NAME
MCE::Examples - Various examples and demonstration
VERSION
This document describes MCE::Examples version 1.699_009
INCLUDED WITH THE DISTRIBUTION
A wrapper script for parallelizing the grep binary. Hence, processing is done by the binary, not Perl. This wrapper resides under the bin directory.
mce_grep
A wrapper script
with
support
for
the following C binaries.
agrep,
grep
, egrep, fgrep, and tre-agrep
Chunking may be applied either at the [file] level,
for
large
file(s), or at the [list] level
when
parsing many files
recursively.
The gain in performance is noticeable
for
expensive patterns,
especially
with
agrep and tre-agrep.
MCE EXAMPLES ON GITHUB
The examples directory, beginning with 1.700, is maintained separately at a Github repository https://github.com/marioroy/mce-examples and no longer included with the Perl MCE distribution.
PROCESSING INPUT DATA
The next section describes ways to process input data in MCE.
CHUNK_SIZE => 1 (in essence, disabling chunking)
Imagine a long running process and wanting to parallelize an array against a pool of workers. The sequence option may be used if simply wanting to loop through a sequence of numbers instead.
Below, a callback function is used for displaying results. The logic shows how one can output results immediately while still preserving output order as if processing serially. The %tmp hash is a temporary cache for out-of-order results.
use
MCE;
## Return an iterator for preserving output order.
sub
preserve_order {
my
(
%result_n
,
%result_d
);
my
$order_id
= 1;
return
sub
{
my
(
$chunk_id
,
$n
,
$data
) =
@_
;
$result_n
{
$chunk_id
} =
$n
;
$result_d
{
$chunk_id
} =
$data
;
while
(1) {
last
unless
exists
$result_d
{
$order_id
};
printf
"n: %5d sqrt(n): %7.3f\n"
,
$result_n
{
$order_id
},
$result_d
{
$order_id
};
delete
$result_n
{
$order_id
};
delete
$result_d
{
$order_id
};
$order_id
++;
}
return
;
};
}
## Use $chunk_ref->[0] or $_ to retrieve the element.
my
@input_data
= (0 .. 18000 - 1);
my
$mce
= MCE->new(
gather
=> preserve_order,
input_data
=> \
@input_data
,
chunk_size
=> 1,
max_workers
=> 3,
user_func
=>
sub
{
my
(
$mce
,
$chunk_ref
,
$chunk_id
) =
@_
;
MCE->gather(
$chunk_id
,
$_
,
sqrt
(
$_
));
}
);
$mce
->run;
This does the same thing using the foreach "sugar" method.
use
MCE;
sub
preserve_order {
...
}
my
$mce
= MCE->new(
chunk_size
=> 1,
max_workers
=> 3,
gather
=> preserve_order
);
## Use $chunk_ref->[0] or $_ to retrieve the element.
my
@input_data
= (0 .. 18000 - 1);
$mce
->
foreach
( \
@input_data
,
sub
{
my
(
$mce
,
$chunk_ref
,
$chunk_id
) =
@_
;
MCE->gather(
$chunk_id
,
$_
,
sqrt
(
$_
));
});
The 2 examples described above were done using the Core API. MCE 1.5 comes with several models. The MCE::Loop model is used below.
use
MCE::Loop;
sub
preserve_order {
...
}
MCE::Loop::init {
chunk_size
=> 1,
max_workers
=> 3,
gather
=> preserve_order
};
## Use $chunk_ref->[0] or $_ to retrieve the element.
my
@input_data
= (0 .. 18000 - 1);
mce_loop {
my
(
$mce
,
$chunk_ref
,
$chunk_id
) =
@_
;
MCE->gather(
$chunk_id
,
$_
,
sqrt
(
$_
));
}
@input_data
;
MCE::Loop::finish;
CHUNKING INPUT DATA
Chunking has the effect of reducing IPC overhead by many folds. A chunk containing $chunk_size items is sent to the next available worker.
use
MCE;
## Return an iterator for preserving output order.
sub
preserve_order {
my
(
%result_n
,
%result_d
,
$size
);
my
$order_id
= 1;
return
sub
{
my
(
$chunk_id
,
$n_ref
,
$data_ref
) =
@_
;
$result_n
{
$chunk_id
} =
$n_ref
;
$result_d
{
$chunk_id
} =
$data_ref
;
while
(1) {
last
unless
exists
$result_d
{
$order_id
};
$size
= @{
$result_d
{
$order_id
} };
for
(0 ..
$size
- 1) {
printf
"n: %5d sqrt(n): %7.3f\n"
,
$result_n
{
$order_id
}->[
$_
],
$result_d
{
$order_id
}->[
$_
];
}
delete
$result_n
{
$order_id
};
delete
$result_d
{
$order_id
};
$order_id
++;
}
return
;
};
}
## Chunking requires one to loop inside the code block.
my
@input_data
= (0 .. 18000 - 1);
my
$mce
= MCE->new(
gather
=> preserve_order,
input_data
=> \
@input_data
,
chunk_size
=> 500,
max_workers
=> 3,
user_func
=>
sub
{
my
(
$mce
,
$chunk_ref
,
$chunk_id
) =
@_
;
my
(
@n
,
@result
);
foreach
( @{
$chunk_ref
} ) {
push
@n
,
$_
;
push
@result
,
sqrt
(
$_
);
}
MCE->gather(
$chunk_id
, \
@n
, \
@result
);
}
);
$mce
->run;
This does the same thing using the forchunk "sugar" method.
use
MCE;
sub
preserve_order {
...
}
my
$mce
= MCE->new(
chunk_size
=> 500,
max_workers
=> 3,
gather
=> preserve_order
);
## Chunking requires one to loop inside the code block.
my
@input_data
= (0 .. 18000 - 1);
$mce
->forchunk( \
@input_data
,
sub
{
my
(
$mce
,
$chunk_ref
,
$chunk_id
) =
@_
;
my
(
@n
,
@result
);
foreach
( @{
$chunk_ref
} ) {
push
@n
,
$_
;
push
@result
,
sqrt
(
$_
);
}
MCE->gather(
$chunk_id
, \
@n
, \
@result
);
});
Finally, chunking with the MCE::Loop model.
use
MCE::Loop;
sub
preserve_order {
...
}
MCE::Loop::init {
chunk_size
=> 500,
max_workers
=> 3,
gather
=> preserve_order
};
## Chunking requires one to loop inside the code block.
my
@input_data
= (0 .. 18000 - 1);
mce_loop {
my
(
$mce
,
$chunk_ref
,
$chunk_id
) =
@_
;
my
(
@n
,
@result
);
foreach
( @{
$chunk_ref
} ) {
push
@n
,
$_
;
push
@result
,
sqrt
(
$_
);
}
MCE->gather(
$chunk_id
, \
@n
, \
@result
);
}
@input_data
;
MCE::Loop::finish;
DEMO APPLYING SEQUENCES WITH USER_TASKS
The following is an extract from the seq_demo.pl example included with MCE. Think of having several MCEs running in parallel. The sequence and chunk_size options may be specified uniquely per each task.
The input scalar $_ (not shown below) contains the same value as $seq_n in user_func.
use
MCE;
## Run with seq_demo.pl | sort
sub
user_func {
my
(
$mce
,
$seq_n
,
$chunk_id
) =
@_
;
my
$wid
= MCE->wid;
my
$task_id
= MCE->task_id;
my
$task_wid
= MCE->task_wid;
if
(
ref
$seq_n
eq
'ARRAY'
) {
## seq_n or $_ is an array reference when chunk_size > 1
foreach
(@{
$seq_n
}) {
MCE->
printf
(
"task_id %d: seq_n %s: chunk_id %d: wid %d: task_wid %d\n"
,
$task_id
,
$_
,
$chunk_id
,
$wid
,
$task_wid
);
}
}
else
{
MCE->
printf
(
"task_id %d: seq_n %s: chunk_id %d: wid %d: task_wid %d\n"
,
$task_id
,
$seq_n
,
$chunk_id
,
$wid
,
$task_wid
);
}
sleep
0.003;
return
;
}
## Each task can be configured uniquely.
my
$mce
= MCE->new(
user_tasks
=> [{
max_workers
=> 2,
chunk_size
=> 1,
sequence
=> {
begin
=> 11,
end
=> 19,
step
=> 1 },
user_func
=> \
&user_func
},{
max_workers
=> 2,
chunk_size
=> 5,
sequence
=> {
begin
=> 21,
end
=> 29,
step
=> 1 },
user_func
=> \
&user_func
},{
max_workers
=> 2,
chunk_size
=> 3,
sequence
=> {
begin
=> 31,
end
=> 39,
step
=> 1 },
user_func
=> \
&user_func
}]
);
$mce
->run;
-- Output
task_id 0: seq_n 11: chunk_id 1: wid 2: task_wid 2
task_id 0: seq_n 12: chunk_id 2: wid 1: task_wid 1
task_id 0: seq_n 13: chunk_id 3: wid 2: task_wid 2
task_id 0: seq_n 14: chunk_id 4: wid 1: task_wid 1
task_id 0: seq_n 15: chunk_id 5: wid 2: task_wid 2
task_id 0: seq_n 16: chunk_id 6: wid 1: task_wid 1
task_id 0: seq_n 17: chunk_id 7: wid 2: task_wid 2
task_id 0: seq_n 18: chunk_id 8: wid 1: task_wid 1
task_id 0: seq_n 19: chunk_id 9: wid 2: task_wid 2
task_id 1: seq_n 21: chunk_id 1: wid 3: task_wid 1
task_id 1: seq_n 22: chunk_id 1: wid 3: task_wid 1
task_id 1: seq_n 23: chunk_id 1: wid 3: task_wid 1
task_id 1: seq_n 24: chunk_id 1: wid 3: task_wid 1
task_id 1: seq_n 25: chunk_id 1: wid 3: task_wid 1
task_id 1: seq_n 26: chunk_id 2: wid 4: task_wid 2
task_id 1: seq_n 27: chunk_id 2: wid 4: task_wid 2
task_id 1: seq_n 28: chunk_id 2: wid 4: task_wid 2
task_id 1: seq_n 29: chunk_id 2: wid 4: task_wid 2
task_id 2: seq_n 31: chunk_id 1: wid 5: task_wid 1
task_id 2: seq_n 32: chunk_id 1: wid 5: task_wid 1
task_id 2: seq_n 33: chunk_id 1: wid 5: task_wid 1
task_id 2: seq_n 34: chunk_id 2: wid 6: task_wid 2
task_id 2: seq_n 35: chunk_id 2: wid 6: task_wid 2
task_id 2: seq_n 36: chunk_id 2: wid 6: task_wid 2
task_id 2: seq_n 37: chunk_id 3: wid 5: task_wid 1
task_id 2: seq_n 38: chunk_id 3: wid 5: task_wid 1
task_id 2: seq_n 39: chunk_id 3: wid 5: task_wid 1
GLOBALLY SCOPED VARIABLES AND MCE MODELS
It is possible that Perl may create a new code ref on subsequent runs causing MCE models to re-spawn. One solution to this is to declare global variables, referenced by workers, with "our" instead of "my".
Let's take a look. The $i variable is declared with my and being reference in both user_begin and mce_loop blocks. This will cause Perl to create a new code ref for mce_loop on subsequent runs.
use
MCE::Loop;
my
$i
= 0;
## <-- this is the reason, try our instead
MCE::Loop::init {
user_begin
=>
sub
{
"process_id: $$\n"
if
MCE->wid == 1;
$i
++;
},
chunk_size
=> 1,
max_workers
=>
'auto'
,
};
for
(1..2) {
## Perl creates another code block ref causing workers
## to re-spawn on subsequent runs.
"\n"
; mce_loop {
"$i: $_\n"
} 1..4;
}
MCE::Loop::finish;
-- Output
process_id: 51380
1: 1
1: 2
1: 3
1: 4
process_id: 51388
1: 1
1: 2
1: 3
1: 4
By making the one line change, we see that workers persist for the duration of the script.
use
MCE::Loop;
our
$i
= 0;
## <-- changed my to our
MCE::Loop::init {
user_begin
=>
sub
{
"process_id: $$\n"
if
MCE->wid == 1;
$i
++;
},
chunk_size
=> 1,
max_workers
=>
'auto'
,
};
for
(1..2) {
## Workers persist between runs. No re-spawning.
"\n"
; mce_loop {
"$i: $_\n"
} 1..4;
}
-- Output
process_id: 51457
1: 1
1: 2
1: 4
1: 3
process_id: 51457
2: 1
2: 2
2: 3
2: 4
One may alternatively specify a code reference to existing routines for user_begin and mce_loop. Take notice of the comma after \&_func though.
use
MCE::Loop;
my
$i
= 0;
## my (ok)
sub
_begin {
"process_id: $$\n"
if
MCE->wid == 1;
$i
++;
}
sub
_func {
"$i: $_\n"
;
}
MCE::Loop::init {
user_begin
=> \
&_begin
,
chunk_size
=> 1,
max_workers
=>
'auto'
,
};
for
(1..2) {
"\n"
; mce_loop \
&_func
, 1..4;
}
MCE::Loop::finish;
-- Output
process_id: 51626
1: 1
1: 2
1: 3
1: 4
process_id: 51626
2: 1
2: 2
2: 3
2: 4
MONTE CARLO SIMULATION
There is an article on the web (search for comp.lang.perl.misc MCE) suggesting that MCE::Examples does not cover a simple simulation scenario. This section demonstrates just that.
The serial code is based off the one by "gamo". A sleep is added to imitate extra CPU time. The while loop is wrapped within a for loop to run 10 times. The random number generator is seeded as well.
srand
5906;
my
(
$var
,
$foo
,
$bar
) = (1, 2, 3);
my
(
$r
,
$a
,
$b
);
my
$start
=
time
;
for
(1..10) {
while
(1) {
$r
=
rand
;
$a
=
$r
* (
$var
+
$foo
+
$bar
);
$b
=
sqrt
(
$var
+
$foo
+
$bar
);
last
if
(
$a
<
$b
+ 0.001 &&
$a
>
$b
- 0.001);
sleep
0.002;
}
"$r -> $a\n"
;
}
my
$end
=
time
;
printf
{
*STDERR
}
"\n## compute time: %0.03f secs\n\n"
,
$end
-
$start
;
-- Output
0.408246276657106 -> 2.44947765994264
0.408099657137821 -> 2.44859794282693
0.408285842931324 -> 2.44971505758794
0.408342292008765 -> 2.45005375205259
0.408333076522673 -> 2.44999845913604
0.408344266898869 -> 2.45006560139321
0.408084104120526 -> 2.44850462472316
0.408197400014714 -> 2.44918440008828
0.408344783704855 -> 2.45006870222913
0.408248062985479 -> 2.44948837791287
## compute time: 93.049 secs
Next, we'd do the same with MCE. The demonstration requires at least MCE 1.509 to run properly. Folks on prior releases (1.505 - 1.508) will not see output for the 2nd run and beyond.
use
MCE::Loop;
srand
5906;
## Configure MCE. Move common variables inside the user_begin
## block when not needed by the manager process.
MCE::Loop::init {
user_begin
=>
sub
{
our
(
$var
,
$foo
,
$bar
) = (1, 2, 3);
},
chunk_size
=> 1,
max_workers
=>
'auto'
,
input_data
=> \
&_input
,
gather
=> \
&_gather
};
## Callback functions.
my
(
$done
,
$r
,
$a
);
sub
_input {
return
if
$done
;
return
rand
;
}
sub
_gather {
my
(
$_r
,
$_a
,
$_b
) =
@_
;
return
if
$done
;
if
(
$_a
<
$_b
+ 0.001 &&
$_a
>
$_b
- 0.001) {
(
$done
,
$r
,
$a
) = (1,
$_r
,
$_a
);
}
return
;
}
## Compute in parallel.
my
$start
=
time
;
for
(1..10) {
$done
= 0;
## Reset $done before running
mce_loop {
# my ($mce, $chunk_ref, $chunk_id) = @_;
# my $r = $chunk_ref->[0];
my
$r
=
$_
;
## Valid due to chunk_size => 1
my
$a
=
$r
* (
$var
+
$foo
+
$bar
);
my
$b
=
sqrt
(
$var
+
$foo
+
$bar
);
MCE->gather(
$r
,
$a
,
$b
);
sleep
0.002;
};
"$r -> $a\n"
;
}
printf
"\n## compute time: %0.03f secs\n\n"
,
time
-
$start
;
-- Output
0.408246276657106 -> 2.44947765994264
0.408099657137821 -> 2.44859794282693
0.408285842931324 -> 2.44971505758794
0.408342292008765 -> 2.45005375205259
0.408333076522673 -> 2.44999845913604
0.408344266898869 -> 2.45006560139321
0.408084104120526 -> 2.44850462472316
0.408197400014714 -> 2.44918440008828
0.408344783704855 -> 2.45006870222913
0.408248062985479 -> 2.44948837791287
## compute time: 12.990 secs
Well, there you have it. MCE is able to complete the same simulation many times faster.
MANY WORKERS RUNNING IN PARALLEL
There are occasions when one wants several workers to run in parallel without having to specify input_data or seqeunce. These two options are optional in MCE. The "do" and "sendto" methods, for sending data to the manager process, are demonstrated below. Both process serially by the manager process on a first come, first serve basis.
sub
report_stats {
my
(
$wid
,
$msg
,
$h_ref
) =
@_
;
"Worker $wid says $msg: "
,
$h_ref
->{
"counter"
},
"\n"
;
}
mce_flow
sub
{
my
(
$mce
) =
@_
;
my
$wid
= MCE->wid;
if
(
$wid
== 1) {
my
%h
= (
"counter"
=> 0);
while
(1) {
$h
{
"counter"
} += 1;
MCE->
do
(
"report_stats"
,
$wid
,
"Hey there"
, \
%h
);
last
if
(
$h
{
"counter"
} == 4);
sleep
2;
}
}
else
{
my
%h
= (
"counter"
=> 0);
while
(1) {
$h
{
"counter"
} += 1;
MCE->
do
(
"report_stats"
,
$wid
,
"Welcome.."
, \
%h
);
last
if
(
$h
{
"counter"
} == 2);
sleep
4;
}
}
MCE->
(\
*STDERR
,
"Worker $wid is exiting\n"
);
};
-- Output
Note how worker 2 comes first in the 2nd run below.
$ ./demo.pl
Worker 1 says Hey there: 1
Worker 2 says Welcome..: 1
Worker 3 says Welcome..: 1
Worker 4 says Welcome..: 1
Worker 1 says Hey there: 2
Worker 2 says Welcome..: 2
Worker 3 says Welcome..: 2
Worker 1 says Hey there: 3
Worker 2 is exiting
Worker 3 is exiting
Worker 4 says Welcome..: 2
Worker 4 is exiting
Worker 1 says Hey there: 4
Worker 1 is exiting
$ ./demo.pl
Worker 2 says Welcome..: 1
Worker 1 says Hey there: 1
Worker 4 says Welcome..: 1
Worker 3 says Welcome..: 1
Worker 1 says Hey there: 2
Worker 2 says Welcome..: 2
Worker 4 says Welcome..: 2
Worker 3 says Welcome..: 2
Worker 2 is exiting
Worker 4 is exiting
Worker 1 says Hey there: 3
Worker 3 is exiting
Worker 1 says Hey there: 4
Worker 1 is exiting
INDEX
AUTHOR
Mario E. Roy, <marioeroy AT gmail DOT com>