MCE::Loop - Parallel loop model for building creative loops
This document describes MCE::Loop version 1.699_010
This module provides a parallel loop implementation through Many-Core Engine. MCE::Loop is not MCE::Map but more along the lines of an easy way to spin up a MCE instance and have user_func pointing to your code block. If you want something similar to map, then see MCE::Map.
## Construction when chunking is not desired use MCE::Loop; MCE::Loop::init { max_workers => 5, chunk_size => 1 }; mce_loop { my ($mce, $chunk_ref, $chunk_id) = @_; MCE->say("$chunk_id: $_"); } 40 .. 48; -- Output 3: 42 1: 40 2: 41 4: 43 5: 44 6: 45 7: 46 8: 47 9: 48 ## Construction for 'auto' or greater than 1 use MCE::Loop; MCE::Loop::init { max_workers => 5, chunk_size => 'auto' }; mce_loop { my ($mce, $chunk_ref, $chunk_id) = @_; for (@{ $chunk_ref }) { MCE->say("$chunk_id: $_"); } } 40 .. 48; -- Output 1: 40 2: 42 1: 41 4: 46 2: 43 5: 48 3: 44 4: 47 3: 45
All models in MCE default to 'auto' for chunk_size. The arguments for the block are the same as writing a user_func block using the Core API.
Beginning with MCE 1.5, the next input item is placed into the input scalar variable $_ when chunk_size equals 1. Otherwise, $_ points to $chunk_ref containing many items. Basically, line 2 below may be omitted from your code when using $_. One can call MCE->chunk_id to obtain the current chunk id.
line 1: user_func => sub { line 2: my ($mce, $chunk_ref, $chunk_id) = @_; line 3: line 4: $_ points to $chunk_ref->[0] line 5: in MCE 1.5 when chunk_size == 1 line 6: line 7: $_ points to $chunk_ref line 8: in MCE 1.5 when chunk_size > 1 line 9: }
Follow this synopsis when chunk_size equals one. Looping is not required from inside the block. Hence, the block is called once per each item.
## Exports mce_loop, mce_loop_f, and mce_loop_s use MCE::Loop; MCE::Loop::init { chunk_size => 1 }; ## Array or array_ref mce_loop { do_work($_) } 1..10000; mce_loop { do_work($_) } [ 1..10000 ]; ## File_path, glob_ref, or scalar_ref mce_loop_f { chomp; do_work($_) } "/path/to/file"; mce_loop_f { chomp; do_work($_) } $file_handle; mce_loop_f { chomp; do_work($_) } \$scalar; ## Sequence of numbers (begin, end [, step, format]) mce_loop_s { do_work($_) } 1, 10000, 5; mce_loop_s { do_work($_) } [ 1, 10000, 5 ]; mce_loop_s { do_work($_) } { begin => 1, end => 10000, step => 5, format => undef };
Follow this synopsis when chunk_size equals 'auto' or greater than 1. This means having to loop through the chunk from inside the block.
use MCE::Loop; MCE::Loop::init { ## Chunk_size defaults to 'auto' when chunk_size => 'auto' ## not specified. Therefore, the init }; ## function may be omitted. ## Syntax is shown for mce_loop for demonstration purposes. ## Looping inside the block is the same for mce_loop_f and ## mce_loop_s. mce_loop { do_work($_) for (@{ $_ }) } 1..10000; ## Same as above, resembles code using the Core API. mce_loop { my ($mce, $chunk_ref, $chunk_id) = @_; for (@{ $chunk_ref }) { do_work($_); } } 1..10000;
Chunking reduces the number of IPC calls behind the scene. Think in terms of chunks whenever processing a large amount of data. For relatively small data, choosing 1 for chunk_size is fine.
The following list options which may be overridden when loading the module.
use Sereal qw( encode_sereal decode_sereal ); use CBOR::XS qw( encode_cbor decode_cbor ); use JSON::XS qw( encode_json decode_json ); use MCE::Loop max_workers => 4, ## Default 'auto' chunk_size => 100, ## Default 'auto' tmp_dir => "/path/to/app/tmp", ## $MCE::Signal::tmp_dir freeze => \&encode_sereal, ## \&Storable::freeze thaw => \&decode_sereal ## \&Storable::thaw ;
There is a simpler way to enable Sereal. The following will attempt to use Sereal if available, otherwise defaults to Storable for serialization.
use MCE::Loop Sereal => 1;
The init function accepts a hash of MCE options.
use MCE::Loop; MCE::Loop::init { chunk_size => 1, max_workers => 4, user_begin => sub { print "## ", MCE->wid, " started\n"; }, user_end => sub { print "## ", MCE->wid, " completed\n"; } }; my %a = mce_loop { MCE->gather($_, $_ * $_) } 1..100; print "\n", "@a{1..100}", "\n"; -- Output ## 3 started ## 1 started ## 2 started ## 4 started ## 1 completed ## 2 completed ## 3 completed ## 4 completed 1 4 9 16 25 36 49 64 81 100 121 144 169 196 225 256 289 324 361 400 441 484 529 576 625 676 729 784 841 900 961 1024 1089 1156 1225 1296 1369 1444 1521 1600 1681 1764 1849 1936 2025 2116 2209 2304 2401 2500 2601 2704 2809 2916 3025 3136 3249 3364 3481 3600 3721 3844 3969 4096 4225 4356 4489 4624 4761 4900 5041 5184 5329 5476 5625 5776 5929 6084 6241 6400 6561 6724 6889 7056 7225 7396 7569 7744 7921 8100 8281 8464 8649 8836 9025 9216 9409 9604 9801 10000
The following assumes chunk_size equals 1 in order to demonstrate all the possibilities of passing input data into the code block.
An iterator reference can by specified for input_data. Iterators are described under "SYNTAX for INPUT_DATA" at MCE::Core.
mce_loop { $_ } make_iterator(10, 30, 2);
Input data can be defined using a list.
mce_loop { $_ } 1..1000; mce_loop { $_ } [ 1..1000 ];
The fastest of these is the /path/to/file. Workers communicate the next offset position among themselves without any interaction from the manager process.
mce_loop_f { $_ } "/path/to/file"; mce_loop_f { $_ } $file_handle; mce_loop_f { $_ } \$scalar;
Sequence can be defined as a list, an array reference, or a hash reference. The functions require both begin and end values to run. Step and format are optional. The format is passed to sprintf (% may be omitted below).
my ($beg, $end, $step, $fmt) = (10, 20, 0.1, "%4.1f"); mce_loop_s { $_ } $beg, $end, $step, $fmt; mce_loop_s { $_ } [ $beg, $end, $step, $fmt ]; mce_loop_s { $_ } { begin => $beg, end => $end, step => $step, format => $fmt };
The sequence engine can compute 'begin' and 'end' items only, for the chunk, and not the items in between (hence boundaries only). This option applies to sequence only and has no effect when chunk_size equals 1.
The time to run is 0.006s below. This becomes 0.827s without the bounds_only option due to computing all items in between, thus creating a very large array. Basically, specify bounds_only => 1 when boundaries is all you need for looping inside the block; e.g. Monte Carlo simulations.
Time was measured using 1 worker to emphasize the difference.
use MCE::Loop; MCE::Loop::init { max_workers => 1, chunk_size => 1_250_000, bounds_only => 1 }; ## For sequence, the input scalar $_ points to $chunk_ref ## when chunk_size > 1, otherwise $chunk_ref->[0]. ## ## mce_loop_s { ## my $begin = $_->[0]; my $end = $_->[-1]; ## ## for ($begin .. $end) { ## ... ## } ## ## } 1, 10_000_000; mce_loop_s { my ($mce, $chunk_ref, $chunk_id) = @_; ## $chunk_ref contains 2 items, not 1_250_000 my $begin = $chunk_ref->[ 0]; my $end = $chunk_ref->[-1]; ## or $chunk_ref->[1] MCE->printf("%7d .. %8d\n", $begin, $end); } 1, 10_000_000; -- Output 1 .. 1250000 1250001 .. 2500000 2500001 .. 3750000 3750001 .. 5000000 5000001 .. 6250000 6250001 .. 7500000 7500001 .. 8750000 8750001 .. 10000000
Unlike MCE::Map where gather and output order are done for you automatically, the gather method is used to have results sent back to the manager process.
use MCE::Loop chunk_size => 1; ## Output order is not guaranteed. my @a = mce_loop { MCE->gather($_ * 2) } 1..100; print "@a\n\n"; ## Outputs to a hash instead (key, value). my %h1 = mce_loop { MCE->gather($_, $_ * 2) } 1..100; print "@h1{1..100}\n\n"; ## This does the same thing due to chunk_id starting at one. my %h2 = mce_loop { MCE->gather(MCE->chunk_id, $_ * 2) } 1..100; print "@h2{1..100}\n\n";
The gather method can be called multiple times within the block unlike return which would leave the block. Therefore, think of gather as yielding results immediately to the manager process without actually leaving the block.
use MCE::Loop chunk_size => 1, max_workers => 3; my @hosts = qw( hosta hostb hostc hostd hoste ); my %h3 = mce_loop { my ($output, $error, $status); my $host = $_; ## Do something with $host; $output = "Worker ". MCE->wid .": Hello from $host"; if (MCE->chunk_id % 3 == 0) { ## Simulating an error condition local $? = 1; $status = $?; $error = "Error from $host" } else { $status = 0; } ## Ensure unique keys (key, value) when gathering to ## a hash. MCE->gather("$host.out", $output); MCE->gather("$host.err", $error) if (defined $error); MCE->gather("$host.sta", $status); } @hosts; foreach my $host (@hosts) { print $h3{"$host.out"}, "\n"; print $h3{"$host.err"}, "\n" if (exists $h3{"$host.err"}); print "Exit status: ", $h3{"$host.sta"}, "\n\n"; } -- Output Worker 2: Hello from hosta Exit status: 0 Worker 1: Hello from hostb Exit status: 0 Worker 3: Hello from hostc Error from hostc Exit status: 1 Worker 2: Hello from hostd Exit status: 0 Worker 1: Hello from hoste Exit status: 0
The following uses an anonymous array containing 3 elements when gathering data. Serialization is automatic behind the scene.
my %h3 = mce_loop { ... MCE->gather($host, [$output, $error, $status]); } @hosts; foreach my $host (@hosts) { print $h3{$host}->[0], "\n"; print $h3{$host}->[1], "\n" if (defined $h3{$host}->[1]); print "Exit status: ", $h3{$host}->[2], "\n\n"; }
Although MCE::Map comes to mind, one may want additional control when gathering data such as retaining output order.
use MCE::Loop; sub preserve_order { my %tmp; my $order_id = 1; my $gather_ref = $_[0]; return sub { $tmp{ (shift) } = \@_; while (1) { last unless exists $tmp{$order_id}; push @{ $gather_ref }, @{ delete $tmp{$order_id++} }; } return; }; } my @m2; MCE::Loop::init { chunk_size => 'auto', max_workers => 'auto', gather => preserve_order(\@m2) }; mce_loop { my @a; my ($mce, $chunk_ref, $chunk_id) = @_; ## Compute the entire chunk data at once. push @a, map { $_ * 2 } @{ $chunk_ref }; ## Afterwards, invoke the gather feature, which ## will direct the data to the callback function. MCE->gather(MCE->chunk_id, @a); } 1..100000; MCE::Loop::finish; print scalar @m2, "\n";
All 6 models support 'auto' for chunk_size unlike the Core API. Think of the models as the basis for providing JIT for MCE. They create the instance, tune max_workers, and tune chunk_size automatically regardless of the hardware.
The following does the same thing using the Core API.
use MCE; sub preserve_order { ... } my $mce = MCE->new( max_workers => 'auto', chunk_size => 8000, user_func => sub { my @a; my ($mce, $chunk_ref, $chunk_id) = @_; ## Compute the entire chunk data at once. push @a, map { $_ * 2 } @{ $chunk_ref }; ## Afterwards, invoke the gather feature, which ## will direct the data to the callback function. MCE->gather(MCE->chunk_id, @a); } ); my @m2; $mce->process({ gather => preserve_order(\@m2) }, [1..100000]); $mce->shutdown; print scalar @m2, "\n";
Workers remain persistent as much as possible after running. Shutdown occurs automatically when the script terminates. Call finish when workers are no longer needed.
use MCE::Loop; MCE::Loop::init { chunk_size => 20, max_workers => 'auto' }; mce_loop { ... } 1..100; MCE::Loop::finish;
MCE, MCE::Core, MCE::Shared
Mario E. Roy, <marioeroy AT gmail DOT com>
To install MCE, copy and paste the appropriate command in to your terminal.
cpanm
cpanm MCE
CPAN shell
perl -MCPAN -e shell install MCE
For more information on module installation, please visit the detailed CPAN module installation guide.