MirBSD manpage: perlthrtut(1)

PERLTHRTUT(1)   Perl Programmers Reference Guide    PERLTHRTUT(1)


     perlthrtut - tutorial on threads in Perl


     NOTE: this tutorial describes the new Perl threading flavour
     introduced in Perl 5.6.0 called interpreter threads, or
     ithreads for short.  In this model each thread runs in its
     own Perl interpreter, and any data sharing between threads
     must be explicit.

     There is another older Perl threading flavour called the
     5.005 model, unsurprisingly for 5.005 versions of Perl.  The
     old model is known to have problems, deprecated, and will
     probably be removed around release 5.10. You are strongly
     encouraged to migrate any existing 5.005 threads code to the
     new model as soon as possible.

     You can see which (or neither) threading flavour you have by
     running "perl -V" and looking at the "Platform" section. If
     you have "useithreads=define" you have ithreads, if you have
     "use5005threads=define" you have 5.005 threads. If you have
     neither, you don't have any thread support built in. If you
     have both, you are in trouble.

     The user-level interface to the 5.005 threads was via the
     Threads class, while ithreads uses the threads class. Note
     the change in case.


     The ithreads code has been available since Perl 5.6.0, and
     is considered stable. The user-level interface to ithreads
     (the threads classes) appeared in the 5.8.0 release, and as
     of this time is considered stable although it should be
     treated with caution as with all new features.

What Is A Thread Anyway?
     A thread is a flow of control through a program with a sin-
     gle execution point.

     Sounds an awful lot like a process, doesn't it? Well, it
     should. Threads are one of the pieces of a process.  Every
     process has at least one thread and, up until now, every
     process running Perl had only one thread.  With 5.8, though,
     you can create extra threads.  We're going to show you how,
     when, and why.

Threaded Program Models

     There are three basic ways that you can structure a threaded
     program.  Which model you choose depends on what you need
     your program to do.  For many non-trivial threaded programs
     you'll need to choose different models for different pieces
     of your program.

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     The boss/worker model usually has one "boss" thread and one
     or more "worker" threads.  The boss thread gathers or gen-
     erates tasks that need to be done, then parcels those tasks
     out to the appropriate worker thread.

     This model is common in GUI and server programs, where a
     main thread waits for some event and then passes that event
     to the appropriate worker threads for processing.  Once the
     event has been passed on, the boss thread goes back to wait-
     ing for another event.

     The boss thread does relatively little work.  While tasks
     aren't necessarily performed faster than with any other
     method, it tends to have the best user-response times.

     Work Crew

     In the work crew model, several threads are created that do
     essentially the same thing to different pieces of data.  It
     closely mirrors classical parallel processing and vector
     processors, where a large array of processors do the exact
     same thing to many pieces of data.

     This model is particularly useful if the system running the
     program will distribute multiple threads across different
     processors.  It can also be useful in ray tracing or render-
     ing engines, where the individual threads can pass on
     interim results to give the user visual feedback.


     The pipeline model divides up a task into a series of steps,
     and passes the results of one step on to the thread process-
     ing the next.  Each thread does one thing to each piece of
     data and passes the results to the next thread in line.

     This model makes the most sense if you have multiple proces-
     sors so two or more threads will be executing in parallel,
     though it can often make sense in other contexts as well.
     It tends to keep the individual tasks small and simple, as
     well as allowing some parts of the pipeline to block (on I/O
     or system calls, for example) while other parts keep going.
     If you're running different parts of the pipeline on dif-
     ferent processors you may also take advantage of the caches
     on each processor.

     This model is also handy for a form of recursive programming
     where, rather than having a subroutine call itself, it
     instead creates another thread.  Prime and Fibonacci genera-
     tors both map well to this form of the pipeline model. (A

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     version of a prime number generator is presented later on.)

What kind of threads are Perl threads?
     If you have experience with other thread implementations,
     you might find that things aren't quite what you expect.
     It's very important to remember when dealing with Perl
     threads that Perl Threads Are Not X Threads, for all values
     of X.  They aren't POSIX threads, or DecThreads, or Java's
     Green threads, or Win32 threads.  There are similarities,
     and the broad concepts are the same, but if you start look-
     ing for implementation details you're going to be either
     disappointed or confused.  Possibly both.

     This is not to say that Perl threads are completely dif-
     ferent from everything that's ever come before--they're not.
     Perl's threading model owes a lot to other thread models,
     especially POSIX.  Just as Perl is not C, though, Perl
     threads are not POSIX threads.  So if you find yourself
     looking for mutexes, or thread priorities, it's time to step
     back a bit and think about what you want to do and how Perl
     can do it.

     However it is important to remember that Perl threads cannot
     magically do things unless your operating systems threads
     allows it. So if your system blocks the entire process on
     sleep(), Perl usually will as well.

     Perl Threads Are Different.

Thread-Safe Modules
     The addition of threads has changed Perl's internals sub-
     stantially. There are implications for people who write
     modules with XS code or external libraries. However, since
     perl data is not shared among threads by default, Perl
     modules stand a high chance of being thread-safe or can be
     made thread-safe easily.  Modules that are not tagged as
     thread-safe should be tested or code reviewed before being
     used in production code.

     Not all modules that you might use are thread-safe, and you
     should always assume a module is unsafe unless the documen-
     tation says otherwise.  This includes modules that are dis-
     tributed as part of the core.  Threads are a new feature,
     and even some of the standard modules aren't thread-safe.

     Even if a module is thread-safe, it doesn't mean that the
     module is optimized to work well with threads. A module
     could possibly be rewritten to utilize the new features in
     threaded Perl to increase performance in a threaded environ-

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     If you're using a module that's not thread-safe for some
     reason, you can protect yourself by using it from one, and
     only one thread at all. If you need multiple threads to
     access such a module, you can use semaphores and lots of
     programming discipline to control access to it.  Semaphores
     are covered in "Basic semaphores".

     See also "Thread-Safety of System Libraries".

Thread Basics

     The core threads module provides the basic functions you
     need to write threaded programs.  In the following sections
     we'll cover the basics, showing you what you need to do to
     create a threaded program.   After that, we'll go over some
     of the features of the threads module that make threaded
     programming easier.

     Basic Thread Support

     Thread support is a Perl compile-time option - it's some-
     thing that's turned on or off when Perl is built at your
     site, rather than when your programs are compiled. If your
     Perl wasn't compiled with thread support enabled, then any
     attempt to use threads will fail.

     Your programs can use the Config module to check whether
     threads are enabled. If your program can't run without them,
     you can say something like:

         $Config{useithreads} or die "Recompile Perl with threads to run this program.";

     A possibly-threaded program using a possibly-threaded module
     might have code like this:

         use Config;
         use MyMod;

         BEGIN {
             if ($Config{useithreads}) {
                 # We have threads
                 require MyMod_threaded;
                import MyMod_threaded;
             } else {
                require MyMod_unthreaded;
                import MyMod_unthreaded;

     Since code that runs both with and without threads is usu-
     ally pretty messy, it's best to isolate the thread-specific
     code in its own module.  In our example above, that's what
     MyMod_threaded is, and it's only imported if we're running

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     on a threaded Perl.

     A Note about the Examples

     Although thread support is considered to be stable, there
     are still a number of quirks that may startle you when you
     try out any of the examples below. In a real situation, care
     should be taken that all threads are finished executing
     before the program exits.  That care has not been taken in
     these examples in the interest of simplicity.  Running these
     examples "as is" will produce error messages, usually caused
     by the fact that there are still threads running when the
     program exits.  You should not be alarmed by this. Future
     versions of Perl may fix this problem.

     Creating Threads

     The threads package provides the tools you need to create
     new threads.  Like any other module, you need to tell Perl
     that you want to use it; "use threads" imports all the
     pieces you need to create basic threads.

     The simplest, most straightforward way to create a thread is
     with new():

         use threads;

         $thr = threads->new(\&sub1);

         sub sub1 {
             print "In the thread\n";

     The new() method takes a reference to a subroutine and
     creates a new thread, which starts executing in the refer-
     enced subroutine.  Control then passes both to the subrou-
     tine and the caller.

     If you need to, your program can pass parameters to the sub-
     routine as part of the thread startup.  Just include the
     list of parameters as part of the "threads::new" call, like

         use threads;

         $Param3 = "foo";
         $thr = threads->new(\&sub1, "Param 1", "Param 2", $Param3);
         $thr = threads->new(\&sub1, @ParamList);
         $thr = threads->new(\&sub1, qw(Param1 Param2 Param3));

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         sub sub1 {
             my @InboundParameters = @_;
             print "In the thread\n";
             print "got parameters >", join("<>", @InboundParameters), "<\n";

     The last example illustrates another feature of threads.
     You can spawn off several threads using the same subroutine.
     Each thread executes the same subroutine, but in a separate
     thread with a separate environment and potentially separate

     "create()" is a synonym for "new()".

     Waiting For A Thread To Exit

     Since threads are also subroutines, they can return values.
     To wait for a thread to exit and extract any values it might
     return, you can use the join() method:

         use threads;

         $thr = threads->new(\&sub1);

         @ReturnData = $thr->join;
         print "Thread returned @ReturnData";

         sub sub1 { return "Fifty-six", "foo", 2; }

     In the example above, the join() method returns as soon as
     the thread ends.  In addition to waiting for a thread to
     finish and gathering up any values that the thread might
     have returned, join() also performs any OS cleanup necessary
     for the thread.  That cleanup might be important, especially
     for long-running programs that spawn lots of threads.  If
     you don't want the return values and don't want to wait for
     the thread to finish, you should call the detach() method
     instead, as described next.

     Ignoring A Thread

     join() does three things: it waits for a thread to exit,
     cleans up after it, and returns any data the thread may have
     produced.  But what if you're not interested in the thread's
     return values, and you don't really care when the thread
     finishes? All you want is for the thread to get cleaned up
     after when it's done.

     In this case, you use the detach() method.  Once a thread is
     detached, it'll run until it's finished, then Perl will
     clean up after it automatically.

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         use threads;

         $thr = threads->new(\&sub1); # Spawn the thread

         $thr->detach; # Now we officially don't care any more

         sub sub1 {
             $a = 0;
             while (1) {
                 print "\$a is $a\n";
                 sleep 1;

     Once a thread is detached, it may not be joined, and any
     return data that it might have produced (if it was done and
     waiting for a join) is lost.

Threads And Data

     Now that we've covered the basics of threads, it's time for
     our next topic: data.  Threading introduces a couple of com-
     plications to data access that non-threaded programs never
     need to worry about.

     Shared And Unshared Data

     The biggest difference between Perl ithreads and the old
     5.005 style threading, or for that matter, to most other
     threading systems out there, is that by default, no data is
     shared. When a new perl thread is created, all the data
     associated with the current thread is copied to the new
     thread, and is subsequently private to that new thread! This
     is similar in feel to what happens when a UNIX process
     forks, except that in this case, the data is just copied to
     a different part of memory within the same process rather
     than a real fork taking place.

     To make use of threading however, one usually wants the
     threads to share at least some data between themselves. This
     is done with the threads::shared module and the " : shared"

         use threads;
         use threads::shared;

         my $foo : shared = 1;
         my $bar = 1;
         threads->new(sub { $foo++; $bar++ })->join;

         print "$foo\n";  #prints 2 since $foo is shared
         print "$bar\n";  #prints 1 since $bar is not shared

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     In the case of a shared array, all the array's elements are
     shared, and for a shared hash, all the keys and values are
     shared. This places restrictions on what may be assigned to
     shared array and hash elements: only simple values or refer-
     ences to shared variables are allowed - this is so that a
     private variable can't accidentally become shared. A bad
     assignment will cause the thread to die. For example:

         use threads;
         use threads::shared;

         my $var           = 1;
         my $svar : shared = 2;
         my %hash : shared;

         ... create some threads ...

         $hash{a} = 1;       # all threads see exists($hash{a}) and $hash{a} == 1
         $hash{a} = $var     # okay - copy-by-value: same effect as previous
         $hash{a} = $svar    # okay - copy-by-value: same effect as previous
         $hash{a} = \$svar   # okay - a reference to a shared variable
         $hash{a} = \$var    # This will die
         delete $hash{a}     # okay - all threads will see !exists($hash{a})

     Note that a shared variable guarantees that if two or more
     threads try to modify it at the same time, the internal
     state of the variable will not become corrupted. However,
     there are no guarantees beyond this, as explained in the
     next section.

     Thread Pitfalls: Races

     While threads bring a new set of useful tools, they also
     bring a number of pitfalls.  One pitfall is the race condi-

         use threads;
         use threads::shared;

         my $a : shared = 1;
         $thr1 = threads->new(\&sub1);
         $thr2 = threads->new(\&sub2);

         print "$a\n";

         sub sub1 { my $foo = $a; $a = $foo + 1; }
         sub sub2 { my $bar = $a; $a = $bar + 1; }

     What do you think $a will be? The answer, unfortunately, is
     "it depends." Both sub1() and sub2() access the global

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     variable $a, once to read and once to write.  Depending on
     factors ranging from your thread implementation's scheduling
     algorithm to the phase of the moon, $a can be 2 or 3.

     Race conditions are caused by unsynchronized access to
     shared data.  Without explicit synchronization, there's no
     way to be sure that nothing has happened to the shared data
     between the time you access it and the time you update it.
     Even this simple code fragment has the possibility of error:

         use threads;
         my $a : shared = 2;
         my $b : shared;
         my $c : shared;
         my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
         my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });

     Two threads both access $a.  Each thread can potentially be
     interrupted at any point, or be executed in any order.  At
     the end, $a could be 3 or 4, and both $b and $c could be 2
     or 3.

     Even "$a += 5" or "$a++" are not guaranteed to be atomic.

     Whenever your program accesses data or resources that can be
     accessed by other threads, you must take steps to coordinate
     access or risk data inconsistency and race conditions. Note
     that Perl will protect its internals from your race condi-
     tions, but it won't protect you from you.

Synchronization and control

     Perl provides a number of mechanisms to coordinate the
     interactions between themselves and their data, to avoid
     race conditions and the like. Some of these are designed to
     resemble the common techniques used in thread libraries such
     as "pthreads"; others are Perl-specific. Often, the standard
     techniques are clumsy and difficult to get right (such as
     condition waits). Where possible, it is usually easier to
     use Perlish techniques such as queues, which remove some of
     the hard work involved.

     Controlling access: lock()

     The lock() function takes a shared variable and puts a lock
     on it. No other thread may lock the variable until the vari-
     able is unlocked by the thread holding the lock. Unlocking
     happens automatically when the locking thread exits the
     outermost block that contains "lock()" function.  Using
     lock() is straightforward: this example has several threads
     doing some calculations in parallel, and occasionally

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     updating a running total:

         use threads;
         use threads::shared;

         my $total : shared = 0;

         sub calc {
             for (;;) {
                 my $result;
                 # (... do some calculations and set $result ...)
                     lock($total); # block until we obtain the lock
                     $total += $result;
                 } # lock implicitly released at end of scope
                 last if $result == 0;

         my $thr1 = threads->new(\&calc);
         my $thr2 = threads->new(\&calc);
         my $thr3 = threads->new(\&calc);
         print "total=$total\n";

     lock() blocks the thread until the variable being locked is
     available.  When lock() returns, your thread can be sure
     that no other thread can lock that variable until the outer-
     most block containing the lock exits.

     It's important to note that locks don't prevent access to
     the variable in question, only lock attempts.  This is in
     keeping with Perl's longstanding tradition of courteous pro-
     gramming, and the advisory file locking that flock() gives

     You may lock arrays and hashes as well as scalars.  Locking
     an array, though, will not block subsequent locks on array
     elements, just lock attempts on the array itself.

     Locks are recursive, which means it's okay for a thread to
     lock a variable more than once.  The lock will last until
     the outermost lock() on the variable goes out of scope. For

         my $x : shared;

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         sub doit {
                     lock($x); # wait for lock
                     lock($x); # NOOP - we already have the lock
                         lock($x); # NOOP
                             lock($x); # NOOP
                 } # *** implicit unlock here ***

         sub lockit_some_more {
             lock($x); # NOOP
         } # nothing happens here

     Note that there is no unlock() function - the only way to
     unlock a variable is to allow it to go out of scope.

     A lock can either be used to guard the data contained within
     the variable being locked, or it can be used to guard some-
     thing else, like a section of code. In this latter case, the
     variable in question does not hold any useful data, and
     exists only for the purpose of being locked. In this
     respect, the variable behaves like the mutexes and basic
     semaphores of traditional thread libraries.

     A Thread Pitfall: Deadlocks

     Locks are a handy tool to synchronize access to data, and
     using them properly is the key to safe shared data.  Unfor-
     tunately, locks aren't without their dangers, especially
     when multiple locks are involved. Consider the following

         use threads;

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         my $a : shared = 4;
         my $b : shared = "foo";
         my $thr1 = threads->new(sub {
             sleep 20;
         my $thr2 = threads->new(sub {
             sleep 20;

     This program will probably hang until you kill it.  The only
     way it won't hang is if one of the two threads acquires both
     locks first.  A guaranteed-to-hang version is more compli-
     cated, but the principle is the same.

     The first thread will grab a lock on $a, then, after a pause
     during which the second thread has probably had time to do
     some work, try to grab a lock on $b.  Meanwhile, the second
     thread grabs a lock on $b, then later tries to grab a lock
     on $a.  The second lock attempt for both threads will block,
     each waiting for the other to release its lock.

     This condition is called a deadlock, and it occurs whenever
     two or more threads are trying to get locks on resources
     that the others own.  Each thread will block, waiting for
     the other to release a lock on a resource.  That never hap-
     pens, though, since the thread with the resource is itself
     waiting for a lock to be released.

     There are a number of ways to handle this sort of problem.
     The best way is to always have all threads acquire locks in
     the exact same order.  If, for example, you lock variables
     $a, $b, and $c, always lock $a before $b, and $b before $c.
     It's also best to hold on to locks for as short a period of
     time to minimize the risks of deadlock.

     The other synchronization primitives described below can
     suffer from similar problems.

     Queues: Passing Data Around

     A queue is a special thread-safe object that lets you put
     data in one end and take it out the other without having to
     worry about synchronization issues.  They're pretty
     straightforward, and look like this:

         use threads;
         use Thread::Queue;

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         my $DataQueue = Thread::Queue->new;
         $thr = threads->new(sub {
             while ($DataElement = $DataQueue->dequeue) {
                 print "Popped $DataElement off the queue\n";

         $DataQueue->enqueue("A", "B", "C");
         sleep 10;

     You create the queue with "new Thread::Queue".  Then you can
     add lists of scalars onto the end with enqueue(), and pop
     scalars off the front of it with dequeue().  A queue has no
     fixed size, and can grow as needed to hold everything pushed
     on to it.

     If a queue is empty, dequeue() blocks until another thread
     enqueues something.  This makes queues ideal for event loops
     and other communications between threads.

     Semaphores: Synchronizing Data Access

     Semaphores are a kind of generic locking mechanism. In their
     most basic form, they behave very much like lockable
     scalars, except that they can't hold data, and that they
     must be explicitly unlocked. In their advanced form, they
     act like a kind of counter, and can allow multiple threads
     to have the 'lock' at any one time.

     Basic semaphores

     Semaphores have two methods, down() and up(): down() decre-
     ments the resource count, while up increments it. Calls to
     down() will block if the semaphore's current count would
     decrement below zero.  This program gives a quick demonstra-

         use threads;
         use Thread::Semaphore;

         my $semaphore = new Thread::Semaphore;
         my $GlobalVariable : shared = 0;

         $thr1 = new threads \&sample_sub, 1;
         $thr2 = new threads \&sample_sub, 2;
         $thr3 = new threads \&sample_sub, 3;

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         sub sample_sub {
             my $SubNumber = shift @_;
             my $TryCount = 10;
             my $LocalCopy;
             sleep 1;
             while ($TryCount--) {
                 $LocalCopy = $GlobalVariable;
                 print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n";
                 sleep 2;
                 $GlobalVariable = $LocalCopy;


     The three invocations of the subroutine all operate in sync.
     The semaphore, though, makes sure that only one thread is
     accessing the global variable at once.

     Advanced Semaphores

     By default, semaphores behave like locks, letting only one
     thread down() them at a time.  However, there are other uses
     for semaphores.

     Each semaphore has a counter attached to it. By default,
     semaphores are created with the counter set to one, down()
     decrements the counter by one, and up() increments by one.
     However, we can override any or all of these defaults simply
     by passing in different values:

         use threads;
         use Thread::Semaphore;
         my $semaphore = Thread::Semaphore->new(5);
                         # Creates a semaphore with the counter set to five

         $thr1 = threads->new(\&sub1);
         $thr2 = threads->new(\&sub1);

         sub sub1 {
             $semaphore->down(5); # Decrements the counter by five
             # Do stuff here
             $semaphore->up(5); # Increment the counter by five


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     If down() attempts to decrement the counter below zero, it
     blocks until the counter is large enough.  Note that while a
     semaphore can be created with a starting count of zero, any
     up() or down() always changes the counter by at least one,
     and so $semaphore->down(0) is the same as

     The question, of course, is why would you do something like
     this? Why create a semaphore with a starting count that's
     not one, or why decrement/increment it by more than one? The
     answer is resource availability.  Many resources that you
     want to manage access for can be safely used by more than
     one thread at once.

     For example, let's take a GUI driven program.  It has a
     semaphore that it uses to synchronize access to the display,
     so only one thread is ever drawing at once.  Handy, but of
     course you don't want any thread to start drawing until
     things are properly set up.  In this case, you can create a
     semaphore with a counter set to zero, and up it when things
     are ready for drawing.

     Semaphores with counters greater than one are also useful
     for establishing quotas.  Say, for example, that you have a
     number of threads that can do I/O at once.  You don't want
     all the threads reading or writing at once though, since
     that can potentially swamp your I/O channels, or deplete
     your process' quota of filehandles.  You can use a semaphore
     initialized to the number of concurrent I/O requests (or
     open files) that you want at any one time, and have your
     threads quietly block and unblock themselves.

     Larger increments or decrements are handy in those cases
     where a thread needs to check out or return a number of
     resources at once.

     cond_wait() and cond_signal()

     These two functions can be used in conjunction with locks to
     notify co-operating threads that a resource has become
     available. They are very similar in use to the functions
     found in "pthreads". However for most purposes, queues are
     simpler to use and more intuitive. See threads::shared for
     more details.

     Giving up control

     There are times when you may find it useful to have a thread
     explicitly give up the CPU to another thread.  You may be
     doing something processor-intensive and want to make sure
     that the user-interface thread gets called frequently.
     Regardless, there are times that you might want a thread to

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     give up the processor.

     Perl's threading package provides the yield() function that
     does this. yield() is pretty straightforward, and works like

         use threads;

         sub loop {
                 my $thread = shift;
                 my $foo = 50;
                 while($foo--) { print "in thread $thread\n" }
                 $foo = 50;
                 while($foo--) { print "in thread $thread\n" }

         my $thread1 = threads->new(\&loop, 'first');
         my $thread2 = threads->new(\&loop, 'second');
         my $thread3 = threads->new(\&loop, 'third');

     It is important to remember that yield() is only a hint to
     give up the CPU, it depends on your hardware, OS and thread-
     ing libraries what actually happens. On many operating sys-
     tems, yield() is a no-op.  Therefore it is important to note
     that one should not build the scheduling of the threads
     around yield() calls. It might work on your platform but it
     won't work on another platform.

General Thread Utility Routines

     We've covered the workhorse parts of Perl's threading pack-
     age, and with these tools you should be well on your way to
     writing threaded code and packages.  There are a few useful
     little pieces that didn't really fit in anyplace else.

     What Thread Am I In?

     The "threads->self" class method provides your program with
     a way to get an object representing the thread it's
     currently in.  You can use this object in the same way as
     the ones returned from thread creation.

     Thread IDs

     tid() is a thread object method that returns the thread ID
     of the thread the object represents.  Thread IDs are
     integers, with the main thread in a program being 0.
     Currently Perl assigns a unique tid to every thread ever
     created in your program, assigning the first thread to be
     created a tid of 1, and increasing the tid by 1 for each new
     thread that's created.

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     Are These Threads The Same?

     The equal() method takes two thread objects and returns true
     if the objects represent the same thread, and false if they

     Thread objects also have an overloaded == comparison so that
     you can do comparison on them as you would with normal

     What Threads Are Running?

     "threads->list" returns a list of thread objects, one for
     each thread that's currently running and not detached.
     Handy for a number of things, including cleaning up at the
     end of your program:

         # Loop through all the threads
         foreach $thr (threads->list) {
             # Don't join the main thread or ourselves
             if ($thr->tid && !threads::equal($thr, threads->self)) {

     If some threads have not finished running when the main Perl
     thread ends, Perl will warn you about it and die, since it
     is impossible for Perl to clean up itself while other
     threads are running

A Complete Example

     Confused yet? It's time for an example program to show some
     of the things we've covered.  This program finds prime
     numbers using threads.

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         1  #!/usr/bin/perl -w
         2  # prime-pthread, courtesy of Tom Christiansen
         4  use strict;
         6  use threads;
         7  use Thread::Queue;
         9  my $stream = new Thread::Queue;
         10 my $kid    = new threads(\&check_num, $stream, 2);
         12 for my $i ( 3 .. 1000 ) {
         13     $stream->enqueue($i);
         14 }
         16 $stream->enqueue(undef);
         17 $kid->join;
         19 sub check_num {
         20     my ($upstream, $cur_prime) = @_;
         21     my $kid;
         22     my $downstream = new Thread::Queue;
         23     while (my $num = $upstream->dequeue) {
         24         next unless $num % $cur_prime;
         25         if ($kid) {
         26            $downstream->enqueue($num);
         27                  } else {
         28            print "Found prime $num\n";
         29                $kid = new threads(\&check_num, $downstream, $num);
         30         }
         31     }
         32     $downstream->enqueue(undef) if $kid;
         33     $kid->join           if $kid;
         34 }

     This program uses the pipeline model to generate prime
     numbers.  Each thread in the pipeline has an input queue
     that feeds numbers to be checked, a prime number that it's
     responsible for, and an output queue into which it funnels
     numbers that have failed the check.  If the thread has a
     number that's failed its check and there's no child thread,
     then the thread must have found a new prime number.  In that
     case, a new child thread is created for that prime and stuck
     on the end of the pipeline.

     This probably sounds a bit more confusing than it really is,
     so let's go through this program piece by piece and see what
     it does.  (For those of you who might be trying to remember
     exactly what a prime number is, it's a number that's only
     evenly divisible by itself and 1)

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     The bulk of the work is done by the check_num() subroutine,
     which takes a reference to its input queue and a prime
     number that it's responsible for.  After pulling in the
     input queue and the prime that the subroutine's checking
     (line 20), we create a new queue (line 22) and reserve a
     scalar for the thread that we're likely to create later
     (line 21).

     The while loop from lines 23 to line 31 grabs a scalar off
     the input queue and checks against the prime this thread is
     responsible for.  Line 24 checks to see if there's a
     remainder when we modulo the number to be checked against
     our prime.  If there is one, the number must not be evenly
     divisible by our prime, so we need to either pass it on to
     the next thread if we've created one (line 26) or create a
     new thread if we haven't.

     The new thread creation is line 29.  We pass on to it a
     reference to the queue we've created, and the prime number
     we've found.

     Finally, once the loop terminates (because we got a 0 or
     undef in the queue, which serves as a note to die), we pass
     on the notice to our child and wait for it to exit if we've
     created a child (lines 32 and 37).

     Meanwhile, back in the main thread, we create a queue (line
     9) and the initial child thread (line 10), and pre-seed it
     with the first prime: 2.  Then we queue all the numbers from
     3 to 1000 for checking (lines 12-14), then queue a die
     notice (line 16) and wait for the first child thread to ter-
     minate (line 17).  Because a child won't die until its child
     has died, we know that we're done once we return from the

     That's how it works.  It's pretty simple; as with many Perl
     programs, the explanation is much longer than the program.

Different implementations of threads

     Some background on thread implementations from the operating
     system viewpoint.  There are three basic categories of
     threads: user-mode threads, kernel threads, and multiproces-
     sor kernel threads.

     User-mode threads are threads that live entirely within a
     program and its libraries.  In this model, the OS knows
     nothing about threads.  As far as it's concerned, your pro-
     cess is just a process.

     This is the easiest way to implement threads, and the way
     most OSes start.  The big disadvantage is that, since the OS
     knows nothing about threads, if one thread blocks they all

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     do.  Typical blocking activities include most system calls,
     most I/O, and things like sleep().

     Kernel threads are the next step in thread evolution.  The
     OS knows about kernel threads, and makes allowances for
     them.  The main difference between a kernel thread and a
     user-mode thread is blocking.  With kernel threads, things
     that block a single thread don't block other threads.  This
     is not the case with user-mode threads, where the kernel
     blocks at the process level and not the thread level.

     This is a big step forward, and can give a threaded program
     quite a performance boost over non-threaded programs.
     Threads that block performing I/O, for example, won't block
     threads that are doing other things.  Each process still has
     only one thread running at once, though, regardless of how
     many CPUs a system might have.

     Since kernel threading can interrupt a thread at any time,
     they will uncover some of the implicit locking assumptions
     you may make in your program.  For example, something as
     simple as "$a = $a + 2" can behave unpredictably with kernel
     threads if $a is visible to other threads, as another thread
     may have changed $a between the time it was fetched on the
     right hand side and the time the new value is stored.

     Multiprocessor kernel threads are the final step in thread
     support.  With multiprocessor kernel threads on a machine
     with multiple CPUs, the OS may schedule two or more threads
     to run simultaneously on different CPUs.

     This can give a serious performance boost to your threaded
     program, since more than one thread will be executing at the
     same time.  As a tradeoff, though, any of those nagging syn-
     chronization issues that might not have shown with basic
     kernel threads will appear with a vengeance.

     In addition to the different levels of OS involvement in
     threads, different OSes (and different thread implementa-
     tions for a particular OS) allocate CPU cycles to threads in
     different ways.

     Cooperative multitasking systems have running threads give
     up control if one of two things happen.  If a thread calls a
     yield function, it gives up control.  It also gives up con-
     trol if the thread does something that would cause it to
     block, such as perform I/O.  In a cooperative multitasking
     implementation, one thread can starve all the others for CPU
     time if it so chooses.

     Preemptive multitasking systems interrupt threads at regular
     intervals while the system decides which thread should run

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     next.  In a preemptive multitasking system, one thread usu-
     ally won't monopolize the CPU.

     On some systems, there can be cooperative and preemptive
     threads running simultaneously. (Threads running with real-
     time priorities often behave cooperatively, for example,
     while threads running at normal priorities behave preemp-

     Most modern operating systems support preemptive multitask-
     ing nowadays.

Performance considerations

     The main thing to bear in mind when comparing ithreads to
     other threading models is the fact that for each new thread
     created, a complete copy of all the variables and data of
     the parent thread has to be taken. Thus thread creation can
     be quite expensive, both in terms of memory usage and time
     spent in creation. The ideal way to reduce these costs is to
     have a relatively short number of long-lived threads, all
     created fairly early on -  before the base thread has accu-
     mulated too much data. Of course, this may not always be
     possible, so compromises have to be made. However, after a
     thread has been created, its performance and extra memory
     usage should be little different than ordinary code.

     Also note that under the current implementation, shared
     variables use a little more memory and are a little slower
     than ordinary variables.

Process-scope Changes
     Note that while threads themselves are separate execution
     threads and Perl data is thread-private unless explicitly
     shared, the threads can affect process-scope state, affect-
     ing all the threads.

     The most common example of this is changing the current
     working directory using chdir().  One thread calls chdir(),
     and the working directory of all the threads changes.

     Even more drastic example of a process-scope change is
     chroot(): the root directory of all the threads changes, and
     no thread can undo it (as opposed to chdir()).

     Further examples of process-scope changes include umask()
     and changing uids/gids.

     Thinking of mixing fork() and threads?  Please lie down and
     wait until the feeling passes.  Be aware that the semantics
     of fork() vary between platforms.  For example, some UNIX
     systems copy all the current threads into the child process,
     while others only copy the thread that called fork(). You

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     have been warned!

     Similarly, mixing signals and threads should not be
     attempted. Implementations are platform-dependent, and even
     the POSIX semantics may not be what you expect (and Perl
     doesn't even give you the full POSIX API).

Thread-Safety of System Libraries
     Whether various library calls are thread-safe is outside the
     control of Perl.  Calls often suffering from not being
     thread-safe include: localtime(), gmtime(),
     get{gr,host,net,proto,serv,pw}*(), readdir(), rand(), and
     srand() -- in general, calls that depend on some global
     external state.

     If the system Perl is compiled in has thread-safe variants
     of such calls, they will be used.  Beyond that, Perl is at
     the mercy of the thread-safety or -unsafety of the calls.
     Please consult your C library call documentation.

     On some platforms the thread-safe library interfaces may
     fail if the result buffer is too small (for example the user
     group databases may be rather large, and the reentrant
     interfaces may have to carry around a full snapshot of those
     databases).  Perl will start with a small buffer, but keep
     retrying and growing the result buffer until the result
     fits.  If this limitless growing sounds bad for security or
     memory consumption reasons you can recompile Perl with
     PERL_REENTRANT_MAXSIZE defined to the maximum number of
     bytes you will allow.


     A complete thread tutorial could fill a book (and has, many
     times), but with what we've covered in this introduction,
     you should be well on your way to becoming a threaded Perl


     Here's a short bibliography courtesy of J|rgen Christoffel:

     Introductory Texts

     Birrell, Andrew D. An Introduction to Programming with
     Threads. Digital Equipment Corporation, 1989, DEC-SRC
     Research Report #35 online as
     (highly recommended)

     Robbins, Kay. A., and Steven Robbins. Practical Unix Pro-
     gramming: A Guide to Concurrency, Communication, and Mul-
     tithreading. Prentice-Hall, 1996.

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     Lewis, Bill, and Daniel J. Berg. Multithreaded Programming
     with Pthreads. Prentice Hall, 1997, ISBN 0-13-443698-9 (a
     well-written introduction to threads).

     Nelson, Greg (editor). Systems Programming with Modula-3.
     Prentice Hall, 1991, ISBN 0-13-590464-1.

     Nichols, Bradford, Dick Buttlar, and Jacqueline Proulx Far-
     rell. Pthreads Programming. O'Reilly & Associates, 1996,
     ISBN 156592-115-1 (covers POSIX threads).

     OS-Related References

     Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
     LoVerso. Programming under Mach. Addison-Wesley, 1994, ISBN

     Tanenbaum, Andrew S. Distributed Operating Systems. Prentice
     Hall, 1995, ISBN 0-13-219908-4 (great textbook).

     Silberschatz, Abraham, and Peter B. Galvin. Operating System
     Concepts, 4th ed. Addison-Wesley, 1995, ISBN 0-201-59292-4

     Other References

     Arnold, Ken and James Gosling. The Java Programming
     Language, 2nd ed. Addison-Wesley, 1998, ISBN 0-201-31006-6.

     comp.programming.threads FAQ,

     Le Sergent, T. and B. Berthomieu. "Incremental MultiThreaded
     Garbage Collection on Virtually Shared Memory Architectures"
     in Memory Management: Proc. of the International Workshop
     IWMM 92, St. Malo, France, September 1992, Yves Bekkers and
     Jacques Cohen, eds. Springer, 1992, ISBN 3540-55940-X
     (real-life thread applications).

     Artur Bergman, "Where Wizards Fear To Tread", June 11, 2002,


     Thanks (in no particular order) to Chaim Frenkel, Steve
     Fink, Gurusamy Sarathy, Ilya Zakharevich, Benjamin Sugars,
     J|rgen Christoffel, Joshua Pritikin, and Alan Burlison, for
     their help in reality-checking and polishing this article.
     Big thanks to Tom Christiansen for his rewrite of the prime
     number generator.


     Dan Sugalski <dan@sidhe.org<gt>

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     Slightly modified by Arthur Bergman to fit the new thread

     Reworked slightly by Jvrg Walter <jwalt@cpan.org<gt> to be
     more concise about thread-safety of perl code.

     Rearranged slightly by Elizabeth Mattijsen
     <liz@dijkmat.nl<gt> to put less emphasis on yield().


     The original version of this article originally appeared in
     The Perl Journal #10, and is copyright 1998 The Perl Jour-
     nal. It appears courtesy of Jon Orwant and The Perl Journal.
     This document may be distributed under the same terms as
     Perl itself.

     For more information please see threads and threads::shared.

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