthreads. (There are nontrivial issues with using PARI in this environment, do not attempt to blindly implement a C solution.) <lang C>void foo() {
if (pari_daemon()) {
// Original
if (pari_daemon()) {
// Original
pari_printf("Enjoy\n");
} else {
// Daemon #2
pari_printf("Code\n");
}
} else {
// Daemon #1
pari_printf("Rosetta\n");
}
}</lang>
See also Bill Allombert's slides on parallel programming in GP.
Pascal
modified for linux. Using simple running thread-counter to circumvent WaitForMultipleObjects.
Output of difference of sleep time and true sleep time ( running with 0..1999 threads you see once a while 1)
<lang pascal>program ConcurrentComputing; {$IFdef FPC}
{$MODE DELPHI}
{$ELSE}
{$APPTYPE CONSOLE}
{$ENDIF} uses
{$IFDEF UNIX}
cthreads,
{$ENDIF}
SysUtils, Classes;
type
TRandomThread = class(TThread) private FString: string; T0 : Uint64; protected procedure Execute; override; public constructor Create(const aString: string); overload; end;
const
MyStrings: array[0..2] of String = ('Enjoy ','Rosetta ','Code ');
var
gblRunThdCnt : LongWord = 0;
constructor TRandomThread.Create(const aString: string); begin
inherited Create(False); FreeOnTerminate := True; FString := aString; interlockedincrement(gblRunThdCnt);
end;
procedure TRandomThread.Execute; var
i : NativeInt;
begin
i := Random(300); T0 := GettickCount64; Sleep(i); //output of difference in time Writeln(FString,i:4,GettickCount64-T0 -i:2); interlockeddecrement(gblRunThdCnt);
end;
var
lThreadArray: Array[0..9] of THandle; i : NativeInt;
begin
Randomize;
gblRunThdCnt := 0;
For i := low(lThreadArray) to High(lThreadArray) do
lThreadArray[i] := TRandomThread.Create(Format('%9s %4d',[myStrings[Random(3)],i])).Handle;
while gblRunThdCnt > 0 do sleep(125);
end.</lang>
- Output:
Enjoy 4 16 0
Code 0 22 0
Code 1 32 0
Rosetta 7 117 0
Enjoy 2 137 0
Code 6 214 0
Code 5 252 0
Enjoy 3 299 0
Perl
<lang perl>use threads; use Time::HiRes qw(sleep);
$_->join for map {
threads->create(sub {
sleep rand;
print shift, "\n";
}, $_)
} qw(Enjoy Rosetta Code);</lang>
Or using coroutines provided by
<lang perl>use fe
Perl
<lang perl>use threads; use Time::HiRes qw(sleep);
$_->join for map {
threads->create(sub {
sleep rand;
print shift, "\n";
}, $_)
} qw(Enjoy Rosetta Code);</lang>
Or using coroutines provided by
<lang perl>use feature qw( say ); use Coro; use Coro::Timer qw( sleep );
$_->join for map {
async {
ature qw( say );
use Coro; use Coro::Timer qw( sleep );
$_->join for map {
async {
sleep rand;
say @_;
} $_
} qw( Enjoy Rosetta Code ); </lang>
Phix
Without the sleep it is almost always Enjoy Rosetta Code, because create_thread() is more costly than echo(), as the former has to create a new call stack etc.
The lock prevents the displays from mangling each other.
<lang Phix>procedure echo(string s)
sleep(rand(100)/100) enter_cs() puts(1,s) puts(1,'\n') leave_cs()
end procedure
constant threads = {create_thread(routine_id("echo"),{"Enjoy"}),
create_thread(routine_id("echo"),{"Rosetta"}),
create_thread(routine_id("echo"),{"Code"})}
wait_thread(threads) puts(1,"done") {} = wait_key()</lang>
PicoLisp
Using background tasks
<lang PicoLisp>(for (N . Str) '("Enjoy" "Rosetta" "Code")
(task (- N) (rand 1000 4000) # Random start time 1 .. 4 sec
Str Str # Closure with string value
(println Str) # Task body: Print the string
(task @) ) ) # and stop the task</lang>
Using child processes
<lang PicoLisp>(for Str '("Enjoy" "Rosetta" "Code")
(let N (rand 1000 4000) # Randomize
(unless (fork) # Create child process
(wait N) # Wait 1 .. 4 sec
(println Str) # Print string
(bye) ) ) ) # Terminate child process</lang>
Pike
Using POSIX threads: <lang Pike>int main() { // Start threads and wait for them to finish ({ Thread.Thread(write, "Enjoy\n"), Thread.Thread(write, "Rosetta\n"), Thread.Thread(write, "Code\n") })->wait();
// Exit program exit(0); }</lang> Output:
Enjoy Rosetta Code
Using Pike's backend: <lang Pike>int main(int argc, array argv) {
call_out(write, random(1.0), "Enjoy\n"); call_out(write, random(1.0), "Rosetta\n"); call_out(write, random(1.0), "Code\n"); call_out(exit, 1, 0); return -1; // return -1 starts the backend which makes Pike run until exit() is called.
}</lang> Output:
Rosetta Code Enjoy
PowerShell
Using Background Jobs: <lang Powershell>$Strings = "Enjoy","Rosetta","Code"
$SB = {param($String)Write-Output $String}
foreach($String in $Strings) {
Start-Job -ScriptBlock $SB -ArgumentList $String | Out-Null }
Get-Job | Wait-Job | Receive-Job Get-Job | Remove-Job</lang>
Using .NET Runspaces: <lang Powershell>$Strings = "Enjoy","Rosetta","Code"
$SB = {param($String)Write-Output $String}
$Pool = [RunspaceFactory]::CreateRunspacePool(1, 3) $Pool.ApartmentState = "STA" $Pool.Open() foreach ($String in $Strings) {
$Pipeline = [System.Management.Automation.PowerShell]::create() $Pipeline.RunspacePool = $Pool [void]$Pipeline.AddScript($SB).AddArgument($String) $AsyncHandle = $Pipeline.BeginInvoke() $Pipeline.EndInvoke($AsyncHandle) $Pipeline.Dispose() }
$Pool.Close()</lang>
Prolog
This example works in SWI-Prolog. It may work in other Prolog implementations too.
Create a separate thread for each word. Join the threads to make sure they complete before the program exits.
<lang prolog>main :-
thread_create(say("Enjoy"),A,[]),
thread_create(say("Rosetta"),B,[]),
thread_create(say("Code"),C,[]),
thread_join(A,_),
thread_join(B,_),
thread_join(C,_).
say(Message) :-
Delay is random_float, sleep(Delay), writeln(Message).</lang>
PureBasic
<lang PureBasic>Global mutex = CreateMutex()
Procedure Printer(*str) LockMutex(mutex) PrintN( PeekS(*str) ) UnlockMutex(mutex) EndProcedure
If OpenConsole() LockMutex(mutex) thread1 = CreateThread(@Printer(), @"Enjoy") thread2 = CreateThread(@Printer(), @"Rosetta") thread3 = CreateThread(@Printer(), @"Code") UnlockMutex(mutex)
WaitThread(thread1) WaitThread(thread2) WaitThread(thread3)
Print(#CRLF$ + #CRLF$ + "Press ENTER to exit") Input()
CloseConsole() EndIf
FreeMutex(mutex)</lang>
Python
Using asyncio module (I know almost nothing about it, so feel free to improve it :-)): <lang python>import asyncio
async def print_(string: str) -> None:
print(string)
async def main():
strings = ['Enjoy', 'Rosetta', 'Code'] coroutines = map(print_, strings) await asyncio.gather(*coroutines)
if __name__ == '__main__':
asyncio.run(main())</lang>
Using the new to Python 3.2 concurrent.futures library and choosing to use processes over threads; the example will use up to as many processes as your machine has cores. This doesn't however guarantee an order of sub-process results. <lang python>Python 3.2 (r32:88445, Feb 20 2011, 21:30:00) [MSC v.1500 64 bit (AMD64)] on win 32 Type "help", "copyright", "credits" or "license" for more information. >>> from concurrent import futures >>> with futures.ProcessPoolExecutor() as executor: ... _ = list(executor.map(print, 'Enjoy Rosetta Code'.split())) ... Enjoy Rosetta Code >>></lang>
<lang python>import threading import random
def echo(text):
print(text)
threading.Timer(random.random(), echo, ("Enjoy",)).start() threading.Timer(random.random(), echo, ("Rosetta",)).start() threading.Timer(random.random(), echo, ("Code",)).start()</lang>
Or, by using a for loop to start one thread per list entry, where our list is our set of source strings:
<lang python>import threading import random
def echo(text):
print(text)
for text in ["Enjoy", "Rosetta", "Code"]:
threading.Timer(random.random(), echo, (text,)).start()</lang>
threading.Thread
<lang python>import random, sys, time import threading
lock = threading.Lock()
def echo(s):
time.sleep(1e-2*random.random())
# use `.write()` with lock due to `print` prints empty lines occasionally
with lock:
sys.stdout.write(s)
sys.stdout.write('\n')
for line in 'Enjoy Rosetta Code'.split():
threading.Thread(target=echo, args=(line,)).start()</lang>
multiprocessing
<lang python>from __future__ import print_function from multiprocessing import Pool
def main():
p = Pool() p.map(print, 'Enjoy Rosetta Code'.split())
if __name__=="__main__":
main()</lang>
twisted
<lang python>import random from twisted.internet import reactor, task, defer from twisted.python.util import println
delay = lambda: 1e-4*random.random() d = defer.DeferredList([task.deferLater(reactor, delay(), println, line)
for line in 'Enjoy Rosetta Code'.split()])
d.addBoth(lambda _: reactor.stop()) reactor.run()</lang>
gevent
<lang python>from __future__ import print_function import random import gevent
delay = lambda: 1e-4*random.random() gevent.joinall([gevent.spawn_later(delay(), print, line)
for line in 'Enjoy Rosetta Code'.split()])</lang>
Racket
Threads provide a simple API for concurrent programming. <lang racket>
- lang racket
(for ([str '("Enjoy" "Rosetta" "Code")])
(thread (λ () (displayln str))))
</lang>
In addition to "thread" which is implemented as green threads (useful for IO etc), Racket has "futures" and "places" which are similar tools for using multiple OS cores.
Raku
(formerly Perl 6)
<lang perl6>my @words = <Enjoy Rosetta Code>; @words.race(:batch(1)).map: { sleep rand; say $_ };</lang>
- Output:
Code Rosetta Enjoy
Raven
<lang raven>[ 'Enjoy' 'Rosetta' 'Code' ] as $words
thread talker
$words pop "%s\n"
repeat dup print
500 choose ms
talker as a talker as b talker as c</lang>
Rhope
<lang rhope>Main(0,0) |:
Print["Enjoy"] Print["Rosetta"] Print["Code"]
- |</lang>
In Rhope, expressions with no shared dependencies run in parallel by default.
Ruby
<lang ruby>%w{Enjoy Rosetta Code}.map do |x|
Thread.new do
sleep rand
puts x
end
end.each do |t|
t.join
end</lang>
Rust
<lang rust>extern crate rand; use std::thread; use rand::thread_rng; use rand::distributions::{Range, IndependentSample};
fn main() {
let mut rng = thread_rng();
let rng_range = Range::new(0u32, 100);
for word in "Enjoy Rosetta Code".split_whitespace() {
let snooze_time = rng_range.ind_sample(&mut rng);
let local_word = word.to_owned();
std::thread::spawn(move || {
thread::sleep_ms(snooze_time);
println!("{}", local_word);
});
}
thread::sleep_ms(1000);
}</lang>
Scala
<lang scala>import scala.actors.Futures List("Enjoy", "Rosetta", "Code").map { x =>
Futures.future {
Thread.sleep((Math.random * 1000).toInt)
println(x)
}
}.foreach(_())</lang>
Scheme
<lang scheme>(parallel-execute (lambda () (print "Enjoy"))
(lambda () (print "Rosetta"))
(lambda () (print "Code")))</lang>
If your implementation doesn't provide parallel-execute, it can be implemented with SRFI-18. <lang scheme>(import (srfi 18)) (define (parallel-execute . thunks)
(let ((threads (map make-thread thunks))) (for-each thread-start! threads) (for-each thread-join! threads)))</lang>
Sidef
A very basic threading support is provided by the Block.fork() method: <lang ruby>var a = <Enjoy Rosetta Code>
a.map{|str|
{ Sys.sleep(1.rand)
say str
}.fork
}.map{|thr| thr.wait }</lang>
- Output:
Enjoy Code Rosetta
Swift
Using Grand Central Dispatch with concurrent queues. <lang Swift>import Foundation
let myList = ["Enjoy", "Rosetta", "Code"]
for word in myList {
dispatch_async(dispatch_get_global_queue(0, 0)) {
NSLog(word)
}
}
dispatch_main()</lang>
- Output:
2015-02-05 10:15:01.831 rosettaconcurrency[1917:37905] Code 2015-02-05 10:15:01.831 rosettaconcurrency[1917:37902] Enjoy 2015-02-05 10:15:01.831 rosettaconcurrency[1917:37904] Rosetta
Standard ML
Works with PolyML <lang Standard ML>structure TTd = Thread.Thread ; structure TTm = Thread.Mutex ;
val threadedStringList = fn tasks:string list =>
let
val mx = TTm.mutex () ;
val taskstore = ref tasks ;
fun makeFastRand () = Real.rem (Time.toReal (Time.now ()),1.0)
val doTask = fn () =>
let
val mytask : string ref = ref "" ;
in
( TTm.lock mx ; mytask := hd ( !taskstore ) ; taskstore:= tl (!taskstore) ; TTm.unlock mx ;
Posix.Process.sleep (Time.fromReal (makeFastRand ())) ;
TTm.lock mx ; print ( !mytask ^ "\n") ; TTm.unlock mx ;
TTd.exit ()
)
end
in
List.tabulate ( length tasks , fn i => TTd.fork (doTask , []) )
end ; </lang> call
threadedStringList [ "Enjoy","Rosetta","Code" ]; Rosetta Code Enjoy
Tcl
Assuming that "random" means that we really want the words to appear in random (rather then "undefined" or "arbitrary") order:
<lang tcl>after [expr int(1000*rand())] {puts "Enjoy"} after [expr int(1000*rand())] {puts "Rosetta"} after [expr int(1000*rand())] {puts "Code"}</lang>
will execute each line after a randomly chosen number (0...1000) of milliseconds.
A step towards "undefined" would be to use after idle, which is Tcl for "do this whenever you get around to it". Thus:
<lang tcl>after idle {puts "Enjoy"} after idle {puts "Rosetta"} after idle {puts "Code"}</lang>
(While no particular order is guaranteed by the Tcl spec, the current implementations will all execute these in the order in which they were added to the idle queue).
It's also possible to use threads for this. Here we do this with the built-in thread-pool support: <lang tcl>package require Thread set pool [tpool::create -initcmd {
proc delayPrint msg {
after [expr int(1000*rand())]
puts $msg
}
}] tpool::post -detached $pool [list delayPrint "Enjoy"] tpool::post -detached $pool [list delayPrint "Rosetta"] tpool::post -detached $pool [list delayPrint "Code"] tpool::release $pool after 1200 ;# Give threads time to do their work exit</lang>
UnixPipes
<lang bash>(echo "Enjoy" & echo "Rosetta"& echo "Code"&)</lang>
VBA
Three tasks scheduled for the same time with OnTime. The last scheduled task gets executed first. <lang vb>Private Sub Enjoy()
Debug.Print "Enjoy"
End Sub Private Sub Rosetta()
Debug.Print "Rosetta"
End Sub Private Sub Code()
Debug.Print "Code"
End Sub Public Sub concurrent()
when = Now + TimeValue("00:00:01")
Application.OnTime when, "Enjoy"
Application.OnTime when, "Rosetta"
Application.OnTime when, "Code"
End Sub</lang>
Visual Basic .NET
<lang vbnet>Imports System.Threading
Module Module1
Public rnd As New Random
Sub Main()
Dim t1 As New Thread(AddressOf Foo)
Dim t2 As New Thread(AddressOf Foo)
Dim t3 As New Thread(AddressOf Foo)
t1.Start("Enjoy")
t2.Start("Rosetta")
t3.Start("Code")
t1.Join()
t2.Join()
t3.Join()
End Sub
Sub Foo(ByVal state As Object)
Thread.Sleep(rnd.Next(1000))
Console.WriteLine(state)
End Sub
End Module</lang>
Alternative version
Try It Online! <lang vbnet>Imports System.Threading Module Module1
Dim rnd As New Random()
Sub Main()
Parallel.ForEach("Enjoy Rosetta Code".Split(" "), Sub(s)
Thread.Sleep(rnd.Next(25)) : Console.WriteLine(s)
End Sub)
End Sub
End Module</lang>
- Output:
Rosetta Enjoy Code
Wren
<lang ecmascript>import "random" for Random
var words = ["Enjoy", "Rosetta", "Code"] var rand = Random.new() for (h in 1..3) {
var fibers = List.filled(3, null)
for (i in 0..2) fibers[i] = Fiber.new { System.print(words[i]) }
var called = List.filled(3, false)
var j = 0
while (j < 3) {
var k = rand.int(3)
if (!called[k]) {
fibers[k].call()
called[k] = true
j = j + 1
}
}
System.print()
}</lang>
- Output:
Sample run:
Enjoy Code Rosetta Code Enjoy Rosetta Rosetta Enjoy Code
zkl
<lang zkl>fcn{println("Enjoy")}.launch(); // thread fcn{println("Rosetta")}.strand(); // co-op thread fcn{println("Code")}.future(); // another thread type</lang>
- Output:
Rosetta Code Enjoy
- Programming Tasks
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