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perlthrtut



DESCRIPTION

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

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

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

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


Status

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


What Is A Thread Anyway?

       A thread is a flow of control through a program with a
       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


       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 vec­
       tor 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 dif­
       ferent 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 pro­
       cessors so two or more threads will be executing in paral­
       lel, 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 program­
       ming 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 val­
       ues of X.  They aren't POSIX threads, or DecThreads, or
       Java's Green threads, or Win32 threads.  There are simi­
       larities, 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 dif­


Thread-Safe Modules

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

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

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

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

       See also "Thread-Safety of System Libraries".


Thread Basics

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

       Basic Thread Support

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

       Your programs can use the Config module to check whether
       threads are enabled. If your program can't run without
       them, you can say something like:
                  import MyMod_threaded;
               } else {
                  require MyMod_unthreaded;
                  import MyMod_unthreaded;
               }
           }

       Since code that runs both with and without threads is usu­
       ally pretty messy, it's best to isolate the thread-spe­
       cific 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

       Although thread support is considered to be stable, there
       are still a number of quirks that may startle you when you
       try out any of the examples below.  In a real situation,
       care should be taken that all threads are finished execut­
       ing 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 mes­
       sages, usually caused by the fact that there are still
       threads running when the program exits.  You should not be
       alarmed by this.  Future versions of Perl may fix this
       problem.

       Creating Threads

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

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

           use threads;

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

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

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

       If you need to, your program can pass parameters to the
       subroutine as part of the thread startup.  Just include
               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 subrou­
       tine.  Each thread executes the same subroutine, but in a
       separate thread with a separate environment and poten­
       tially separate arguments.

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

       Waiting For A Thread To Exit

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

           use threads;

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

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

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

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

       Ignoring A Thread

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

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

           use threads;

           }

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


Threads And Data

       Now that we've covered the basics of threads, it's time
       for our next topic: data.  Threading introduces a couple
       of 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 pro­
       cess forks, except that in this case, the data is just
       copied to a different part of memory within the same pro­
       cess 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->new(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;

       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 con­
       dition:

           use threads;
           use threads::shared;

           my $a : shared = 1;
           $thr1 = threads->new(\&sub1);
           $thr2 = threads->new(\&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 schedul­
       ing 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 possi­
       bility 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.
       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 outermost block that contains "lock()" function.
       Using lock() is straightforward: this example has several
       threads doing some calculations in parallel, and occasion­
       ally updating a running total:

           use threads;
           use threads::shared;

           my $total : shared = 0;

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

           my $thr1 = threads->new(\&calc);
           my $thr2 = threads->new(\&calc);
           my $thr3 = threads->new(\&calc);
           $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
       outermost 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.
               {
                   {
                       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 lat­
       ter case, the variable in question does not hold any use­
       ful 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, espe­
       cially when multiple locks are involved.  Consider the
       following code:

           use threads;

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

       This condition is called a deadlock, and it occurs when­
       ever 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 vari­
       ables $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;
           $thr = threads->new(sub {
               while ($DataElement = $DataQueue->dequeue) {
                   print "Popped $DataElement off the queue\n";
               }
           });

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

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

           use threads;
           use Thread::Semaphore;

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

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

           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.

       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 sim­
       ply 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

           $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/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 dis­
       play, 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 them­
       selves.

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

       cond_wait() and cond_signal()

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

       Giving up control

       There are times when you may find it useful to have a
       thread explicitly give up the CPU to another thread.  You
                   while($foo--) { print "in thread $thread\n" }
                   threads->yield;
                   $foo = 50;
                   while($foo--) { print "in thread $thread\n" }
           }

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

       It is important to remember that yield() is only a hint to
       give up the CPU, it depends on your hardware, OS and
       threading libraries what actually happens.  On many oper­
       ating systems, yyiieelldd(()) is a no-op.  Therefore it is impor­
       tant 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 any­
       place 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 inte­
       gers, with the main thread in a program being 0.  Cur­
       rently Perl assigns a unique tid to every thread ever cre­
       ated 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.

       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 nor­
       mal objects.


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


A Complete Example

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

           1  #!/usr/bin/perl -w
           2  # prime-pthread, courtesy of Tom Christiansen
           3
           4  use strict;
           5
           6  use threads;
           7  use Thread::Queue;
           8
           9  my $stream = new Thread::Queue;
           10 my $kid    = new threads(\&check_num, $stream, 2);
           11
           12 for my $i ( 3 .. 1000 ) {
           13     $stream->enqueue($i);
           14 }
           15
           16 $stream->enqueue(undef);
           17 $kid->join;
           18
           19 sub check_num {
           20     my ($upstream, $cur_prime) = @_;
           21     my $kid;
           22     my $downstream = new Thread::Queue;
           23     while (my $num = $upstream->dequeue) {
           24         next unless $num % $cur_prime;
           25         if ($kid) {
           26            $downstream->enqueue($num);
           27                  } else {
           28            print "Found prime $num\n";
           29                $kid = new threads(\&check_num, $downstream, $num);
           30         }
           31     }
           32     $downstream->enqueue(undef) if $kid;
           33     $kid->join           if $kid;
           34 }

       This program uses the pipeline model to generate prime
       numbers.  Each thread in the pipeline has an input queue
       that feeds numbers to be checked, a prime number that it's
       responsible for, and an output queue into which it funnels
       numbers that have failed the check.  If the thread has a
       number that's failed its check and there's no child
       ing (line 20), we create a new queue (line 22) and reserve
       a scalar for the thread that we're likely to create later
       (line 21).

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

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

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

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

       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 operat­
       ing system viewpoint.  There are three basic categories of
       threads: user-mode threads, kernel threads, and multipro­
       cessor 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().

       less 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 ker­
       nel 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 nag­
       ging 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 implementa­
       tions for a particular OS) allocate CPU cycles to threads
       in different ways.

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

       Preemptive multitasking systems interrupt threads at regu­
       lar 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 exam­
       ple, while threads running at normal priorities behave
       preemptively.)

       Most modern operating systems support preemptive multi­
       tasking nowadays.


Performance considerations

       The main thing to bear in mind when comparing ithreads to
       other threading models is the fact that for each new
       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/gids.

       Thinking of mixing fork() and threads?  Please lie down
       and wait until the feeling passes-- but in case you really
       want to know, the semantics is that fork() duplicates all
       the threads.  (In UNIX, at least, other platforms will do
       something different.)

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


Thread-Safety of System Libraries

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

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

       On some platforms the thread-safe library interfaces may
       fail if the result buffer is too small (for example the
       user group databases may be rather large, and the reen­
       trant 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

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

       Robbins, Kay. A., and Steven Robbins. Practical Unix Pro­
       gramming: A Guide to Concurrency, Communication, and Mul­
       tithreading. 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 0-201-52739-1.

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

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

       Other References

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

       comp.programming.threads FAQ, <http://www.serpen­
       tine.com/~bos/threads-faq/>

       Le Sergent, T. and B. Berthomieu. "Incremental Multi­
       Threaded Garbage Collection on Virtually Shared Memory
       Architectures" in Memory Management: Proc. of the Interna­
       tional 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>

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

       Rearranged slightly by Elizabeth Mattijsen <liz@dijk­
       mat.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.

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

perl v5.8.1                 2003-09-02              PERLTHRTUT(1)
  




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