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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 interpreter
threads, or ithreads for short. In this model each thread
runs in its own Perl interpreter, and any data sharing
between threads must be explicit.
There is another older Perl threading flavour called the
5.005 model, unsurprisingly for 5.005 versions of Perl.
The old model is known to have problems, deprecated, and
will probably be removed around release 5.10. You are
strongly encouraged to migrate any existing 5.005 threads
code to the new model as soon as possible.
You can see which (or neither) threading flavour you have
by running "perl -V" and looking at the "Platform" sec-
tion. If you have "useithreads=define" you have ithreads,
if you have "use5005threads=define" you have 5.005
threads. If you have neither, you don't have any thread
support built in. If you have both, you are in trouble.
The user-level interface to the 5.005 threads was via the
Threads class, while ithreads uses the threads class. Note
the change in case.
Status
The ithreads code has been available since Perl 5.6.0, and
is considered stable. The user-level interface to ithreads
(the threads classes) appeared in the 5.8.0 release, and
as of this time is considered stable although it should be
treated with caution as with all new features.
What Is A Thread Anyway?
A thread is a flow of control through a program with a
single execution point.
Sounds an awful lot like a process, doesn't it? Well, it
should. Threads are one of the pieces of a process.
Every process has at least one thread and, up until now,
every process running Perl had only one thread. With 5.8,
though, you can create extra threads. We're going to show
you how, when, and why.
Threaded Program Models
There are three basic ways that you can structure a
threaded program. Which model you choose depends on what
you need your program to do. For many non-trivial
threaded programs you'll need to choose different models
for different pieces of your program.
Boss/Worker
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.
Work Crew
In the work crew model, several threads are created that
do essentially the same thing to different pieces of data.
It closely mirrors classical parallel processing and vec-
tor processors, where a large array of processors do the
exact same thing to many pieces of data.
This model is particularly useful if the system running
the program will distribute multiple threads across dif-
ferent processors. It can also be useful in ray tracing
or rendering engines, where the individual threads can
pass on interim results to give the user visual feedback.
Pipeline
The pipeline model divides up a task into a series of
steps, and passes the results of one step on to the thread
processing the next. Each thread does one thing to each
piece of data and passes the results to the next thread in
line.
This model makes the most sense if you have multiple pro-
cessors so two or more threads will be executing in paral-
lel, though it can often make sense in other contexts as
well. It tends to keep the individual tasks small and
simple, as well as allowing some parts of the pipeline to
block (on I/O or system calls, for example) while other
parts keep going. If you're running different parts of
the pipeline on different processors you may also take
advantage of the caches on each processor.
This model is also handy for a form of recursive program-
ming where, rather than having a subroutine call itself,
it instead creates another thread. Prime and Fibonacci
generators both map well to this form of the pipeline
model. (A version of a prime number generator is presented
later on.)
What kind of threads are Perl threads?
If you have experience with other thread implementations,
you might find that things aren't quite what you expect.
It's very important to remember when dealing with Perl
threads that Perl Threads Are Not X Threads, for all val-
ues of X. They aren't POSIX threads, or DecThreads, or
Java's Green threads, or Win32 threads. There are simi-
larities, and the broad concepts are the same, but if you
start looking for implementation details you're going to
be either disappointed or confused. Possibly both.
This is not to say that Perl threads are completely dif-
ferent 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 your-
self 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 can-
not magically do things unless your operating 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 sub-
stantially. There are implications for people who write
modules with XS code or external libraries. However, since
perl data is not shared among threads by default, Perl
modules stand a high chance of being thread-safe or can be
made thread-safe easily. Modules that are not tagged as
thread-safe should be tested or code reviewed before being
used in production code.
Not all modules that you might use are thread-safe, and
you should always assume a module is unsafe unless the
documentation says otherwise. This includes modules that
are distributed as part of the core. Threads are a new
feature, and even some of the standard modules aren't
thread-safe.
Even if a module is thread-safe, it doesn't mean that the
module is optimized to work well with threads. A module
could possibly be rewritten to utilize the new features in
threaded Perl to increase performance in a threaded envi-
ronment.
If you're using a module that's not thread-safe for some
reason, you can protect yourself by using it from one, and
only one thread at all. If you need multiple threads to
access such a module, you can use semaphores and lots of
programming discipline to control access to it.
Semaphores are covered in "Basic semaphores".
See also "Thread-Safety of System Libraries".
Thread Basics
The core threads module provides the basic functions you
need to write threaded programs. In the following sec-
tions we'll cover the basics, showing you what you need to
do to create a threaded program. After that, we'll go
over some of the features of the threads module that make
threaded programming easier.
Basic Thread Support
Thread support is a Perl compile-time option - it's some-
thing that's turned on or off when Perl is built at your
site, rather than when your programs are compiled. If your
Perl wasn't compiled with thread support enabled, then any
attempt to use threads will fail.
Your programs can use the Config module to check whether
threads are enabled. If your program can't run without
them, you can say something like:
$Config{useithreads} or die "Recompile Perl with threads to run this program.";
A possibly-threaded program using a possibly-threaded mod-
ule might have code like this:
use Config;
use MyMod;
BEGIN {
if ($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 usu-
ally pretty messy, it's best to isolate the thread-spe-
cific code in its own module. In our example above,
that's what MyMod_threaded is, and it's only imported if
we're running on a threaded Perl.
A Note about the Examples
Although thread support is considered to be stable, there
are still a number of quirks that may startle you when you
try out any of the examples below. In a real situation,
care should be taken that all threads are finished execut-
ing before the program exits. That care has not been
taken in these examples in the interest of simplicity.
Running these examples "as is" will produce error mes-
sages, usually caused by the fact that there are still
threads running when the program exits. You should not be
alarmed by this. Future versions of Perl may fix this
problem.
Creating Threads
The threads package provides the tools you need to create
new threads. Like any other module, you need to tell Perl
that you want to use it; "use threads" imports all the
pieces you need to create basic threads.
The simplest, most straightforward way to create a thread
is with new():
use threads;
$thr = threads->new(\&sub1);
sub sub1 {
print "In the thread\n";
}
The new() method takes a reference to a subroutine and
creates a new thread, which starts executing in the refer-
enced subroutine. Control then passes both to the subrou-
tine and the caller.
If you need to, your program can pass parameters to the
subroutine as part of the thread startup. Just include
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 subrou-
tine. Each thread executes the same subroutine, but in a
separate thread with a separate environment and poten-
tially separate arguments.
"create()" is a synonym for "new()".
Waiting For A Thread To Exit
Since threads are also subroutines, they can return val-
ues. To wait for a thread to exit and extract any values
it might return, you can use the join() method:
use threads;
$thr = threads->new(\&sub1);
@ReturnData = $thr->join;
print "Thread returned @ReturnData";
sub sub1 { return "Fifty-six", "foo", 2; }
In the example above, the join() method returns as soon as
the thread ends. In addition to waiting for a thread to
finish and gathering up any values that the thread might
have returned, join() also performs any OS cleanup neces-
sary for the thread. That cleanup might be important,
especially for long-running programs that spawn lots of
threads. If you don't want the return values and don't
want to wait for the thread to finish, you should call the
detach() method instead, as described next.
Ignoring A Thread
join() does three things: it waits for a thread to exit,
cleans up after it, and returns any data the thread may
have produced. But what if you're not interested in the
thread's return values, and you don't really care when the
thread finishes? All you want is for the thread to get
cleaned up after when it's done.
In this case, you use the detach() method. Once a thread
is detached, it'll run until it's finished, then Perl will
clean up after it automatically.
use threads;
$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 introduces a couple
of complications to data access that non-threaded programs
never need to worry about.
Shared And Unshared Data
The biggest difference between Perl ithreads and the old
5.005 style threading, or for that matter, to most other
threading systems out there, is that by default, no data
is shared. When a new perl thread is created, all the data
associated with the current thread is copied to the new
thread, and is subsequently private to that new thread!
This is similar in feel to what happens when a UNIX pro-
cess forks, except that in this case, the data is just
copied to a different part of memory within the same pro-
cess rather than a real fork taking place.
To make use of threading however, one usually wants the
threads to share at least some data between themselves.
This is done with the threads::shared module and the " :
shared" attribute:
use threads;
use threads::shared;
my $foo : shared = 1;
my $bar = 1;
threads->new(sub { $foo++; $bar++ })->join;
print "$foo\n"; #prints 2 since $foo is shared
print "$bar\n"; #prints 1 since $bar is not shared
In the case of a shared array, all the array's elements
are shared, and for a shared hash, all the keys and values
are shared. This places restrictions on what may be
assigned to shared array and hash elements: only simple
values or references to shared variables are allowed -
this is so that a private variable can't accidentally
become shared. A bad assignment will cause the thread to
die. For example:
use threads;
use threads::shared;
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 con-
dition:
use threads;
use threads::shared;
my $a : shared = 1;
$thr1 = threads->new(\&sub1);
$thr2 = threads->new(\&sub2);
$thr1->join;
$thr2->join;
print "$a\n";
sub sub1 { my $foo = $a; $a = $foo + 1; }
sub sub2 { my $bar = $a; $a = $bar + 1; }
What do you think $a will be? The answer, unfortunately,
is "it depends." Both sub1() and sub2() access the global
variable $a, once to read and once to write. Depending on
factors ranging from your thread implementation's schedul-
ing algorithm to the phase of the moon, $a can be 2 or 3.
Race conditions are caused by unsynchronized access to
shared data. Without explicit synchronization, there's no
way to be sure that nothing has happened to the shared
data between the time you access it and the time you
update it. Even this simple code fragment has the possi-
bility of error:
use threads;
my $a : shared = 2;
my $b : shared;
my $c : shared;
my $thr1 = threads->create(sub { $b = $a; $a = $b + 1; });
my $thr2 = threads->create(sub { $c = $a; $a = $c + 1; });
$thr1->join;
$thr2->join;
Two threads both access $a. Each thread can potentially
be interrupted at any point, or be executed in any order.
At the end, $a could be 3 or 4, and both $b and $c could
be 2 or 3.
Even "$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 coor-
dinate access or risk data inconsistency and race condi-
tions. Note that Perl will protect its internals from your
race conditions, but it won't protect you from you.
Synchronization and control
Perl provides a number of mechanisms to coordinate the
interactions between themselves and their data, to avoid
race conditions and the like. Some of these are designed
to resemble the common techniques used in thread libraries
such as "pthreads"; others are Perl-specific. Often, the
standard techniques are clumsy and difficult to get right
(such as condition waits). Where possible, it is usually
easier to use Perlish techniques such as queues, which
remove some of the hard work involved.
Controlling access: lock()
The lock() function takes a shared variable and puts a
lock on it. No other thread may lock the variable until
the variable is unlocked by the thread holding the lock.
Unlocking happens automatically when the locking thread
exits the outermost block that contains "lock()" function.
Using lock() is straightforward: this example has several
threads doing some calculations in parallel, and occasion-
ally updating a running total:
use threads;
use threads::shared;
my $total : shared = 0;
sub calc {
for (;;) {
my $result;
# (... do some calculations and set $result ...)
{
lock($total); # block until we obtain the lock
$total += $result;
} # lock implicitly released at end of scope
last if $result == 0;
}
}
my $thr1 = threads->new(\&calc);
my $thr2 = threads->new(\&calc);
my $thr3 = threads->new(\&calc);
$thr1->join;
$thr2->join;
$thr3->join;
print "total=$total\n";
lock() blocks the thread until the variable being locked
is available. When lock() returns, your thread can be
sure that no other thread can lock that variable until the
outermost block containing the lock exits.
It's important to note that locks don't prevent access to
the variable in question, only lock attempts. This is in
keeping with Perl's longstanding tradition of courteous
programming, and the advisory file locking that flock()
gives you.
You may lock arrays and hashes as well as scalars. Lock-
ing an array, though, will not block subsequent locks on
array elements, just lock attempts on the array itself.
Locks are recursive, which means it's okay for a thread to
lock a variable more than once. The lock will last until
the outermost lock() on the variable goes out of scope.
For example:
my $x : shared;
doit();
sub doit {
{
{
lock($x); # wait for lock
lock($x); # NOOP - we already have the lock
{
lock($x); # NOOP
{
lock($x); # NOOP
lockit_some_more();
}
}
} # *** implicit unlock here ***
}
}
sub lockit_some_more {
lock($x); # NOOP
} # nothing happens here
Note that there is no unlock() function - the only way to
unlock a variable is to allow it to go out of scope.
A lock can either be used to guard the data contained
within the variable being locked, or it can be used to
guard something else, like a section of code. In this lat-
ter case, the variable in question does not hold any use-
ful data, and exists only for the purpose of being locked.
In this respect, the variable behaves like the mutexes and
basic semaphores of traditional thread libraries.
A Thread Pitfall: Deadlocks
Locks are a handy tool to synchronize access to data, and
using them properly is the key to safe shared data.
Unfortunately, locks aren't without their dangers, espe-
cially when multiple locks are involved. Consider the
following code:
use threads;
my $a : shared = 4;
my $b : shared = "foo";
my $thr1 = threads->new(sub {
lock($a);
sleep 20;
lock($b);
});
my $thr2 = threads->new(sub {
lock($b);
sleep 20;
lock($a);
});
This program will probably hang until you kill it. The
only way it won't hang is if one of the two threads
acquires both locks first. A guaranteed-to-hang version
is more complicated, but the principle is the same.
The first thread will grab a lock on $a, then, after a
pause during which the second thread has probably had time
to do some work, try to grab a lock on $b. Meanwhile, the
second thread grabs a lock on $b, then later tries to grab
a lock on $a. The second lock attempt for both threads
will block, each waiting for the other to release its
lock.
This condition is called a deadlock, and it occurs when-
ever two or more threads are trying to get locks on
resources that the others own. Each thread will block,
waiting for the other to release a lock on a resource.
That never happens, though, since the thread with the
resource is itself waiting for a lock to be released.
There are a number of ways to handle this sort of problem.
The best way is to always have all threads acquire locks
in the exact same order. If, for example, you lock vari-
ables $a, $b, and $c, always lock $a before $b, and $b
before $c. It's also best to hold on to locks for as
short a period of time to minimize the risks of deadlock.
The other synchronization primitives described below can
suffer from similar problems.
Queues: Passing Data Around
A queue is a special thread-safe object that lets you put
data in one end and take it out the other without having
to worry about synchronization issues. They're pretty
straightforward, and look like this:
use threads;
use Thread::Queue;
my $DataQueue = Thread::Queue->new;
$thr = threads->new(sub {
while ($DataElement = $DataQueue->dequeue) {
print "Popped $DataElement off the queue\n";
}
});
$DataQueue->enqueue(12);
$DataQueue->enqueue("A", "B", "C");
$DataQueue->enqueue(\$thr);
sleep 10;
$DataQueue->enqueue(undef);
$thr->join;
You create the queue with "new Thread::Queue". Then you
can add lists of scalars onto the end with enqueue(), and
pop scalars off the front of it with dequeue(). A queue
has no fixed size, and can grow as needed to hold every-
thing pushed on to it.
If a queue is empty, dequeue() blocks until another thread
enqueues something. This makes queues ideal for event
loops and other communications between threads.
Semaphores: Synchronizing Data Access
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 increments it.
Calls to down() will block if the semaphore's current
count would decrement below zero. This program gives a
quick demonstration:
use threads;
use Thread::Semaphore;
my $semaphore = new Thread::Semaphore;
my $GlobalVariable : shared = 0;
$thr1 = new threads \&sample_sub, 1;
$thr2 = new threads \&sample_sub, 2;
$thr3 = new threads \&sample_sub, 3;
sub sample_sub {
my $SubNumber = shift @_;
my $TryCount = 10;
my $LocalCopy;
sleep 1;
while ($TryCount--) {
$semaphore->down;
$LocalCopy = $GlobalVariable;
print "$TryCount tries left for sub $SubNumber (\$GlobalVariable is $GlobalVariable)\n";
sleep 2;
$LocalCopy++;
$GlobalVariable = $LocalCopy;
$semaphore->up;
}
}
$thr1->join;
$thr2->join;
$thr3->join;
The three invocations of the subroutine all operate in
sync. The semaphore, though, makes sure that only one
thread is accessing the global variable at once.
Advanced Semaphores
By default, semaphores behave like locks, letting only one
thread down() them at a time. However, there are other
uses for semaphores.
Each semaphore has a counter attached to it. By default,
semaphores are created with the counter set to one, down()
decrements the counter by one, and up() increments by one.
However, we can override any or all of these defaults sim-
ply by passing in different values:
use threads;
use Thread::Semaphore;
my $semaphore = Thread::Semaphore->new(5);
# Creates a semaphore with the counter set to five
$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 dis-
play, so only one thread is ever drawing at once. Handy,
but of course you don't want any thread to start drawing
until things are properly set up. In this case, you can
create a semaphore with a counter set to zero, and up it
when things are ready for drawing.
Semaphores with counters greater than one are also useful
for establishing quotas. Say, for example, that you have
a number of threads that can do I/O at once. You don't
want all the threads reading or writing at once though,
since that can potentially swamp your I/O channels, or
deplete your process' quota of filehandles. You can use a
semaphore initialized to the number of concurrent I/O
requests (or open files) that you want at any one time,
and have your threads quietly block and unblock them-
selves.
Larger increments or decrements are handy in those cases
where a thread needs to check out or return a number of
resources at once.
cond_wait() and cond_signal()
These two functions can be used in conjunction with locks
to notify co-operating threads that a resource has become
available. They are very similar in use to the functions
found in "pthreads". However for most purposes, queues are
simpler to use and more intuitive. See threads::shared for
more details.
Giving up control
There are times when you may find it useful to have a
thread explicitly give up the CPU to another thread. You
may be doing something processor-intensive and want to
make sure that the user-interface thread gets called fre-
quently. Regardless, there are times that you might want
a thread to give up the processor.
Perl's threading package provides the yield() function
that does this. yield() is pretty straightforward, and
works like this:
use threads;
sub loop {
my $thread = shift;
my $foo = 50;
while($foo--) { print "in thread $thread\n" }
threads->yield;
$foo = 50;
while($foo--) { print "in thread $thread\n" }
}
my $thread1 = threads->new(\&loop, 'first');
my $thread2 = threads->new(\&loop, 'second');
my $thread3 = threads->new(\&loop, 'third');
It is important to remember that yield() is only a hint to
give up the CPU, it depends on your hardware, OS and
threading libraries what actually happens. On many oper-
ating systems, yield() is a no-op. Therefore it is impor-
tant to note that one should not build the scheduling of
the threads around yield() calls. It might work on your
platform but it won't work on another platform.
General Thread Utility Routines
We've covered the workhorse parts of Perl's threading
package, and with these tools you should be well on your
way to writing threaded code and packages. There are a
few useful little pieces that didn't really fit in any-
place else.
What Thread Am I In?
The "threads->self" class method provides your program
with a way to get an object representing the thread it's
currently in. You can use this object in the same way as
the ones returned from thread creation.
Thread IDs
tid() is a thread object method that returns the thread ID
of the thread the object represents. Thread IDs are inte-
gers, with the main thread in a program being 0. Cur-
rently Perl assigns a unique tid to every thread ever cre-
ated in your program, assigning the first thread to be
created a tid of 1, and increasing the tid by 1 for each
new thread that's created.
Are These Threads The Same?
The equal() method takes two thread objects and returns
true if the objects represent the same thread, and false
if they don't.
Thread objects also have an overloaded == comparison so
that you can do comparison on them as you would with nor-
mal objects.
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 program finds
prime numbers using threads.
1 #!/usr/bin/perl -w
2 # prime-pthread, courtesy of Tom Christiansen
3
4 use strict;
5
6 use threads;
7 use Thread::Queue;
8
9 my $stream = new Thread::Queue;
10 my $kid = new threads(\&check_num, $stream, 2);
11
12 for my $i ( 3 .. 1000 ) {
13 $stream->enqueue($i);
14 }
15
16 $stream->enqueue(undef);
17 $kid->join;
18
19 sub check_num {
20 my ($upstream, $cur_prime) = @_;
21 my $kid;
22 my $downstream = new Thread::Queue;
23 while (my $num = $upstream->dequeue) {
24 next unless $num % $cur_prime;
25 if ($kid) {
26 $downstream->enqueue($num);
27 } else {
28 print "Found prime $num\n";
29 $kid = new threads(\&check_num, $downstream, $num);
30 }
31 }
32 $downstream->enqueue(undef) if $kid;
33 $kid->join if $kid;
34 }
This program uses the pipeline model to generate prime
numbers. Each thread in the pipeline has an input queue
that feeds numbers to be checked, a prime number that it's
responsible for, and an output queue into which it funnels
numbers that have failed the check. If the thread has a
number that's failed its check and there's no child
thread, then the thread must have found a new prime num-
ber. 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() subrou-
tine, 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 check-
ing (line 20), we create a new queue (line 22) and reserve
a scalar for the thread that we're likely to create later
(line 21).
The while loop from lines 23 to line 31 grabs a scalar off
the input queue and checks against the prime this thread
is responsible for. Line 24 checks to see if there's a
remainder when we modulo the number to be checked against
our prime. If there is one, the number must not be evenly
divisible by our prime, so we need to either pass it on to
the next thread if we've created one (line 26) or create a
new thread if we haven't.
The new thread creation is line 29. We pass on to it a
reference to the queue we've created, and the prime number
we've found.
Finally, once the loop terminates (because we got a 0 or
undef in the queue, which serves as a note to die), we
pass on the notice to our child and wait for it to exit if
we've created a child (lines 32 and 37).
Meanwhile, back in the main thread, we create a queue
(line 9) and the initial child thread (line 10), and pre-
seed it with the first prime: 2. Then we queue all the
numbers from 3 to 1000 for checking (lines 12-14), then
queue a die notice (line 16) and wait for the first child
thread to terminate (line 17). Because a child won't die
until its child has died, we know that we're done once we
return from the join.
That's how it works. It's pretty simple; as with many
Perl programs, the explanation is much longer than the
program.
Different implementations of threads
Some background on thread implementations from the operat-
ing system viewpoint. There are three basic categories of
threads: user-mode threads, kernel threads, and multipro-
cessor kernel threads.
User-mode threads are threads that live entirely within a
program and its libraries. In this model, the OS knows
nothing about threads. As far as it's concerned, your
process is just a process.
This is the easiest way to implement threads, and the way
most OSes start. The big disadvantage is that, since the
OS knows nothing about threads, if one thread blocks they
all do. Typical blocking activities include most system
calls, most I/O, and things like sleep().
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 pro-
gram 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, regard-
less of how many CPUs a system might have.
Since kernel threading can interrupt a thread at any time,
they will uncover some of the implicit locking assumptions
you may make in your program. For example, something as
simple as "$a = $a + 2" can behave unpredictably with ker-
nel threads if $a is visible to other threads, as another
thread may have changed $a between the time it was fetched
on the right hand side and the time the new value is
stored.
Multiprocessor kernel threads are the final step in thread
support. With multiprocessor kernel threads on a machine
with multiple CPUs, the OS may schedule two or more
threads to run simultaneously on different CPUs.
This can give a serious performance boost to your threaded
program, since more than one thread will be executing at
the same time. As a tradeoff, though, any of those nag-
ging synchronization issues that might not have shown with
basic kernel threads will appear with a vengeance.
In addition to the different levels of OS involvement in
threads, different OSes (and different thread implementa-
tions for a particular OS) allocate CPU cycles to threads
in different ways.
Cooperative multitasking systems have running threads give
up control if one of two things happen. If a thread calls
a yield function, it gives up control. It also gives up
control if the thread does something that would cause it
to block, such as perform I/O. In a cooperative multi-
tasking implementation, one thread can starve all the oth-
ers for CPU time if it so chooses.
Preemptive multitasking systems interrupt threads at regu-
lar intervals while the system decides which thread should
run next. In a preemptive multitasking system, one thread
usually won't monopolize the CPU.
On some systems, there can be cooperative and preemptive
threads running simultaneously. (Threads running with
realtime priorities often behave cooperatively, for exam-
ple, while threads running at normal priorities behave
preemptively.)
Most modern operating systems support preemptive multi-
tasking nowadays.
Performance considerations
The main thing to bear in mind when comparing ithreads to
other threading models is the fact that for each new
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 per-
formance 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-dependent, and
even the POSIX semantics may not be what you expect (and
Perl doesn't even give you the full POSIX API).
Thread-Safety of System Libraries
Whether various library calls are thread-safe is outside
the control of Perl. Calls often suffering from not being
thread-safe include: localtime(), gmtime(),
get{gr,host,net,proto,serv,pw}*(), readdir(), rand(), and
srand() -- in general, calls that depend on some global
external state.
If the system Perl is compiled in has thread-safe variants
of such calls, they will be used. Beyond that, Perl is at
the mercy of the thread-safety or -unsafety of the calls.
Please consult your C library call documentation.
On some platforms the thread-safe library interfaces may
fail if the result buffer is too small (for example the
user group databases may be rather large, and the reen-
trant interfaces may have to carry around a full snapshot
of those databases). Perl will start with a small buffer,
but keep retrying and growing the result buffer until the
result fits. If this limitless growing sounds bad for
security or memory consumption reasons you can recompile
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 Jurgen Christof-
fel:
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 Pro-
gramming: A Guide to Concurrency, Communication, and Mul-
tithreading. Prentice-Hall, 1996.
Lewis, Bill, and Daniel J. Berg. Multithreaded Programming
with Pthreads. Prentice Hall, 1997, ISBN 0-13-443698-9 (a
well-written introduction to threads).
Nelson, Greg (editor). Systems Programming with Modula-3.
Prentice Hall, 1991, ISBN 0-13-590464-1.
Nichols, Bradford, Dick Buttlar, and Jacqueline Proulx
Farrell. Pthreads Programming. O'Reilly & Associates,
1996, ISBN 156592-115-1 (covers POSIX threads).
OS-Related References
Boykin, Joseph, David Kirschen, Alan Langerman, and Susan
LoVerso. Programming under Mach. Addison-Wesley, 1994,
ISBN 0-201-52739-1.
Tanenbaum, Andrew S. Distributed Operating Systems. Pren-
tice Hall, 1995, ISBN 0-13-219908-4 (great textbook).
Silberschatz, Abraham, and Peter B. Galvin. Operating Sys-
tem Concepts, 4th ed. Addison-Wesley, 1995, ISBN
0-201-59292-4
Other References
Arnold, Ken and James Gosling. The Java Programming Lan-
guage, 2nd ed. Addison-Wesley, 1998, ISBN 0-201-31006-6.
comp.programming.threads FAQ,
Le Sergent, T. and B. Berthomieu. "Incremental Multi-
Threaded Garbage Collection on Virtually Shared Memory
Architectures" in Memory Management: Proc. of the Interna-
tional Workshop IWMM 92, St. Malo, France, September 1992,
Yves Bekkers and Jacques Cohen, eds. Springer, 1992, ISBN
3540-55940-X (real-life thread applications).
Artur Bergman, "Where Wizards Fear To Tread", June 11,
2002,
Acknowledgements
Thanks (in no particular order) to Chaim Frenkel, Steve
Fink, Gurusamy Sarathy, Ilya Zakharevich, Benjamin Sugars,
Jurgen Christoffel, Joshua Pritikin, and Alan Burlison,
for their help in reality-checking and polishing this
article. Big thanks to Tom Christiansen for his rewrite
of the prime number generator.
AUTHOR
Dan Sugalski
Slightly modified by Arthur Bergman to fit the new thread
model/module.
Reworked slightly by Jorg Walter to be
more concise about thread-safety of perl code.
Rearranged slightly by Elizabeth Mattijsen 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)