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NAME
       perlthrtut - Tutorial on threads in Perl

DESCRIPTION
       This tutorial describes the use of Perl interpreter
       threads (sometimes referred to as ithreads) that was first
       introduced in Perl 5.6.0.  In this model, each thread runs
       in its own Perl interpreter, and any data sharing between
       threads must be explicit.  The user-level interface for
       ithreads uses the threads class.

       NOTE: There was another older Perl threading flavor called
       the 5.005 model that used the Threads class.  This old
       model was known to have problems, is deprecated, and was
       removed for 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 threads and threads::shared modules are included in
       the core Perl distribution.  Additionally, they are
       maintained as a separate modules on CPAN, so you can check
       there for any updates.

What Is A Thread Anyway?
       A thread is a flow of control through a program with a
       single 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.

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



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       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 waiting 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 rendering engines, where the individual threads
       can pass on interim results to give the user visual
       feedback.

   Pipeline
       The pipeline model divides up a task into a series of
       steps, and passes the results of one step on to the thread
       processing 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
       processors 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 different 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 generators both map well to this form of the
       pipeline model. (A 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



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       Green threads, or Win32 threads.  There are similarities,
       and the broad concepts are the same, but if you start
       looking for implementation details you're going to be
       either disappointed or confused.  Possibly both.

       This is not to say that Perl threads are completely
       different 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 system's
       threads allow 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
       substantially. 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
       documentation says otherwise.  This includes modules that
       are distributed as part of the core.  Threads are a
       relatively 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
       environment.

       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".





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Thread Basics
       The 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
       something 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:

           use Config;
           $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
       usually 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 on a threaded Perl.

   A Note about the Examples
       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.




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   Creating Threads
       The threads module 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 "create()":

           use threads;

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

           sub sub1 {
               print("In the thread\n");
           }

       The "create()" method takes a reference to a subroutine
       and creates a new thread that starts executing in the
       referenced subroutine.  Control then passes both to the
       subroutine and the caller.

       If you need to, your program can pass parameters to the
       subroutine as part of the thread startup.  Just include
       the list of parameters as part of the "threads->create()"
       call, like this:

           use threads;

           my $Param3 = 'foo';
           my $thr1 = threads->create(\&sub1, 'Param 1', 'Param 2', $Param3);
           my @ParamList = (42, 'Hello', 3.14);
           my $thr2 = threads->create(\&sub1, @ParamList);
           my $thr3 = threads->create(\&sub1, qw(Param1 Param2 Param3));

           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 arguments.

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

   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:




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           use threads;

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

           my @ReturnData = $thr->join();
           print('Thread returned ', join(', ', @ReturnData), "\n");

           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.

       NOTE: In the example above, the thread returns a list,
       thus necessitating that the thread creation call be made
       in list context (i.e., "my ($thr)").  See ""$thr-" in
       threadsjoin()"> and "THREAD CONTEXT" in threads for more
       details on thread context and return values.

   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.

           use threads;

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

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

           sleep(15);        # Let thread run for awhile

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




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       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.

       "detach()" can also be called as a class method to allow a
       thread to detach itself:

           use threads;

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

           sub sub1 {
               threads->detach();
               # Do more work
           }

   Process and Thread Termination
       With threads one must be careful to make sure they all
       have a chance to run to completion, assuming that is what
       you want.

       An action that terminates a process will terminate all
       running threads.  die() and exit() have this property, and
       perl does an exit when the main thread exits, perhaps
       implicitly by falling off the end of your code, even if
       that's not what you want.

       As an example of this case, this code prints the message
       "Perl exited with active threads: 2 running and unjoined":

           use threads;
           my $thr1 = threads->new(\&thrsub, "test1");
           my $thr2 = threads->new(\&thrsub, "test2");
           sub thrsub {
              my ($message) = @_;
              sleep 1;
              print "thread $message\n";
           }

       But when the following lines are added at the end:

           $thr1->join();
           $thr2->join();

       it prints two lines of output, a perhaps more useful
       outcome.

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 complications to data access that non-threaded programs
       never need to worry about.





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   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" attribute:

           use threads;
           use threads::shared;

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

           print("$foo\n");  # Prints 2 since $foo is shared
           print("$bar\n");  # Prints 1 since $bar is not shared

       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 references 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



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       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
       condition:

           use threads;
           use threads::shared;

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

           $thr1->join();
           $thr2->join();
           print("$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 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; });
           $thr1->join();
           $thr2->join();

       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



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       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 conditions, 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 variable is unlocked by the thread holding the lock.
       Unlocking happens automatically when the locking thread
       exits the block that contains the call to the "lock()"
       function.  Using "lock()" is straightforward: This example
       has several threads doing some calculations in parallel,
       and occasionally updating a running total:

           use threads;
           use threads::shared;

           my $total :shared = 0;

           sub calc {
               while (1) {
                   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->create(\&calc);
           my $thr2 = threads->create(\&calc);
           my $thr3 = threads->create(\&calc);
           $thr1->join();
           $thr2->join();
           $thr3->join();
           print("total=$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



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       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
       programming, and the advisory file locking that "flock()"
       gives you.

       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 example:

           my $x :shared;
           doit();

           sub doit {
               {
                   {
                       lock($x); # Wait for lock
                       lock($x); # NOOP - we already have the lock
                       {
                           lock($x); # NOOP
                           {
                               lock($x); # NOOP
                               lockit_some_more();
                           }
                       }
                   } # *** 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 something 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



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       using them properly is the key to safe shared data.
       Unfortunately, locks aren't without their dangers,
       especially when multiple locks are involved.  Consider the
       following code:

           use threads;

           my $a :shared = 4;
           my $b :shared = 'foo';
           my $thr1 = threads->create(sub {
               lock($a);
               sleep(20);
               lock($b);
           });
           my $thr2 = threads->create(sub {
               lock($b);
               sleep(20);
               lock($a);
           });

       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 complicated, 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 happens, 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



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       straightforward, and look like this:

           use threads;
           use Thread::Queue;

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

           $DataQueue->enqueue(12);
           $DataQueue->enqueue("A", "B", "C");
           sleep(10);
           $DataQueue->enqueue(undef);
           $thr->join();

       You create the queue with "Thread::Queue->new()".  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()"
       decrements 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 demonstration:

           use threads;
           use Thread::Semaphore;

           my $semaphore = Thread::Semaphore->new();
           my $GlobalVariable :shared = 0;

           $thr1 = threads->create(\&sample_sub, 1);
           $thr2 = threads->create(\&sample_sub, 2);
           $thr3 = threads->create(\&sample_sub, 3);

           sub sample_sub {



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

           $thr1->join();
           $thr2->join();
           $thr3->join();

       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

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

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

           $thr1->detach();
           $thr2->detach();

       If "down()" attempts to decrement the counter below zero,
       it blocks until the counter is large enough.  Note that



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       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 "$semaphore->down(0)" is the same as
       "$semaphore->down(1)".

       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 or 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.

   Waiting for a Condition
       The functions "cond_wait()" and "cond_signal()" 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 give up the processor.

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



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           use threads;

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

           my $thr1 = threads->create(\&loop, 'first');
           my $thr2 = threads->create(\&loop, 'second');
           my $thr3 = threads->create(\&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
       threading libraries what actually happens.  On many
       operating systems, 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
       package, 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.  When used as a class method,
       "threads->tid()" can be used by a thread to get its own
       TID.

   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 don't.

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



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       normal objects.

   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 (from the main Perl thread, of
       course):

           # Loop through all the threads
           foreach my $thr (threads->list()) {
               $thr->join();
           }

       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.

       NOTE:  The main Perl thread (thread 0) is in a detached
       state, and so does not appear in the list returned by
       "threads->list()".

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.

            1 #!/usr/bin/perl
            2 # prime-pthread, courtesy of Tom Christiansen
            3
            4 use strict;
            5 use warnings;
            6
            7 use threads;
            8 use Thread::Queue;
            9
           10 sub check_num {
           11     my ($upstream, $cur_prime) = @_;
           12     my $kid;
           13     my $downstream = Thread::Queue->new();
           14     while (my $num = $upstream->dequeue()) {
           15         next unless ($num % $cur_prime);
           16         if ($kid) {
           17             $downstream->enqueue($num);
           18         } else {
           19             print("Found prime: $num\n");
           20             $kid = threads->create(\&check_num, $downstream, $num);
           21             if (! $kid) {
           22                 warn("Sorry.  Ran out of threads.\n");
           23                 last;
           24             }
           25         }
           26     }



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           27     if ($kid) {
           28         $downstream->enqueue(undef);
           29         $kid->join();
           30     }
           31 }
           32
           33 my $stream = Thread::Queue->new(3..1000, undef);
           34 check_num($stream, 2);

       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.)

       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 is
       checking (line 11), we create a new queue (line 13) and
       reserve a scalar for the thread that we're likely to
       create later (line 12).

       The while loop from line 14 to line 26 grabs a scalar off
       the input queue and checks against the prime this thread
       is responsible for.  Line 15 checks to see if there's a
       remainder when we divide the number to be checked by 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 17) or create a
       new thread if we haven't.

       The new thread creation is line 20.  We pass on to it a
       reference to the queue we've created, and the prime number
       we've found.  In lines 21 through 24, we check to make
       sure that our new thread got created, and if not, we stop
       checking any remaining numbers in the queue.

       Finally, once the loop terminates (because we got a 0 or
       "undef" in the queue, which serves as a note to
       terminate), we pass on the notice to our child, and wait
       for it to exit if we've created a child (lines 27 and 30).

       Meanwhile, back in the main thread, we first create a



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       queue (line 33) and queue up all the numbers from 3 to
       1000 for checking, plus a termination notice.  Then all we
       have to do to get the ball rolling is pass the queue and
       the first prime to the "check_num()" subroutine (line 34).

       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 multiprocessor 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
       process 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 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



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       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 synchronization 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
       implementations 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
       control 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 next.  In a preemptive multitasking system, one
       thread usually won't monopolize the CPU.

       On some systems, there can be cooperative and preemptive
       threads running simultaneously. (Threads running with
       realtime priorities often behave cooperatively, for
       example, while threads running at normal priorities behave
       preemptively.)

       Most modern operating systems support preemptive
       multitasking nowadays.

Performance considerations
       The main thing to bear in mind when comparing Perl's
       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 accumulated 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.




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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,
       affecting 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 and 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 have been warned!

       Similarly, mixing signals and threads may be problematic.
       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).  For example, there is
       no way to guarantee that a signal sent to a multi-threaded
       Perl application will get intercepted by any particular
       thread.  (However, a recently added feature does provide
       the capability to send signals between threads.  See
       ""THREAD SIGNALLING" in threads for more details.)

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()",  functions
       fetching user, group and network information (such as
       "getgrent()", "gethostent()", "getnetent()" and so on),
       "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



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       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.

Conclusion
       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 expert.

SEE ALSO
       Annotated POD for threads:
       <http://annocpan.org/?mode=search&field=Module&name=threads>

       Lastest version of threads on CPAN:
       <http://search.cpan.org/search?module=threads>

       Annotated POD for threads::shared:
       <http://annocpan.org/?mode=search&field=Module&name=threads%3A%3Ashared>

       Lastest version of threads::shared on CPAN:
       <http://search.cpan.org/search?module=threads%3A%3Ashared>

       Perl threads mailing list:
       <http://lists.cpan.org/showlist.cgi?name=iThreads>

Bibliography
       Here's a short bibliography courtesy of JXrgen
       Christoffel:

   Introductory Texts
       Birrell, Andrew D. An Introduction to Programming with
       Threads. Digital Equipment Corporation, 1989, DEC-SRC
       Research Report #35 online as
       http://gatekeeper.dec.com/pub/DEC/SRC/research-reports/abstracts/src-rr-035.html
       (highly recommended)

       Robbins, Kay. A., and Steven Robbins. Practical Unix
       Programming: A Guide to Concurrency, Communication, and
       Multithreading. Prentice-Hall, 1996.

       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
       Farrell.  Pthreads Programming. O'Reilly & Associates,
       1996, ISBN 156592-115-1 (covers POSIX threads).




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   OS-Related References
       Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
       LoVerso. Programming under Mach. Addison-Wesley, 1994,
       ISBN 0-201-52739-1.

       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,
       <http://www.serpentine.com/~bos/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, <http://www.perl.com/pub/a/2002/06/11/threads.html>

Acknowledgements
       Thanks (in no particular order) to Chaim Frenkel, Steve
       Fink, Gurusamy Sarathy, Ilya Zakharevich, Benjamin Sugars,
       JXrgen 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.

AUTHOR
       Dan Sugalski <dan@sidhe.org<gt>

       Slightly modified by Arthur Bergman to fit the new thread
       model/module.

       Reworked slightly by JXrg 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().

Copyrights
       The original version of this article originally appeared
       in The Perl Journal #10, and is copyright 1998 The Perl



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       Journal. It appears courtesy of Jon Orwant and The Perl
       Journal.  This document may be distributed under the same
       terms as Perl itself.






















































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