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PROGRAM:

NAME

PDL::ParallelCPU - Parallel Processor MultiThreading Support in PDL (Experimental)

DESCRIPTION

PDL has support (currently experimental) for splitting up numerical processing between
multiple parallel processor threads (or pthreads) using the set_autopthread_targ and
set_autopthread_size functions. This can improve processing performance (by greater than
2-4X in most cases) by taking advantage of multi-core and/or multi-processor machines.

SYNOPSIS

use PDL;

# Set target of 4 parallel pthreads to create, with a lower limit of
# 5Meg elements for splitting processing into parallel pthreads.
set_autopthread_targ(4);
set_autopthread_size(5);

$a = zeroes(5000,5000); # Create 25Meg element array

$b = $a + 5; # Processing will be split up into multiple pthreads

# Get the actual number of pthreads for the last
# processing operation.
$actualPthreads = get_autopthread_actual();

Terminology

The use of the term threading can be confusing with PDL, because it can refer to PDL
threading, as defined in the PDL::Threading docs, or to processor multi-threading.

To reduce confusion with the existing PDL threading terminology, this document uses
pthreading to refer to processor multi-threading, which is the use of multiple processor
threads to split up numerical processing into parallel operations.

Functions that control PDL PThreads

This is a brief listing and description of the PDL pthreading functions, see the PDL::Core
docs for detailed information.

set_autopthread_targ
Set the target number of processor-threads (pthreads) for multi-threaded processing.
Setting auto_pthread_targ to 0 means that no pthreading will occur.

See PDL::Core for details.

set_autopthread_size
Set the minimum size (in Meg-elements or 2**20 elements) of the largest PDL involved
in a function where auto-pthreading will be performed. For small PDLs, it probably
isn't worth starting multiple pthreads, so this function is used to define a minimum
threshold where auto-pthreading won't be attempted.

See PDL::Core for details.

get_autopthread_actual
Get the actual number of pthreads executed for the last pdl processing function.

See PDL::get_autopthread_actual for details.

Global Control of PDL PThreading using Environment Variables

PDL PThreading can be globally turned on, without modifying existing code by setting
environment variables PDL_AUTOPTHREAD_TARG and PDL_AUTOPTHREAD_SIZE before running a PDL
script. These environment variables are checked when PDL starts up and calls to
set_autopthread_targ and set_autopthread_size functions made with the environment
variable's values.

For example, if the environment var PDL_AUTOPTHREAD_TARG is set to 3, and
PDL_AUTOPTHREAD_SIZE is set to 10, then any pdl script will run as if the following lines
were at the top of the file:

set_autopthread_targ(3);
set_autopthread_size(10);

How It Works

The auto-pthreading process works by analyzing threaded array dimensions in PDL operations
and splitting up processing based on the thread dimension sizes and desired number of
pthreads (i.e. the pthread target or pthread_targ). The offsets and increments that PDL
uses to step thru the data in memory are modified for each pthread so each one sees a
different set of data when performing processing.

Example

$a = sequence(20,4,3); # Small 3-D Array, size 20,4,3

# Setup auto-pthreading:
set_autopthread_targ(2); # Target of 2 pthreads
set_autopthread_size(0); # Zero so that the small PDLs in this example will be pthreaded

# This will be split up into 2 pthreads
$c = maximum($a);

For the above example, the maximum function has a signature of "(a(n); [o]c())", which
means that the first dimension of $a (size 20) is a Core dimension of the maximum
function. The other dimensions of $a (size 4,3) are threaded dimensions (i.e. will be
threaded-over in the maximum function.

The auto-pthreading algorithm examines the threaded dims of size (4,3) and picks the 4
dimension, since it is evenly divisible by the autopthread_targ of 2. The processing of
the maximum function is then split into two pthreads on the size-4 dimension, with dim
indexes 0,2 processed by one pthread
and dim indexes 1,3 processed by the other pthread.

Limitations

Must have POSIX Threads Enabled
Auto-PThreading only works if your PDL installation was compiled with POSIX threads
enabled. This is normally the case if you are running on linux, or other unix variants.

Non-Threadsafe Code
Not all the libraries that PDL intefaces to are thread-safe, i.e. they aren't written to
operate in a multi-threaded environment without crashing or causing side-effects. Some
examples in the PDL core is the fft function and the pnmout functions.

To operate properly with these types of functions, the PPCode flag NoPthread has been
introduced to indicate a function as not being pthread-safe. See PDL::PP docs for details.

Size of PDL Dimensions and PThread Target
Due to the way a PDL is split-up for operation using multiple pthreads, the size of a
dimension must be evenly divisible by the pthread target. For example, if a PDL has
threaded dimension sizes of (4,3,3) and the auto_pthread_targ has been set to 2, then the
first threaded dimension (size 4) will be picked to be split up into two pthreads of size
2 and 2. However, if the threaded dimension sizes are (3,3,3) and the auto_pthread_targ is
still 2, then pthreading won't occur, because no threaded dimensions are divisible by 2.

The algorithm that picks the actual number of pthreads has some smarts (but could probably
be improved) to adjust down from the auto_pthread_targ to get a number of pthreads that
can evenly divide one of the threaded dimensions. For example, if a PDL has threaded
dimension sizes of (9,2,2) and the auto_pthread_targ is 4, the algorithm will see that no
dimension is divisible by 4, then adjust down the target to 3, resulting in splitting up
the first threaded dimension (size 9) into 3 pthreads.

Speed improvement might be less than you expect.
If you have a 8 core machine and call auto_pthread_targ with 8 to generate 8 parallel
pthreads, you probably won't get a 8X improvement in speed, due to memory bandwidth
issues. Even though you have 8 separate CPUs crunching away on data, you will have (for
most common machine architectures) common RAM that now becomes your bottleneck. For simple
calculations (e.g simple additions) you can run into a performance limit at about
4 pthreads. For more complex calculations the limit will be higher.

COPYRIGHT

Copyright 2011 John Cerney. You can distribute and/or modify this document under the same
terms as the current Perl license.

See: http://dev.perl.org/licenses/

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