[% setvar title Lightweight Threads %]
To see what is currently happening visit http://www.perl6.org/
Lightweight Threads
Maintainer: Steven McDougall <swmcd@world.std.com> Date: 30 Aug 2000 Last Modified: 26 Sep 2000 Mailing List: perl6-language-flow@perl.org Number: 178 Version: 5 Status: Frozen
A lightweight thread model for Perl.
localizing global variablesmyFrozen
There was substantial--if somewhat disjointed--discussion of thread models on perl6-internals. The consensus among those with internals experience is that this RFC shares too much data between threads, and that the CPU cost of acquiring a lock for every variable access will be prohibitive.
Dan Sugalski discussed some of the tradeoffs and sketched an alternate threading model at
www.mail-archive.com
however, this has not been submitted as an RFC.
The overriding design principle in this model is that there is one program executing in multiple threads. One body of code; one set of global variables; many threads of execution. I like this model because
We'll call the first thread that executes in a program the main thread. It isn't distinguished in any other way. All other threads are called spawned threads.
Code that isn't contained in a BLOCK.
Examples are written in Perl5, and use the thread programming model
documented in Thread.pm. Discussions of performance and
implementation is based on the Perl5 internals; obviously, these are
subject to change.
Subroutines are typically defined during the initial compilation of a
program. use, require, do, and eval can later define
additional subroutines or redefine existing ones. Regardless, at any
point in its execution, a program has one and only one collection of
defined subroutines, and all threads see this collection.
Example 1
sub foo { print 1 }
sub hack_foo { eval 'sub foo { print 2 }' }
foo();
Thread->new(\&hack_foo)->join;
foo();
Output: 12. The main thread executes foo; the spawned thread
redefines foo; the main thread executes the redefined subroutine.
Example 2
sub foo { print 1 }
sub hack_foo { eval 'sub foo { print 2 }' }
foo();
Thread->new(\&hack_foo);
foo();
Output: 11 or 12, according as the main thread does or does not make
the second call to foo() before the spawned thread redefines it. If
the user cares which happens first, then they are responsible for
doing their own synchronization, for example, with join, as shown
in Example 1.
Code refs (like all Perl data objects) are reference counted. Threads increment the reference count upon entry to a subroutine, and decrement it upon exit. This ensures that the op tree won't be garbage collected while the thread is executing it.
Example 3
#!/my/path/to/perl
$a = 1;
Thread->new(\&foo)->join;
print $a;
sub foo { $a++ }
Output: 2. $a is a global, and it is the same global in both the
main thread and the spawned thread.
localizing global
variablesExample 4
#!/my/path/to/perl
$a = 1;
Thread->new(\&foo);
print $a;
sub foo { local $a = 2 }
Output: 1. The spawned thread gets it's own copy of $a. The copy of
$a in the main thread is unaffected. It doesn't matter whether the
assignment in foo executes before or after the print in the main
thread. It doesn't matter whether the copy of $a goes out of scope
before or after the print executes.
As in Perl5, localized variables are visible to any subroutines
called while they remain in scope.
Example 5
#!/my/path/to/perl
$a = 1;
Thread->new(\&foo);
bar();
sub foo
{
local $a = 2;
bar();
}
sub bar { print $a }
Output: 12 or 21, depending on the order in which the calls to bar
execute.
Dynamic scopes are not inherited by spawned threads.
Example 6
#!/my/path/to/perl
$a = 1;
foo();
sub foo
{
local $a = 2;
Thread->new(\&bar)->join;
}
sub bar { print $a }
Output: 1. The spawned thread sees the original value of $a.
Example 7
#!/my/path/to/perl
my $a = 1;
Thread->new(\&foo)->join;
print $a;
sub foo { $a = 2 }
Output: 2. $a is a file-scoped lexical. It is the same variable in
both the main thread and the spawned thread.
myExample 8
#!/my/path/to/perl
foo();
Thread->new(\&foo);
sub foo
{
my $a = 1;
print $a++;
}
Output: 11. This result is guaranteed, even if the statements execute in this order
Main thread Spawned thread my $a = 1; my $a = 1; print $a++; print $a++
$a is a block-scoped lexical variable. Every time a thread executes
the my, a new variable is created, completely unrelated to any
other variable in any thread.
By passing a reference into a threaded subroutine
Example 9
#!/my/path/to/perl
foo();
sub foo
{
my $a;
Thread->new(\&bar, $a)->join;
$a++;
print $a;
}
sub bar { $_[0]++ }
Output: 2
Example 10:
By declaring one subroutine within the scope of another
#!/my/path/to/perl
foo();
sub foo
{
my $a;
Thread->new(\&bar)->join;
$a++;
print $a;
sub bar { $$a++ }
}
Output: 2
Example 11:
Using closures
#!/my/path/to/perl
my $foo = foo_generator(1);
$foo->();
Thread->new($foo);
sub foo_generator
{
my $a = shift;
sub { print $a++ }
}
Output: 12
Threads execute BLOCKs
new Thread \&foo
new Thread sub { ... }
async { ... }
This means that code that is not contained in a BLOCK can only be executed by a thread that compiles it.
Example 12
#!/my/path/to/perl
Thread->new(\&foo)->join;
Thread->new(\&foo)->join;
print $a;
sub foo { require Bar; }
# Bar.pm
$a++;
Output: 1. require won't compile the same file twice, so the
increment only executes in the first spawned thread.
Example 13
#!/my/path/to/perl
Thread->new(\&foo)->join;
Thread->new(\&foo)->join;
print $a;
sub foo { do 'Bar.pm'; }
# Bar.pm
$a++;
Output: 2. do will compile the same file repeatedly, so the
increment executes in both spawned threads.
Example 14
#!/my/path/to/perl
Thread->new(\&foo)->join;
Thread->new(\&foo)->join;
sub foo { do 'Bar.pm'; }
# Bar.pm
my $a = 1;
print $a++;
Output: 11. The my creates a new file-scoped lexical each time it
executes.
Example 15
#!/my/path/to/perl
$a++;
async { do $0 } if $a < 2;
print $a;
Output: 12 or 21. Evil, but straightforward. The main thread and the spawned thread both compile and execute the program.
The language guarantees atomic access to data values. Access to a data value means a fetch or a store.
Example 16
#!/my/path/to/perl
$a = 'abcd';
async { $a = 'wxyz' }
print $a;
Output: `abcd' or `wxyz'. Without atomic data access, the print
statement might fetch $a while the async block is storing it.
This could produce output like `wxcd', or crash the interpreter.
Any serialization beyond atomic data access is the responsibility of the user.
Example 17
#!/my/path/to/perl
$a = 0;
$thread = new Thread \&foo;
$a++;
$thread->join;
print $a;
sub foo { $a++ }
Output: 1 or 2. The output is 1 if the increment operations interleave like this
Main thread Spawned thread
fetch a
fetch a
add 1
add 1
store a
store a
Perl6 could have either cooperative threads or preemptive threads.
RFC 47 proposes that "there...be one event loop for all of Perl". This event loop would dispatch op codes, deliver signals, and invoke callbacks. It would be a natural extension of this architecture for the event loop to dispatch op codes for multiple threads of a Perl program.
The big advantage of cooperative threads is that the Perl interpreter remains a single-threaded program. A Perl program may have many threads, but the interpreter has only one: it runs an event loop and it dispatches op codes. Because it is single-threaded, the interpreter is not subject to race conditions, and requires no synchronization code.
Cooperative threads have several disadvantages
yield() call for XSUBs
to call during time-consuming operations.The interpreter is implemented on top of a native threading package, such as PThreads. Each Perl thread runs in its own native thread. We get SMP, and we always get control back from XSUBs. (Although XSUBs can still crash the interpreter.)
The big drawback of preemptive threads is that the interpreter itself becomes a multi-threaded program, with all attendant synchronization requirements. If Perl6 gets preemptive threads, expect race conditions to become the kind of ongoing headache that memory leaks were for Perl4 and Perl5.
If Perl6 implements preemptive threads, then the interpreter must lock variables to ensure atomic data access.
Perl source Implementation
$a = $b lock b
fetch b
unlock b
lock a
store a
unlock a
Acquiring and releasing locks takes time. There is concern on perl6-language-flow and perl6-internals that threaded programs will run slowly if the interpreter must acquire a lock for every variable access.
RFC1 "Implementation of Threads in Perl" proposes that, by default, threads be isolated in separate data spaces.
global:: provides shared storage between threads. $a # different in different threads
$global::a # shared between different threads
use's all its modules, so that it any module data can
be reinitialized for that thread.Discussion on perl6-language-flow has further suggested that each
thread get its own copy of each lexical variable. A :shared
attribute could be used to declare lexicals that are shared between
threads.
my $a # different in different threads
my $a : shared # shared between different threads
We'll call this an isolated data model. The rational for adopting an isolated data model is that it will make existing Perl5 modules reentrant.
This RFC proposes that Perl not take any special steps to isolate threads in separate data spaces. Globals are shared unless localized, and file-scoped lexicals are shared unless a thread recompiles the file. We'll call this a shared data model.
I prefer a shared data model because
This isn't something that we can argue about with thought experiments. The modules are out there on CPAN; we have to look and see how they behave. I took a quick stroll through the modules that are installed on my own system; here is a small, non-random sample of what I found.
Sys::HostnameSys::Hostname gets the system hostname and caches it in
$Sys::Hostname::host. This works correctly in a shared data model,
even without any synchronization mechanism. An isolated data model
defeats the cache, forcing every thread to look up the hostname
itself.
Set::IntSpanSet::IntSpan uses one global: $Set::IntSpan::Empty_String. All
Set::IntSpan objects must see the same value for this global.
Applications typically set this global once and then leave it
untouched; methods in Set::IntSpan read it, but do not write it.
This works correctly in a shared data model; it breaks in an isolated
data model.
Time::LocalTime::Local caches the start times of months in
%Time::Local::cheat. This works correctly in shared data model; an
isolated data model defeats the cache.
Some methods in Time::Local store temporary values in package
globals, e.g. $Time::Local::ym. This works correctly in an isolated
data model, and breaks in a shared data model.
File::FindFile::Find stores the name of the current file in
$File::Find::name, and the current directory path in
$File::Find::path. This works in an isolated data model, and breaks
in a shared data model.
However, File::Find also cds to the directory where the current
file is. This isn't reentrant, and it can't be made reentrant, because
a process has only one CWD, which is shared by all threads. This means
that the File::Find interface is intrinsically broken under
threads.
Term::CompleteTerm::Complete stores key codes in globals:
$Term::Complete::complete, $Term::Complete::kill,
$Term::Complete::erase1, and $Term::Complete::erase2. This is
reentrant in an isolated data model, and not in a shared data model.
However, Term::Complete isn't even reentrant under Perl5. If two
different parts of an application both use Term::Complete, they
don't need threads to fight over the values of its globals. I'm hard
pressed to see that the design of Perl6 should be driven by the need
to fix modules that are broken in Perl5.
Again, this sample of modules isn't large, or random. But it does show that
RFCs 27 and 31 discuss coroutines. RFC 47 discusses asynchronous I/O. I'm happy to have other concurrency mechanisms in Perl, but I want threads, and I don't want to give up any features of threads on the grounds that you can do the same thing with some other concurrency mechanism.
RFC 1: Implementation of Threads in Perl
RFC 27: Coroutines for Perl
RFC 31: Subroutines: Co-routines
RFC 47: Universal Asynchronous I/O
RFC 185: Thread Programming Model