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authormarkm <markm@FreeBSD.org>1999-05-02 14:33:17 +0000
committermarkm <markm@FreeBSD.org>1999-05-02 14:33:17 +0000
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treeb4adabf341898a4378f4b7f8c7fb65f3f7c77769 /contrib/perl5/pod/perlthrtut.pod
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Maintenance releace 3 of perl5.005. Includes support for threads.
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+=head1 NAME
+
+perlthrtut - tutorial on threads in Perl
+
+=head1 DESCRIPTION
+
+One of the most prominent new features of Perl 5.005 is the inclusion
+of threads. Threads make a number of things a lot easier, and are a
+very useful addition to your bag of programming tricks.
+
+=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 5.005, 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 = $a + 2> can behave
+unpredictably with kernel threads if C<$a> is visible to other
+threads, as another thread may have changed C<$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.
+
+=head1 Threadsafe Modules
+
+The addition of threads has changed Perl's internals
+substantially. There are implications for people who write
+modules--especially modules with XS code or external libraries. While
+most modules won't encounter any problems, modules that aren't
+explicitly tagged as thread-safe should be tested 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 beta feature, and even some of the standard
+modules aren't thread-safe.
+
+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 Thread 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 Thread 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:
+
+ $Config{usethreads} or die "Recompile Perl with threads to run this program.";
+
+A possibly-threaded program using a possibly-threaded module might
+have code like this:
+
+ use Config;
+ use MyMod;
+
+ if ($Config{usethreads}) {
+ # 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 Thread package provides the tools you need to create new
+threads. Like any other module, you need to tell Perl you want to use
+it; use Thread imports all the pieces you need to create basic
+threads.
+
+The simplest, straightforward way to create a thread is with new():
+
+ use Thread;
+
+ $thr = new Thread \&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<Thread::new> call, like this:
+
+ use Thread;
+ $Param3 = "foo";
+ $thr = new Thread \&sub1, "Param 1", "Param 2", $Param3;
+ $thr = new Thread \&sub1, @ParamList;
+ $thr = new Thread \&sub1, qw(Param1 Param2 $Param3);
+
+ sub sub1 {
+ my @InboundParameters = @_;
+ print "In the thread\n";
+ print "got parameters >", join("<>", @InboundParameters), "<\n";
+ }
+
+
+The subroutine runs like a normal Perl subroutine, and the call to new
+Thread returns whatever the subroutine returns.
+
+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.
+
+The other way to spawn a new thread is with async(), which is a way to
+spin off a chunk of code like eval(), but into its own thread:
+
+ use Thread qw(async);
+
+ $LineCount = 0;
+
+ $thr = async {
+ while(<>) {$LineCount++}
+ print "Got $LineCount lines\n";
+ };
+
+ print "Waiting for the linecount to end\n";
+ $thr->join;
+ print "All done\n";
+
+You'll notice we did a use Thread qw(async) in that example. async is
+not exported by default, so if you want it, you'll either need to
+import it before you use it or fully qualify it as
+Thread::async. You'll also note that there's a semicolon after the
+closing brace. That's because async() treats the following block as an
+anonymous subroutine, so the semicolon is necessary.
+
+Like eval(), the code executes in the same context as it would if it
+weren't spun off. Since both the code inside and after the async start
+executing, you need to be careful with any shared resources. Locking
+and other synchronization techniques are covered later.
+
+=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 Thread qw(yield async);
+ async {
+ my $foo = 50;
+ while ($foo--) { print "first async\n" }
+ yield;
+ $foo = 50;
+ while ($foo--) { print "first async\n" }
+ };
+ async {
+ my $foo = 50;
+ while ($foo--) { print "second async\n" }
+ yield;
+ $foo = 50;
+ while ($foo--) { print "second async\n" }
+ };
+
+=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 Thread;
+ $thr = new Thread \&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 Errors In Threads
+
+So what happens when an error occurs in a thread? Any errors that
+could be caught with eval() are postponed until the thread is
+joined. If your program never joins, the errors appear when your
+program exits.
+
+Errors deferred until a join() can be caught with eval():
+
+ use Thread qw(async);
+ $thr = async {$b = 3/0}; # Divide by zero error
+ $foo = eval {$thr->join};
+ if ($@) {
+ print "died with error $@\n";
+ } else {
+ print "Hey, why aren't you dead?\n";
+ }
+
+eval() passes any results from the joined thread back unmodified, so
+if you want the return value of the thread, this is your only chance
+to get them.
+
+=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 Thread;
+ $thr = new Thread \&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 single most important thing to remember when using threads is that
+all threads potentially have access to all the data anywhere in your
+program. While this is true with a nonthreaded Perl program as well,
+it's especially important to remember with a threaded program, since
+more than one thread can be accessing this data at once.
+
+Perl's scoping rules don't change because you're using threads. If a
+subroutine (or block, in the case of async()) could see a variable if
+you weren't running with threads, it can see it if you are. This is
+especially important for the subroutines that create, and makes my
+variables even more important. Remember--if your variables aren't
+lexically scoped (declared with C<my>) you're probably sharing it between
+threads.
+
+=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 Thread;
+ $a = 1;
+ $thr1 = Thread->new(\&sub1);
+ $thr2 = Thread->new(\&sub2);
+
+ sleep 10;
+ print "$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 Thread qw(async);
+ $a = 2;
+ async{ $b = $a; $a = $b + 1; };
+ async{ $c = $a; $a = $c + 1; };
+
+Two threads both access $a. Each thread can potentially be interrupted
+at any point, or be executed in any order. At the end, $a could be 3
+or 4, and both $b and $c could be 2 or 3.
+
+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 variable (or subroutine, but we'll get to
+that later) 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 Thread qw(async);
+ $a = 4;
+ $thr1 = async {
+ $foo = 12;
+ {
+ lock ($a); # Block until we get access to $a
+ $b = $a;
+ $a = $b * $foo;
+ }
+ print "\$foo was $foo\n";
+ };
+ $thr2 = async {
+ $bar = 7;
+ {
+ lock ($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. Locked subroutines behave differently,
+however. We'll cover that later in the article.
+
+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 Thread qw(async yield);
+ $a = 4;
+ $b = "foo";
+ async {
+ lock($a);
+ yield;
+ sleep 20;
+ lock ($b);
+ };
+ async {
+ lock($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 Thread qw(async);
+ use Thread::Queue;
+
+ my $DataQueue = new Thread::Queue;
+ $thr = async {
+ while ($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);
+
+You create the queue with new Thread::Queue. Then you can add lists of
+scalars onto the end with enqueue(), and pop scalars off the front of
+it with dequeue(). A queue has no fixed size, and can grow as needed
+to hold everything pushed on to it.
+
+If a queue is empty, dequeue() blocks until another thread enqueues
+something. This makes queues ideal for event loops and other
+communications between threads.
+
+=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 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 Thread qw(yield);
+ use Thread::Semaphore;
+ my $semaphore = new Thread::Semaphore;
+ $GlobalVariable = 0;
+
+ $thr1 = new Thread \&sample_sub, 1;
+ $thr2 = new Thread \&sample_sub, 2;
+ $thr3 = new Thread \&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";
+ yield;
+ sleep 2;
+ $LocalCopy++;
+ $GlobalVariable = $LocalCopy;
+ $semaphore->up;
+ }
+ }
+
+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 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. 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).
+
+The question, of course, is why would you do something like this? Why
+create a semaphore with a starting count that's not one, or why
+decrement/increment it by more than one? The answer is resource
+availability. Many resources that you want to manage access for can be
+safely used by more than one thread at once.
+
+For example, let's take a GUI driven program. It has a semaphore that
+it uses to synchronize access to the display, so only one thread is
+ever drawing at once. Handy, but of course you don't want any thread
+to start drawing until things are properly set up. In this case, you
+can create a semaphore with a counter set to zero, and up it when
+things are ready for drawing.
+
+Semaphores with counters greater than one are also useful for
+establishing quotas. Say, for example, that you have a number of
+threads that can do I/O at once. You don't want all the threads
+reading or writing at once though, since that can potentially swamp
+your I/O channels, or deplete your process' quota of filehandles. You
+can use a semaphore initialized to the number of concurrent I/O
+requests (or open files) that you want at any one time, and have your
+threads quietly block and unblock themselves.
+
+Larger increments or decrements are handy in those cases where a
+thread needs to check out or return a number of resources at once.
+
+=back
+
+=head2 Attributes: Restricting Access To Subroutines
+
+In addition to synchronizing access to data or resources, you might
+find it useful to synchronize access to subroutines. You may be
+accessing a singular machine resource (perhaps a vector processor), or
+find it easier to serialize calls to a particular subroutine than to
+have a set of locks and sempahores.
+
+One of the additions to Perl 5.005 is subroutine attributes. The
+Thread package uses these to provide several flavors of
+serialization. It's important to remember that these attributes are
+used in the compilation phase of your program so you can't change a
+subroutine's behavior while your program is actually running.
+
+=head2 Subroutine Locks
+
+The basic subroutine lock looks like this:
+
+ sub test_sub {
+ use attrs qw(locked);
+ }
+
+This ensures that only one thread will be executing this subroutine at
+any one time. Once a thread calls this subroutine, any other thread
+that calls it will block until the thread in the subroutine exits
+it. A more elaborate example looks like this:
+
+ use Thread qw(yield);
+
+ new Thread \&thread_sub, 1;
+ new Thread \&thread_sub, 2;
+ new Thread \&thread_sub, 3;
+ new Thread \&thread_sub, 4;
+
+ sub sync_sub {
+ use attrs qw(locked);
+ my $CallingThread = shift @_;
+ print "In sync_sub for thread $CallingThread\n";
+ yield;
+ sleep 3;
+ print "Leaving sync_sub for thread $CallingThread\n";
+ }
+
+ sub thread_sub {
+ my $ThreadID = shift @_;
+ print "Thread $ThreadID calling sync_sub\n";
+ sync_sub($ThreadID);
+ print "$ThreadID is done with sync_sub\n";
+ }
+
+The use attrs qw(locked) locks sync_sub(), and if you run this, you
+can see that only one thread is in it at any one time.
+
+=head2 Methods
+
+Locking an entire subroutine can sometimes be overkill, especially
+when dealing with Perl objects. When calling a method for an object,
+for example, you want to serialize calls to a method, so that only one
+thread will be in the subroutine for a particular object, but threads
+calling that subroutine for a different object aren't blocked. The
+method attribute indicates whether the subroutine is really a method.
+
+ use Thread;
+
+ sub tester {
+ my $thrnum = shift @_;
+ my $bar = new Foo;
+ foreach (1..10) {
+ print "$thrnum calling per_object\n";
+ $bar->per_object($thrnum);
+ print "$thrnum out of per_object\n";
+ yield;
+ print "$thrnum calling one_at_a_time\n";
+ $bar->one_at_a_time($thrnum);
+ print "$thrnum out of one_at_a_time\n";
+ yield;
+ }
+ }
+
+ foreach my $thrnum (1..10) {
+ new Thread \&tester, $thrnum;
+ }
+
+ package Foo;
+ sub new {
+ my $class = shift @_;
+ return bless [@_], $class;
+ }
+
+ sub per_object {
+ use attrs qw(locked method);
+ my ($class, $thrnum) = @_;
+ print "In per_object for thread $thrnum\n";
+ yield;
+ sleep 2;
+ print "Exiting per_object for thread $thrnum\n";
+ }
+
+ sub one_at_a_time {
+ use attrs qw(locked);
+ my ($class, $thrnum) = @_;
+ print "In one_at_a_time for thread $thrnum\n";
+ yield;
+ sleep 2;
+ print "Exiting one_at_a_time for thread $thrnum\n";
+ }
+
+As you can see from the output (omitted for brevity; it's 800 lines)
+all the threads can be in per_object() simultaneously, but only one
+thread is ever in one_at_a_time() at once.
+
+=head2 Locking A Subroutine
+
+You can lock a subroutine as you would lock a variable. Subroutine
+locks work the same as a C<use attrs qw(locked)> in the subroutine,
+and block all access to the subroutine for other threads until the
+lock goes out of scope. When the subroutine isn't locked, any number
+of threads can be in it at once, and getting a lock on a subroutine
+doesn't affect threads already in the subroutine. Getting a lock on a
+subroutine looks like this:
+
+ lock(\&sub_to_lock);
+
+Simple enough. Unlike use attrs, which is a compile time option,
+locking and unlocking a subroutine can be done at runtime at your
+discretion. There is some runtime penalty to using lock(\&sub) instead
+of use attrs qw(locked), so make sure you're choosing the proper
+method to do the locking.
+
+You'd choose lock(\&sub) when writing modules and code to run on both
+threaded and unthreaded Perl, especially for code that will run on
+5.004 or earlier Perls. In that case, it's useful to have subroutines
+that should be serialized lock themselves if they're running threaded,
+like so:
+
+ package Foo;
+ use Config;
+ $Running_Threaded = 0;
+
+ BEGIN { $Running_Threaded = $Config{'usethreads'} }
+
+ sub sub1 { lock(\&sub1) if $Running_Threaded }
+
+
+This way you can ensure single-threadedness regardless of which
+version of Perl you're running.
+
+=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 Thread->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.
+
+=head2 What Threads Are Running?
+
+Thread->list returns a list of thread objects, one for each thread
+that's currently running. Handy for a number of things, including
+cleaning up at the end of your program:
+
+ # Loop through all the threads
+ foreach $thr (Thread->list) {
+ # Don't join the main thread or ourselves
+ if ($thr->tid && !Thread::equal($thr, Thread->self)) {
+ $thr->join;
+ }
+ }
+
+The example above is just for illustration. It isn't strictly
+necessary to join all the threads you create, since Perl detaches all
+the threads before it exits.
+
+=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 Thread;
+ 7 use Thread::Queue;
+ 8
+ 9 my $stream = new Thread::Queue;
+ 10 my $kid = new Thread(\&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 Thread(\&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 documention 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 0-13-143934-0 (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>
+
+=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.
+
+
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