PERLTHRTUT(1) Perl Programmers Reference Guide PERLTHRTUT(1)
NAME
perlthrtut - tutorial on threads in Perl
DESCRIPTION
NOTE: this tutorial describes the new Perl threading flavour introduced in Perl 5.6.0 called inter-preter interpreter
preter 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 ver-sions versions
sions 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" section. If you have "useithreads=define" you have ithreads, if you have
"use5005threads=define" you have 5.005 threads. If you have neither, you don't have any thread sup-port support
port 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
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 appropri-ate appropriate
ate worker thread.
This model is common in GUI and server programs, where a main thread waits for some event and then
passes that event to the appropriate worker threads for processing. Once the event has been passed
on, the boss thread goes back to waiting for another event.
The boss thread does relatively little work. While tasks aren't necessarily performed faster than
with any other method, it tends to have the best user-response times.
Work Crew
In the work crew model, several threads are created that do essentially the same thing to different
pieces of data. It closely mirrors classical parallel processing and vector processors, where a
large array of processors do the exact same thing to many pieces of data.
This model is particularly useful if the system running the program will distribute multiple threads
across different processors. It can also be useful in ray tracing or rendering engines, where the
individual threads can pass on interim results to give the user visual feedback.
Pipeline
The pipeline model divides up a task into a series of steps, and passes the results of one step on to
the thread processing the next. Each thread does one thing to each piece of data and passes the
results to the next thread in line.
This model makes the most sense if you have multiple processors so two or more threads will be exe-cuting executing
cuting in parallel, though it can often make sense in other contexts as well. It tends to keep the
individual tasks small and simple, as well as allowing some parts of the pipeline to block (on I/O or
system calls, for example) while other parts keep going. If you're running different parts of the
pipeline on different processors you may also take advantage of the caches on each processor.
This model is also handy for a form of recursive programming where, rather than having a subroutine
call itself, it instead creates another thread. Prime and Fibonacci generators both map well to this
form of the pipeline model. (A version of a prime number generator is presented later on.)
What kind of threads are Perl threads?
If you have experience with other thread implementations, you might find that things aren't quite
what you expect. It's very important to remember when dealing with Perl threads that Perl Threads
Are Not X Threads, for all values of X. They aren't POSIX threads, or DecThreads, or Java's 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. Possi-bly Possibly
bly both.
This is not to say that Perl threads are completely different from everything that's ever come
before--they're not. Perl's threading model owes a lot to other thread models, especially POSIX.
Just as Perl is not C, though, Perl threads are not POSIX threads. So if you find yourself looking
for mutexes, or thread priorities, it's time to step back a bit and think about what you want to do
and how Perl can do it.
However it is important to remember that Perl threads cannot magically do things unless your operat-ing operating
ing systems threads allows it. So if your system blocks the entire process on sleep(), Perl usually
will as well.
Perl Threads Are Different.
Thread-Safe Modules
The addition of threads has changed Perl's internals substantially. There are implications for people
who write modules with XS code or external libraries. However, since perl data is not shared among
threads by default, Perl modules stand a high chance of being thread-safe or can be made thread-safe
easily. Modules that are not tagged as thread-safe should be tested or code reviewed before being
used in production code.
Not all modules that you might use are thread-safe, and you should always assume a module is unsafe
unless the documentation says otherwise. This includes modules that are distributed as part of the
core. Threads are a new feature, and even some of the standard modules aren't thread-safe.
Even if a module is thread-safe, it doesn't mean that the module is optimized to work well with
threads. A module could possibly be rewritten to utilize the new features in threaded Perl to
increase performance in a threaded environment.
If you're using a module that's not thread-safe for some reason, you can protect yourself by using it
from one, and only one thread at all. If you need multiple threads to access such a module, you can
use semaphores and lots of programming discipline to control access to it. Semaphores are covered in
"Basic semaphores".
See also "Thread-Safety of System Libraries".
Thread Basics
The core 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 pro-gram. program.
gram. After that, we'll go over some of the features of the threads module that make threaded pro-gramming programming
gramming easier.
Basic Thread Support
Thread support is a Perl compile-time option - it's something that's turned on or off when Perl is
built at your site, rather than when your programs are compiled. If your Perl wasn't compiled with
thread support enabled, then any attempt to use threads will fail.
Your programs can use the Config module to check whether threads are enabled. If your program can't
run without them, you can say something like:
$Config{useithreads} or die "Recompile Perl with threads to run this program.";
A possibly-threaded program using a possibly-threaded module might have code like this:
use Config;
use MyMod;
BEGIN {
if ($Config{useithreads}) {
# We have threads
require MyMod_threaded;
import MyMod_threaded;
} else {
require MyMod_unthreaded;
import MyMod_unthreaded;
}
}
Since code that runs both with and without threads is usually pretty messy, it's best to isolate the
thread-specific code in its own module. In our example above, that's what MyMod_threaded is, and
it's only imported if we're running on a threaded Perl.
A Note about the Examples
Although thread support is considered to be stable, there are still a number of quirks that may star-tle startle
tle you when you try out any of the examples below. In a real situation, care should be taken that
all threads are finished executing before the program exits. That care has not been taken in these
examples in the interest of simplicity. Running these examples "as is" will produce error messages,
usually caused by the fact that there are still threads running when the program exits. You should
not be alarmed by this. 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 referenced subroutine. Control then passes both to the subroutine and the caller.
If you need to, your program can pass parameters to the subroutine as part of the thread startup.
Just include the list of parameters as part of the "threads::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.
"create()" is a synonym for "new()".
Waiting For A Thread To Exit
Since threads are also subroutines, they can return values. To wait for a thread to exit and extract
any values it might return, you can use the join() method:
use threads;
$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, 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;
$thr = threads->new(\&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 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 intro-duces introduces
duces a couple of complications to data access that non-threaded programs never need to worry about.
Shared And Unshared Data
The biggest difference between Perl ithreads and the old 5.005 style threading, or for that matter,
to most other threading systems out there, is that by default, no data is shared. When a new perl
thread is created, all the data associated with the current thread is copied to the new thread, and
is subsequently private to that new thread! This is similar in feel to what happens when a UNIX
process forks, except that in this case, the data is just copied to a different part of memory within
the same process rather than a real fork taking place.
To make use of threading however, one usually wants the threads to share at least some data between
themselves. This is done with the threads::shared module and the " : shared" attribute:
use threads;
use threads::shared;
my $foo : shared = 1;
my $bar = 1;
threads->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 pri-vate private
vate variable can't accidentally become shared. A bad assignment will cause the thread to die. For
example:
use threads;
use threads::shared;
my $var = 1;
my $svar : shared = 2;
my %hash : shared;
... create some threads ...
$hash{a} = 1; # all threads see exists($hash{a}) and $hash{a} == 1
$hash{a} = $var # okay - copy-by-value: same effect as previous
$hash{a} = $svar # okay - copy-by-value: same effect as previous
$hash{a} = \$svar # okay - a reference to a shared variable
$hash{a} = \$var # This will die
delete $hash{a} # okay - all threads will see !exists($hash{a})
Note that a shared variable guarantees that if two or more threads try to modify it at the same time,
the internal state of the variable will not become corrupted. However, there are no guarantees beyond
this, as explained in the next section.
Thread Pitfalls: Races
While threads bring a new set of useful tools, they also bring a number of pitfalls. One pitfall is
the race condition:
use threads;
use threads::shared;
my $a : shared = 1;
$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 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 synchroniza-tion, synchronization,
tion, there's no way to be sure that nothing has happened to the shared data between the time you
access it and the time you update it. Even this simple code fragment has the possibility of error:
use threads;
my $a : shared = 2;
my $b : shared;
my $c : shared;
my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });
$thr1->join;
$thr2->join;
Two threads both access $a. Each thread can potentially be interrupted at any point, or be executed
in any order. At the end, $a could be 3 or 4, and both $b and $c could be 2 or 3.
Even "$a += 5" or "$a++" are not guaranteed to be atomic.
Whenever your program accesses data or resources that can be accessed by other threads, you must take
steps to coordinate access or risk data inconsistency and race conditions. Note that Perl will pro-tect protect
tect its internals from your race conditions, but it won't protect you from you.
Synchronization and control
Perl provides a number of mechanisms to coordinate the interactions between themselves and their
data, to avoid race conditions and the like. Some of these are designed to resemble the common tech-niques techniques
niques used in thread libraries such as "pthreads"; others are Perl-specific. Often, the standard
techniques are clumsy and difficult to get right (such as condition waits). Where possible, it is
usually easier to use Perlish techniques such as queues, which remove some of the hard work involved.
Controlling access: lock()
The lock() function takes a shared variable and puts a lock on it. No other thread may lock the
variable until the variable is unlocked by the thread holding the lock. Unlocking happens automati-cally automatically
cally 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
occasionally 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.
You may lock arrays and hashes as well as scalars. Locking an array, though, will not block subse-quent subsequent
quent locks on array elements, just lock attempts on the array itself.
Locks are recursive, which means it's okay for a thread to lock a variable more than once. The lock
will last until the outermost lock() on the variable goes out of scope. For example:
my $x : shared;
doit();
sub doit {
{
{
lock($x); # wait for lock
lock($x); # NOOP - we already have the lock
{
lock($x); # NOOP
{
lock($x); # NOOP
lockit_some_more();
}
}
} # *** implicit unlock here ***
}
}
sub lockit_some_more {
lock($x); # NOOP
} # nothing happens here
Note that there is no unlock() function - the only way to unlock a variable is to allow it to go out
of scope.
A lock can either be used to guard the data contained within the variable being locked, or it can be
used to guard something else, like a section of code. In this latter case, the variable in question
does not hold any useful data, and exists only for the purpose of being locked. In this respect, the
variable behaves like the mutexes and basic semaphores of traditional thread libraries.
A Thread Pitfall: Deadlocks
Locks are a handy tool to synchronize access to data, and using them properly is the key to safe
shared data. Unfortunately, locks aren't without their dangers, especially when multiple locks are
involved. Consider the following code:
use threads;
my $a : shared = 4;
my $b : shared = "foo";
my $thr1 = threads->new(sub {
lock($a);
sleep 20;
lock($b);
});
my $thr2 = threads->new(sub {
lock($b);
sleep 20;
lock($a);
});
This program will probably hang until you kill it. The only way it won't hang is if one of the two
threads acquires both locks first. A guaranteed-to-hang version is more complicated, but the princi-ple principle
ple is the same.
The first thread will grab a lock on $a, then, after a pause during which the second thread has prob-ably probably
ably had time to do some work, try to grab a lock on $b. Meanwhile, the second thread grabs a lock
on $b, then later tries to grab a lock on $a. The second lock attempt for both threads will block,
each waiting for the other to release its lock.
This condition is called a deadlock, and it occurs whenever two or more threads are trying to get
locks on resources that the others own. Each thread will block, waiting for the other to release a
lock on a resource. That never happens, though, since the thread with the resource is itself waiting
for a lock to be released.
There are a number of ways to handle this sort of problem. The best way is to always have all
threads acquire locks in the exact same order. If, for example, you lock variables $a, $b, and $c,
always lock $a before $b, and $b before $c. It's also best to hold on to locks for as short a period
of time to minimize the risks of deadlock.
The other synchronization primitives described below can suffer from similar problems.
Queues: Passing Data Around
A queue is a special thread-safe object that lets you put data in one end and take it out the other
without having to worry about synchronization issues. They're pretty 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 everything pushed on to it.
If a queue is empty, dequeue() blocks until another thread enqueues something. This makes queues
ideal for event loops and other communications between threads.
Semaphores: Synchronizing Data Access
Semaphores are a kind of generic locking mechanism. In their most basic form, they behave very much
like lockable scalars, except that they can't hold data, and that they must be explicitly unlocked.
In their advanced form, they act like a kind of counter, and can allow multiple threads to have the
'lock' at any one time.
Basic semaphores
Semaphores have two methods, down() and up(): down() decrements the resource count, while up incre-ments increments
ments it. Calls to down() will block if the semaphore's current count would decrement below zero.
This program gives a quick demonstration:
use threads;
use Thread::Semaphore;
my $semaphore = 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 simply by passing in different values:
use threads;
use Thread::Semaphore;
my $semaphore = Thread::Semaphore->new(5);
# Creates a semaphore with the counter set to five
$thr1 = threads->new(\&sub1);
$thr2 = threads->new(\&sub1);
sub sub1 {
$semaphore->down(5); # Decrements the counter by five
# Do stuff here
$semaphore->up(5); # Increment the counter by five
}
$thr1->detach;
$thr2->detach;
If down() attempts to decrement the counter below zero, it blocks until the counter is large enough.
Note that while a semaphore can be created with a starting count of zero, any up() or down() always
changes the counter by at least one, and so $semaphore->down(0) is the same as $semaphore->down(1).
The question, of course, is why would you do something like this? Why create a semaphore with a
starting count that's not one, or why decrement/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 them-selves. themselves.
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 may be doing something processor-intensive and want to make sure that the user-interface
thread gets called frequently. Regardless, there are times that you might want a thread to give up
the processor.
Perl's threading package provides the yield() function that does this. yield() is pretty straightfor-ward, straightforward,
ward, and works like this:
use threads;
sub loop {
my $thread = shift;
my $foo = 50;
while($foo--) { print "in thread $thread\n" }
threads->yield;
$foo = 50;
while($foo--) { print "in thread $thread\n" }
}
my $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 hard-ware, hardware,
ware, OS and threading libraries what actually happens. On many operating systems, yed) is a
no-op. Therefore it is important to note that one should not build the scheduling of the threads
around yield() calls. It might work on your platform but it won't work on another platform.
General Thread Utility Routines
We've covered the workhorse parts of Perl's threading package, and with these tools you should be
well on your way to writing threaded code and packages. There are a few useful little pieces that
didn't really fit in anyplace else.
What Thread Am I In?
The "threads->self" class method provides your program with a way to get an object representing the
thread it's currently in. You can use this object in the same way as the ones returned from thread
creation.
Thread IDs
tid() is a thread object method that returns the thread ID of the thread the object represents.
Thread IDs are integers, with the main thread in a program being 0. Currently Perl assigns a unique
tid to every thread ever created in your program, assigning the first thread to be created a tid of
1, and increasing the tid by 1 for each new thread that's created.
Are These Threads The Same?
The equal() method takes two thread objects and returns true if the objects represent the same
thread, and false if they don't.
Thread objects also have an overloaded == comparison so that you can do comparison on them as you
would with normal objects.
What Threads Are Running?
"threads->list" returns a list of thread objects, one for each thread that's currently running and
not detached. Handy for a number of things, including cleaning up at the end of your program:
# 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 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 pro-gram program
gram 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 thread, then the thread must have found a new prime number. In
that case, a new child thread is created for that prime and stuck on the end of the pipeline.
This probably sounds a bit more confusing than it really is, so let's go through this program piece
by piece and see what it does. (For those of you who might be trying to remember exactly what a
prime number is, it's a number that's only evenly divisible by itself and 1)
The bulk of the work is done by the check_num() subroutine, which takes a reference to its input
queue and a prime number that it's responsible for. After pulling in the input queue and the prime
that the subroutine'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 ter-minate terminate
minate (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 operating system viewpoint. There are three basic
categories of threads: user-mode threads, kernel threads, and multiprocessor kernel threads.
User-mode threads are threads that live entirely within a program and its libraries. In this model,
the OS knows nothing about threads. As far as it's concerned, your process is just a process.
This is the easiest way to implement threads, and the way most OSes start. The big disadvantage is
that, since the OS knows nothing about threads, if one thread blocks they all do. Typical blocking
activities include most system calls, most I/O, and things like sleep().
Kernel threads are the next step in thread evolution. The OS knows about kernel threads, and makes
allowances for them. The main difference between a kernel thread and a user-mode thread is blocking.
With kernel threads, things that block a single thread don't block other threads. This is not the
case with user-mode threads, where the kernel blocks at the process level and not the thread level.
This is a big step forward, and can give a threaded program quite a performance boost over non-threaded nonthreaded
threaded programs. Threads that block performing I/O, for example, won't block threads that are
doing other things. Each process still has only one thread running at once, though, regardless of
how many CPUs a system might have.
Since kernel threading can interrupt a thread at any time, they will uncover some of the implicit
locking assumptions you may make in your program. For example, something as simple as "$a = $a + 2"
can behave unpredictably with kernel threads if $a is visible to other threads, as another thread may
have changed $a between the time it was fetched on the right hand side and the time the new value is
stored.
Multiprocessor kernel threads are the final step in thread support. With multiprocessor kernel
threads on a machine with multiple CPUs, the OS may schedule two or more threads to run simultane-ously simultaneously
ously 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 implemen-tation, implementation,
tation, one thread can starve all the others for CPU time if it so chooses.
Preemptive multitasking systems interrupt threads at regular intervals while the system decides which
thread should run next. In a preemptive multitasking system, one thread usually won't monopolize the
CPU.
On some systems, there can be cooperative and preemptive threads running simultaneously. (Threads
running with realtime priorities often behave cooperatively, for example, while threads running at
normal priorities behave preemptively.)
Most modern operating systems support preemptive multitasking nowadays.
Performance considerations
The main thing to bear in mind when comparing ithreads to other threading models is the fact that for
each new thread created, a complete copy of all the variables and data of the parent thread has to be
taken. Thus thread creation can be quite expensive, both in terms of memory usage and time spent in
creation. The ideal way to reduce these costs is to have a relatively short number of long-lived
threads, all created fairly early on - before the base thread has accumulated too much data. Of
course, this may not always be possible, so compromises have to be made. However, after a thread has
been created, its performance and extra memory usage should be little different than ordinary code.
Also note that under the current implementation, shared variables use a little more memory and are a
little slower than ordinary variables.
Process-scope Changes
Note that while threads themselves are separate execution threads and Perl data is thread-private
unless explicitly shared, the threads can affect process-scope state, affecting all the threads.
The most common example of this is changing the current working directory using chdir(). One thread
calls chdir(), and the working directory of all the threads changes.
Even more drastic example of a process-scope change is chroot(): the root directory of all the
threads changes, and no thread can undo it (as opposed to chdir()).
Further examples of process-scope changes include umask() and changing uids/gids.
Thinking of mixing fork() and threads? Please lie down and wait until the feeling passes. Be aware
that the semantics of fork() vary between platforms. For example, some UNIX systems copy all the
current threads into the child process, while others only copy the thread that called fork(). You
have been warned!
Similarly, mixing signals and threads should not be attempted. Implementations are platform-depen-dent, platform-dependent,
dent, 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}*(), read-dir(), readdir(),
dir(), rand(), and srand() -- in general, calls that depend on some global external state.
If the system Perl is compiled in has thread-safe variants of such calls, they will be used. Beyond
that, Perl is at the mercy of the thread-safety or -unsafety of the calls. Please consult your C
library call documentation.
On some platforms the thread-safe library interfaces may fail if the result buffer is too small (for
example the user group databases may be rather large, and the reentrant interfaces may have to carry
around a full snapshot of those databases). Perl will start with a small buffer, but keep retrying
and growing the result buffer until the result fits. If this limitless growing sounds bad for secu-rity security
rity or memory consumption reasons you can recompile Perl with PERL_REENTRANT_MAXSIZE defined to the
maximum number of bytes you will allow.
Conclusion
A complete thread tutorial could fill a book (and has, many times), but with what we've covered in
this introduction, you should be well on your way to becoming a threaded Perl expert.
Bibliography
Here's a short bibliography courtesy of Jrgen Christoffel:
Introductory Texts
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 Programming: A Guide to Concurrency, Communica-
tion, 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 & As-
sociates, 1996, ISBN 156592-115-1 (covers POSIX threads).
OS-Related References
Boykin, Joseph, David Kirschen, Alan Langerman, and Susan LoVerso. Programming under Mach. Addi-
son-Wesley, 1994, ISBN 0-201-52739-1.
Tanenbaum, Andrew S. Distributed Operating Systems. Prentice Hall, 1995, ISBN 0-13-219908-4 (great
textbook).
Silberschatz, Abraham, and Peter B. Galvin. Operating System Concepts, 4th ed. Addison-Wesley, 1995,
ISBN 0-201-59292-4
Other References
Arnold, Ken and James Gosling. The Java Programming Language, 2nd ed. Addison-Wesley, 1998, ISBN
0-201-31006-6.
comp.programming.threads FAQ, <http://www.serpentine.com/~bos/threads-faq/
Le Sergent, T. and B. Berthomieu. "Incremental MultiThreaded Garbage Collection on Virtually Shared
Memory Architectures" in Memory Management: Proc. of the International Workshop IWMM 92, St. Malo,
France, September 1992, Yves Bekkers and Jacques Cohen, eds. Springer, 1992, ISBN 3540-55940-X
(real-life thread applications).
Artur Bergman, "Where Wizards Fear To Tread", June 11, 2002,
<http://www.perl.com/pub/a/2002/06/11/threads.html
Acknowledgements
Thanks (in no particular order) to Chaim Frenkel, Steve Fink, Gurusamy Sarathy, Ilya Zakharevich,
Benjamin Sugars, Jrgen Christoffel, Joshua Pritikin, and Alan Burlison, for their help in reality-checking realitychecking
checking and polishing this article. Big thanks to Tom Christiansen for his rewrite of the prime
number generator.
AUTHOR
Dan Sugalski <dan@sidhe.org<gt>
Slightly modified by Arthur Bergman to fit the new thread model/module.
Reworked slightly by Jrg Walter <jwalt@cpan.org<gt> to be more concise about thread-safety of perl
code.
Rearranged slightly by Elizabeth Mattijsen <liz@dijkmat.nl<gt> to put less emphasis on yield().
Copyrights
The original version of this article originally appeared in The Perl Journal #10, and is copyright
1998 The Perl Journal. It appears courtesy of Jon Orwant and The Perl Journal. This document may be
distributed under the same terms as Perl itself.
For more information please see threads and threads::shared.
perl v5.8.8 2006-01-07 PERLTHRTUT(1)
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