mmstick / parallel
- суббота, 27 августа 2016 г. в 03:13:51
Rust
Inspired by GNU Parallel, a command-line CPU load balancer written in Rust.
This is an attempt at recreating the functionality of GNU Parallel in Rust under a MIT license. The end goal will be to support much of the functionality of GNU Parallel and then to extend the functionality further for the next generation of command-line utilities written in Rust.
Here are some benchmarks from an i5-2410M laptop running Ubuntu 16.04.
parallel 'echo {%}: {}' ::: /usr/bin/* > /dev/nullreal 0m5.911s
user 0m2.752s
sys 0m1.764s
real 0m0.559s
user 0m0.084s
sys 0m0.372s
Parallel does not currently support reading from stdin at this time. However, it does support parsing input arguments from the command line to achieve the same effect. The following syntax is supported:
parallel 'echo {}' ::: * // {} will be replaced with each input found.
parallel echo ::: * // If no placeholders are used, it is automatically assumed.
parallel ::: "echo 1" "echo 2" "echo 3" // If no command is supplied, the input arguments become commands.In addition to the command syntax, there are also some options that you can use to configure the load balancer:
Available syntax options for the placeholders values are:
ffmpeg is a highly useful application for converting music and videos. However, audio transcoding is limited to a a single core. If you have a large FLAC archive and you wanted to compress it into the efficient Opus codec, it would take forever with the fastest processor to complete, unless you were to take advantage of all cores in your CPU.
parallel 'ffmpeg -v 0 -i {} -c:a libopus -b:a 128k {.}.opus' ::: $(find -type f -name '*.flac')VP9 has one glaring flaw in regards to encoding: it can only use about three cores at any given point in time. If you have an eight core processor and a dozen or more episodes of a TV series to transcode, you can use the parallel program to run three jobs at the same time, provided you also have enough memory for that.
vp9_params="-c:v libvpx-vp9 -tile-columns 6 -frame-parallel 1 -rc_lookahead 25 -threads 4 -speed 1 -b:v 0 -crf 18"
opus_params="-c:a libopus -b:a 128k"
parallel -j 3 "ffmpeg -v 0 -i {} $vp9_params $opus_params -f webm {.}.webm" ::: $(find -type f -name '*.mkv')There are a lot of commands that will take an input and then consume an entire CPU core as it processes the input. However, sometimes you have dozens, hundreds, or even thousands of files that you want to process. The standard solution would be to construct a for loop and run your jobs serially one at a time. However, this would take forever with processes that only make use of a single core. Another solution is to construct the same for loop but to have your shell run it in the background. The problem with that solution is that if there are a lot of inputs to process, you will end locking up your system and crashing your jobs due to OOM (out of memory) errors.
A complicated setup that I have seen people perform is to create as many separate lists or directories as they have CPU cores, and then manually spinning up a terminal and copying and pasting the same for loop into each one. The issue with this approach is that it takes a lot of time to set this up, and because some tasks finish much sooner than others, you may end up with several cores sitting and waiting because they've completed all of their assigned inputs while other cores are busy with many more tasks left to perform.
Instead of processing files using a for loop, you can use a load balancer like parallel to distribute jobs evenly
to every core in the system, which will only pass new values when a core has finished it's task. This has the benefit
that you can process inputs chronologically, and because some inputs may finish sooner than others, you can ensure
that every core has a job to process at any given point in time. Not to mention, it's about as easy to write as a
for loop:
# This is a for loop
for file in *; do echo $file; done
# This is a parallel version of that for loop
parallel 'echo {}' ::: *