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perlthrtut (1)

Name

perlthrtut - Tutorial on threads in Perl

Synopsis

Please see following description for synopsis

Description




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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



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     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
     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.



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     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
     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



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     are covered in "Basic semaphores".

     See also "Thread-Safety of System Libraries".

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



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     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.

  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.



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     "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:

         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->join()" in threads
     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




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         sub sub1 {
             $a = 0;
             while (1) {
                 $a++;
                 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.

     "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();



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     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.

  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 ...



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         $hash{a} = 1;       # All threads see exists($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
     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:











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         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 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 ...)



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                 {
                     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
     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 ***



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             }
         }

         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
     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.




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     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
     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



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     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 {
             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.





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     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 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's quota of filehandles.  You can use a



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     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:

         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.





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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 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()".




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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 (! $kid) {
         22                 warn("Sorry.  Ran out of threads.\n");
         23                 last;
         24             }
         25         }
         26     }
         27     if ($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



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     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 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.




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     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 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.



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     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.

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.





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     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 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.


ATTRIBUTES
     See attributes(5) for descriptions of the following
     attributes:



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     +---------------+------------------+
     |ATTRIBUTE TYPE | ATTRIBUTE VALUE  |
     +---------------+------------------+
     |Availability   | runtime/perl-512 |
     +---------------+------------------+
     |Stability      | Uncommitted      |
     +---------------+------------------+
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 JA~Xrgen
     Christoffel:

  Introductory Texts
     Birrell, Andrew D. An Introduction to Programming with
     Threads. Digital Equipment Corporation, 1989, DEC-SRC
     Research Report #35 online as
     ftp://ftp.dec.com/pub/DEC/SRC/research-reports/SRC-035.pdf
     (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).

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



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     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/
     <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,
     JA~Xrgen 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 JA~Xrg 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
     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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NOTES
     This software was built from source available at
     https://java.net/projects/solaris-userland.  The original
     community source was downloaded from
     http://www.cpan.org/src/5.0/perl-5.12.5.tar.bz2

     Further information about this software can be found on the
     open source community website at http://www.perl.org/.















































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