If you have neither, you don't have any thread support built in.
If you have both, you are in trouble.
-This document is unfortunately rather sparse as of 2001-Sep-17.
-In the meanwhile, you can read up on threading basics (while keeping
-in mind the above caveat about the changing threading flavours) in
-L<perlothrtut>
+=head1 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.
+
+=head1 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.
+
+=head2 Boss/Worker
+
+The boss/worker model usually has one `boss' thread and one or more
+`worker' threads. The boss thread gathers or generates tasks that need
+to be done, then parcels those tasks out to the appropriate worker
+thread.
+
+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.
+
+=head2 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.
+
+=head2 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.)
+
+=head1 Native threads
+
+There are several different ways to implement threads on a system. How
+threads are implemented depends both on the vendor and, in some cases,
+the version of the operating system. Often the first implementation
+will be relatively simple, but later versions of the OS will be more
+sophisticated.
+
+While the information in this section is useful, it's not necessary,
+so you can skip it if you don't feel up to it.
+
+There are three basic categories of threads-user-mode threads, kernel
+threads, and multiprocessor kernel threads.
+
+User-mode threads are threads that live entirely within a program and
+its libraries. In this model, the OS knows nothing about threads. As
+far as it's concerned, your process is just a process.
+
+This is the easiest way to implement threads, and the way most OSes
+start. The big disadvantage is that, since the OS knows nothing about
+threads, if one thread blocks they all do. Typical blocking activities
+include most system calls, most I/O, and things like sleep().
+
+Kernel threads are the next step in thread evolution. The OS knows
+about kernel threads, and makes allowances for them. The main
+difference between a kernel thread and a user-mode thread is
+blocking. With kernel threads, things that block a single thread don't
+block other threads. This is not the case with user-mode threads,
+where the kernel blocks at the process level and not the thread level.
+
+This is a big step forward, and can give a threaded program quite a
+performance boost over non-threaded programs. Threads that block
+performing I/O, for example, won't block threads that are doing other
+things. Each process still has only one thread running at once,
+though, regardless of how many CPUs a system might have.
+
+Since kernel threading can interrupt a thread at any time, they will
+uncover some of the implicit locking assumptions you may make in your
+program. For example, something as simple as C<$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.
+
+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.)
+
+=head1 What kind of threads are perl threads?
+
+If you have experience with other thread implementations, you might
+find that things aren't quite what you expect. It's very important to
+remember when dealing with Perl threads that Perl Threads Are Not X
+Threads, for all values of X. They aren't POSIX threads, or
+DecThreads, or Java's Green threads, or Win32 threads. There are
+similarities, and the broad concepts are the same, but if you start
+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 remeber that perl threads cannot magicly
+do things unless your operating systems threads allows it. So if your
+system blocks the entire process on sleep(), so will usually perl aswell.
+
+=head1 Threadsafe 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 the threads
+do not share data pure perl modules that don't interact with external
+systems should be safe. 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. (*** I think ActiveState checked this for
+psuedofork, check with GSAR)
+
+Even if a module us threadsafe, it doesn't mean that the module is optimized
+to work well with threads. A module could maybe be rewritten to utilize the new
+features in perl threaded to increase performance in a threaded enviroment.
+
+If you're using a module that's not thread-safe for some reason, you
+can protect yourself by using semaphores and lots of programming
+discipline to control access to the module. Semaphores are covered
+later in the article. Perl Threads Are Different
+
+=head1 Thread Basics
+
+The core L<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 L<threads> module that
+make threaded programming easier.
+
+=head2 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.
+
+Remember that the threading support in 5.005 is in beta release, and
+should be treated as such. You should expect that it may not function
+entirely properly, and the thread interface may well change some
+before it is a fully supported, production release. The beta version
+shouldn't be used for mission-critical projects. Having said that,
+threaded Perl is pretty nifty, and worth a look. (??)
+
+Your programs can use the Config module to check whether threads are
+enabled. If your program can't run without them, you can say something
+like:
+
+ $Config{useithreads} or die "Recompile Perl with threads to run this program.";
+
+A possibly-threaded program using a possibly-threaded module might
+have code like this:
+
+ use Config;
+ use MyMod;
+
+ if ($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.
+
+=head2 Creating Threads
+
+The L<threads> package provides the tools you need to create new
+threads. Like any other module, you need to tell Perl you want to use
+it; C<use threads> imports all the pieces you need to create basic
+threads.
+
+The simplest, 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 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 C<threads::new> call, like this:
+
+ use threads;
+ $Param3 = "foo";
+ $thr = threads->new(\&sub1, "Param 1", "Param 2", $Param3);
+ $thr = threads->new(\&sub1, @ParamList);
+ $thr = threads->new(\&sub1, qw(Param1 Param2 $Param3));
+
+ 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.
+
+=head2 Giving up control
+
+There are times when you may find it useful to have a thread
+explicitly give up the CPU to another thread. Your threading package
+might not support preemptive multitasking for threads, for example, or
+you may be doing something compute-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--) {Êprint "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.
+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.
+
+=head2 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 scalars it might return, you can
+use the join() method.
+
+ use threads;
+ $thr = threads->new(\&sub1);
+
+ @ReturnData = $thr->join;
+ print "Thread returned @ReturnData";
+
+ sub sub1 { return "Fifty-six", "foo", 2; }
+
+In the example above, the join() method returns as soon as the thread
+ends. In addition to waiting for a thread to finish and gathering up
+any values that the thread might have returned, join() also performs
+any OS cleanup necessary for the thread. That cleanup might be
+important, especially for long-running programs that spawn lots of
+threads. If you don't want the return values and don't want to wait
+for the thread to finish, you should call the detach() method
+instead. detach() is covered later in the article.
+
+=head2 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;
+ $thr = new threads \&sub1; # Spawn the thread
+
+ $thr->detach; # Now we officially don't care any more
+
+ 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 output that
+it might have produced (if it was done and waiting for a join) is
+lost.
+
+=head1 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.
+
+=head2 Shared And Unshared Data
+
+The biggest difference between perl threading and the old 5.005 style
+threading, or most other threading systems out there, is that all data
+is not shared. When a new perl thread is created all data is cloned
+and is private to that thread!
+
+To make use of threading however, one usually want the threads to share
+data between each other, that is used with the L<threads::shared> module
+and the C< : 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
+
+=head2 Thread Pitfall: 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;
+ $thr1 = threads->new(\&sub1);
+ $thr2 = threads->new(\&sub2);
+
+ $thr1->join;
+ $thr2->join;
+ print "$a\n";
+
+ sub sub1 { $foo = $a; $a = $foo + 1; }
+ sub sub2 { $bar = $a; $a = $bar + 1; }
+
+What do you think $a will be? The answer, unfortunately, is "it
+depends." Both sub1() and sub2() access the global variable $a, once
+to read and once to write. Depending on factors ranging from your
+thread implementation's scheduling algorithm to the phase of the moon,
+$a can be 2 or 3.
+
+Race conditions are caused by unsynchronized access to shared
+data. Without explicit synchronization, there's no way to be sure that
+nothing has happened to the shared data between the time you access it
+and the time you update it. Even this simple code fragment has the
+possibility of error:
+
+ use threads;
+ my $a : shared = 2;
+ my $b : shared;
+ my $c : shared;
+ my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
+ my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });
+ $thr1->join();
+ $thr2->join();
+
+Two threads both access $a. Each thread can potentially be interrupted
+at any point, or be executed in any order. At the end, $a could be 3
+or 4, and both $b and $c could be 2 or 3.
+
+Whenever your program accesses data or resources that can be accessed
+by other threads, you must take steps to coordinate access or risk
+data corruption and race conditions.
+
+=head2 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 locking thread exits
+the innermost block containing the lock.
+Using lock() is straightforward:
+
+ use threads;
+ my $a : shared = 4;
+ $thr1 = threads->new(sub {
+ $foo = 12;
+ {
+ lock ($a); # Block until we get access to $a
+ $b = $a;
+ $a = $b * $foo;
+ }
+ print "\$foo was $foo\n";
+ });
+ $thr2 = threads->new(sub {
+ $bar = 7;
+ {
+ lock ($a); # Block until we can get access to $a
+ $c = $a;
+ $a = $c * $bar;
+ }
+ print "\$bar was $bar\n";
+ });
+ $thr1->join;
+ $thr2->join;
+ print "\$a is $a\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 innermost 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.
+
+Finally, 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.
+
+=head2 Thread Pitfall: Deadlocks
+
+Locks are a handy tool to synchronize access to data. Using them
+properly is the key to safe shared data. Unfortunately, locks aren't
+without their dangers. Consider the following code:
+
+ use threads;
+ my $a : shared = 4;
+ my $b : shared = "foo";
+ my $thr1 = threads->new(sub {
+ lock($a);
+ yield;
+ sleep 20;
+ lock ($b);
+ });
+ my $thr2 = threads->new(sub {
+ lock($b);
+ yield;
+ 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 async() routines acquires both locks
+first. A guaranteed-to-hang version is more complicated, but the
+principle is the same.
+
+The first thread spawned by async() will grab a lock on $a then, a
+second or two later, try to grab a lock on $b. Meanwhile, the second
+thread grabs a lock on $b, then later tries to grab a lock on $a. The
+second lock attempt for both threads will block, each waiting for the
+other to release its lock.
+
+This condition is called a deadlock, and it occurs whenever two or
+more threads are trying to get locks on resources that the others
+own. Each thread will block, waiting for the other to release a lock
+on a resource. That never happens, though, since the thread with the
+resource is itself waiting for a lock to be released.
+
+There are a number of ways to handle this sort of problem. The best
+way is to always have all threads acquire locks in the exact same
+order. If, for example, you lock variables $a, $b, and $c, always lock
+$a before $b, and $b before $c. It's also best to hold on to locks for
+as short a period of time to minimize the risks of deadlock.
+
+=head2 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 threads::shared::queue;
+
+ my $DataQueue = new threads::shared::queue;
+ $thr = threads->new(sub {
+ while ($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 threads::shared::queue. Then you can add lists of
+scalars onto the end with enqueue(), and pop scalars off the front of
+it with dequeue(). A queue has no fixed size, and can grow as needed
+to hold everything pushed on to it.
+
+If a queue is empty, dequeue() blocks until another thread enqueues
+something. This makes queues ideal for event loops and other
+communications between threads.
+
+
+=head1 Threads And Code
+
+In addition to providing thread-safe access to data via locks and
+queues, threaded Perl also provides general-purpose semaphores for
+coarser synchronization than locks provide and thread-safe access to
+entire subroutines.
+
+=head2 Semaphores: Synchronizing Data Access
+
+Semaphores are a kind of generic locking mechanism. Unlike lock, which
+gets a lock on a particular scalar, Perl doesn't associate any
+particular thing with a semaphore so you can use them to control
+access to anything you like. In addition, semaphores can allow more
+than one thread to access a resource at once, though by default
+semaphores only allow one thread access at a time.
=over 4
-=item *
+=item Basic semaphores
+
+Semaphores have two methods, down and up. down decrements the resource
+count, while up increments it. down calls will block if the
+semaphore's current count would decrement below zero. This program
+gives a quick demonstration:
+
+ use threads qw(yield);
+ use threads::shared::semaphore;
+ my $semaphore = new threads::shared::semaphore;
+ $GlobalVariable = 0;
-L<perlothrtut/What Is A Thread Anyway?>
+ $thr1 = new threads \&sample_sub, 1;
+ $thr2 = new threads \&sample_sub, 2;
+ $thr3 = new threads \&sample_sub, 3;
-=item *
+ 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";
+ yield;
+ sleep 2;
+ $LocalCopy++;
+ $GlobalVariable = $LocalCopy;
+ $semaphore->up;
+ }
+ }
+
+ $thr1->join();
+ $thr2->join();
+ $thr3->join();
-L<perlothrtut/Threaded Program Models>
+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.
-=item *
+=item Advanced Semaphores
-L<perlothrtut/Native threads>
+By default, semaphores behave like locks, letting only one thread
+down() them at a time. However, there are other uses for semaphores.
-=item *
+Each semaphore has a counter attached to it. down() decrements the
+counter and up() increments the counter. By default, semaphores are
+created with the counter set to one, down() decrements by one, and
+up() increments by one. 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. $semaphore->down(0) is the same as $semaphore->down(1).
-L<perlothrtut/What kind of threads are perl threads?>
+The question, of course, is why would you do something like this? Why
+create a semaphore with a starting count that's not one, or why
+decrement/increment it by more than one? The answer is resource
+availability. Many resources that you want to manage access for can be
+safely used by more than one thread at once.
+For example, let's take a GUI driven program. It has a semaphore that
+it uses to synchronize access to the display, so only one thread is
+ever drawing at once. Handy, but of course you don't want any thread
+to start drawing until things are properly set up. In this case, you
+can create a semaphore with a counter set to zero, and up it when
+things are ready for drawing.
-=item *
+Semaphores with counters greater than one are also useful for
+establishing quotas. Say, for example, that you have a number of
+threads that can do I/O at once. You don't want all the threads
+reading or writing at once though, since that can potentially swamp
+your I/O channels, or deplete your process' quota of filehandles. You
+can use a semaphore initialized to the number of concurrent I/O
+requests (or open files) that you want at any one time, and have your
+threads quietly block and unblock themselves.
-L<perlothrtut/Threadsafe Modules>
+Larger increments or decrements are handy in those cases where a
+thread needs to check out or return a number of resources at once.
=back
-When C<perlothrut> reaches L<perlothrtut/Thread Basics> is when
-you should slow down and remember to mentally read C<threads>
-when C<perlothrtut> says C<Thread>. The C<Thread> was the old
-5.005-style threading module, the C<threads> is the new ithreads
-style threading module.
+=head1 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.
+
+=head2 What Thread Am I In?
+
+The threads->self 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 the thread creation.
+
+=head2 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.
+
+=head2 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.
+
+=head2 What Threads Are Running?
+
+threads->list returns a list of thread objects, one for each thread
+that's currently running and not detached. Handy for a number of things,
+including cleaning up at the end of your program:
+
+ # Loop through all the threads
+ foreach $thr (threads->list) {
+ # Don't join the main thread or ourselves
+ if ($thr->tid && !threads::equal($thr, threads->self)) {
+ $thr->join;
+ }
+ }
+
+If not all threads are 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 runninng
+
+=head1 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 threads::shared::queue;
+ 8
+ 9 my $stream = new threads::shared::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 threads::shared::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
+that it funnels numbers that have failed the check into. 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 lets
+go through this program piece by piece and see what it does. (For
+those of you who might be trying to remember exactly what a prime
+number is, it's a number that's only evenly divisible by itself and 1)
+
+The bulk of the work is done by the check_num() subroutine, which
+takes a reference to its input queue and a prime number that it's
+responsible for. After pulling in the input queue and the prime that
+the subroutine's checking (line 20), we create a new queue (line 22)
+and reserve a scalar for the thread that we're likely to create later
+(line 21).
+
+The while loop from lines 23 to line 31 grabs a scalar off the input
+queue and checks against the prime this thread is responsible
+for. Line 24 checks to see if there's a remainder when we modulo the
+number to be checked against our prime. If there is one, the number
+must not be evenly divisible by our prime, so we need to either pass
+it on to the next thread if we've created one (line 26) or create a
+new thread if we haven't.
+
+The new thread creation is line 29. We pass on to it a reference to
+the queue we've created, and the prime number we've found.
+
+Finally, once the loop terminates (because we got a 0 or undef in the
+queue, which serves as a note to die), we pass on the notice to our
+child and wait for it to exit if we've created a child (Lines 32 and
+37).
+
+Meanwhile, back in the main thread, we create a queue (line 9) and the
+initial child thread (line 10), and pre-seed it with the first prime:
+2. Then we queue all the numbers from 3 to 1000 for checking (lines
+12-14), then queue a die notice (line 16) and wait for the first child
+thread to 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.
+
+=head1 Conclusion
+
+A complete thread tutorial could fill a book (and has, many times),
+but this should get you well on your way. The final authority on how
+Perl's threads behave is the documentation bundled with the Perl
+distribution, but with what we've covered in this article, you should
+be well on your way to becoming a threaded Perl expert.
+
+=head1 Bibliography
+
+Here's a short bibliography courtesy of Jürgen Christoffel:
+
+=head2 Introductory Texts
+
+Birrell, Andrew D. An Introduction to Programming with
+Threads. Digital Equipment Corporation, 1989, DEC-SRC Research Report
+#35 online as
+http://www.research.digital.com/SRC/staff/birrell/bib.html (highly
+recommended)
+
+Robbins, Kay. A., and Steven Robbins. Practical Unix Programming: A
+Guide to Concurrency, Communication, and
+Multithreading. Prentice-Hall, 1996.
+
+Lewis, Bill, and Daniel J. Berg. Multithreaded Programming with
+Pthreads. Prentice Hall, 1997, ISBN 0-13-443698-9 (a well-written
+introduction to threads).
+
+Nelson, Greg (editor). Systems Programming with Modula-3. Prentice
+Hall, 1991, ISBN 0-13-590464-1.
+
+Nichols, Bradford, Dick Buttlar, and Jacqueline Proulx Farrell.
+Pthreads Programming. O'Reilly & Associates, 1996, ISBN 156592-115-1
+(covers POSIX threads).
+
+=head2 OS-Related References
+
+Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
+LoVerso. Programming under Mach. Addison-Wesley, 1994, ISBN
+0-201-52739-1.
+
+Tanenbaum, Andrew S. Distributed Operating Systems. Prentice Hall,
+1995, ISBN 0-13-219908-4 (great textbook).
+
+Silberschatz, Abraham, and Peter B. Galvin. Operating System Concepts,
+4th ed. Addison-Wesley, 1995, ISBN 0-201-59292-4
+
+=head2 Other References
+
+Arnold, Ken and James Gosling. The Java Programming Language, 2nd
+ed. Addison-Wesley, 1998, ISBN 0-201-31006-6.
+
+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).
+
+=head1 Acknowledgements
+
+Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy
+Sarathy, Ilya Zakharevich, Benjamin Sugars, Jürgen 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.
+
+=head1 AUTHOR
+
+Dan Sugalski E<lt>sugalskd@ous.eduE<gt>
+
+Slightly modified by Arthur Bergman to fit the new thread model/module.
+
+=head1 Copyrights
+
+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 L<threads> and L<threads::shared>.
projects / p5sagit/p5-mst-13.2.git / blobdiff