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NAME

MCE - Many-Core Engine for Perl providing parallel processing capabilities

VERSION

This document describes MCE version 1.706

Many-Core Engine (MCE) for Perl helps enable a new level of performance by maximizing all available cores.

MCE

DESCRIPTION

MCE spawns a pool of workers and therefore does not fork a new process per each element of data. Instead, MCE follows a bank queuing model. Imagine the line being the data and bank-tellers the parallel workers. MCE enhances that model by adding the ability to chunk the next n elements from the input stream to the next available worker.

Bank Queuing Model

SYNOPSIS

This is a simplistic use case of MCE running with 5 workers.

   # Construction using the Core API

   use MCE;

   my $mce = MCE->new(
      max_workers => 5,
      user_func => sub {
         my ($mce) = @_;
         $mce->say("Hello from " . $mce->wid);
      }
   );

   $mce->run;

   # Construction using a MCE model

   use MCE::Flow max_workers => 5;

   mce_flow sub {
      my ($mce) = @_;
      MCE->say("Hello from " . MCE->wid);
   };

The following is a demonstration for parsing a huge log file in parallel.

   use MCE::Loop;

   MCE::Loop::init { max_workers => 8, use_slurpio => 1 };

   my $pattern  = 'something';
   my $hugefile = 'very_huge.file';

   my @result = mce_loop_f {
      my ($mce, $slurp_ref, $chunk_id) = @_;

      # Quickly determine if a match is found.
      # Process the slurped chunk only if true.

      if ($$slurp_ref =~ /$pattern/m) {
         my @matches;

         # The following is fast on Unix, but performance degrades
         # drastically on Windows beyond 4 workers.

         open my $MEM_FH, '<', $slurp_ref;
         binmode $MEM_FH, ':raw';
         while (<$MEM_FH>) { push @matches, $_ if (/$pattern/); }
         close   $MEM_FH;

         # Therefore, use the following construction on Windows.

         while ( $$slurp_ref =~ /([^\n]+\n)/mg ) {
            my $line = $1; # save $1 to not lose the value
            push @matches, $line if ($line =~ /$pattern/);
         }

         # Gather matched lines.

         MCE->gather(@matches);
      }

   } $hugefile;

   print join('', @result);

The next demonstration loops through a sequence of numbers with MCE::Flow.

   use MCE::Flow;

   my $N = shift || 4_000_000;

   sub compute_pi {
      my ( $beg_seq, $end_seq ) = @_;
      my ( $pi, $t ) = ( 0.0 );

      foreach my $i ( $beg_seq .. $end_seq ) {
         $t = ( $i + 0.5 ) / $N;
         $pi += 4.0 / ( 1.0 + $t * $t );
      }

      MCE->gather( $pi );
   }

   # Compute bounds only, workers receive [ begin, end ] values

   MCE::Flow::init(
      chunk_size  => 200_000,
      max_workers => 8,
      bounds_only => 1
   );

   my @ret = mce_flow_s sub {
      compute_pi( $_->[0], $_->[1] );
   }, 0, $N - 1;

   my $pi = 0.0;  $pi += $_ for @ret;

   printf "pi = %0.13f\n", $pi / $N;  # 3.1415926535898

CORE MODULES

Three modules make up the core engine for MCE.

MCE::Core

Provides the Core API for Many-Core Engine. The various MCE options are described here.

MCE::Signal

Temporary directory creation, cleanup, and signal handling.

MCE::Util

Utility functions for Many-Core Engine.

MCE EXTRAS

There are 4 add-on modules for use with MCE.

MCE::Candy

Provides a collection of sugar methods and output iterators for preserving output order.

MCE::Mutex

Provides a simple semaphore implementation supporting threads and processes.

MCE::Queue

Provides a hybrid queuing implementation for MCE supporting normal queues and priority queues from a single module. MCE::Queue exchanges data via the core engine to enable queueing to work for both children (spawned from fork) and threads.

MCE::Relay

Enables workers to receive and pass on information orderly with zero involvement by the manager process while running.

MCE MODELS

The models take Many-Core Engine to a new level for ease of use. Two options (chunk_size and max_workers) are configured automatically as well as spawning and shutdown.

MCE::Loop

Provides a parallel loop utilizing MCE for building creative loops.

MCE::Flow

A parallel flow model for building creative applications. This makes use of user_tasks in MCE. The author has full control when utilizing this model. MCE::Flow is similar to MCE::Loop, but allows for multiple code blocks to run in parallel with a slight change to syntax.

MCE::Grep

Provides a parallel grep implementation similar to the native grep function.

MCE::Map

Provides a parallel map model similar to the native map function.

MCE::Step

Provides a parallel step implementation utilizing MCE::Queue between user tasks. MCE::Step is a spin off from MCE::Flow with a touch of MCE::Stream. This model, introduced in 1.506, allows one to pass data from one sub-task into the next transparently.

MCE::Stream

Provides an efficient parallel implementation for chaining multiple maps and greps together through user_tasks and MCE::Queue. Like with MCE::Flow, MCE::Stream can run multiple code blocks in parallel with a slight change to syntax from MCE::Map and MCE::Grep.

MISCELLANEOUS

Miscellaneous additions included with the distribution.

MCE::Examples

Describes various demonstrations for MCE including a Monte Carlo simulation.

MCE::Subs

Exports functions mapped directly to MCE methods; e.g. mce_wid. The module allows 3 options; :manager, :worker, and :getter.

REQUIREMENTS

Perl 5.8.0 or later. PDL::IO::Storable is required in scripts running PDL.

SOURCE AND FURTHER READING

The source, cookbook, and examples are hosted at GitHub.

SEE ALSO

MCE::Shared provides data sharing capabilities for MCE. It includes MCE::Hobo for running code asynchronously.

AUTHOR

Mario E. Roy, <marioeroy AT gmail DOT com>

COPYRIGHT AND LICENSE

Copyright (C) 2012-2016 by Mario E. Roy

MCE is released under the same license as Perl.

See http://dev.perl.org/licenses/ for more information.