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 Gentoo.
sh
time parallel 'echo {#}: {}' ::: /usr/bin/* > /dev/null
real 0m5.728s
user 0m2.960s
sys 0m1.310s
--ungroup Option
real 0m4.801s
user 0m2.070s
sys 0m1.290s
sh
time target/release/parallel 'echo {#}: {}' ::: /usr/bin/* > /dev/null
The default options are the slowest options, with all features enabled.
real 0m1.198s
user 0m0.130s
sys 0m0.550s
--no-shell optionsh
time target/release/parallel --no-shell 'echo {#}: {}' ::: /usr/bin/* > /dev/null
A significant amount of overhead is caused by executing commands within the platform's preferred shell. On Unix
systems, that shell is sh, whereas on Windows it is cmd. Disabling shell executing is a good idea if your
command is simple and doesn't require chaining multiple commands.
real 0m0.559s
user 0m0.084s
sys 0m0.372s
--no-shell and --ungroup Optionsh
time target/release/parallel --no-shell --ungroup 'echo {#}: {}' ::: /usr/bin/* > /dev/null
This will achieve utmost optimization at the cost of not having the standard output and error printed in order.
``` real 0m0.575s user 0m0.060s sys 0m0.450s
```
The following syntax is supported:
sh
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.
parallel 'cd {}; echo Directory: {}; echo - {}' // Commands may be chained in the platform\'s shell.
ls | parallel 'echo {}' // If no input arguments are supplied, stdin will be read.
In addition to the command syntax, there are also some options that you can use to configure the load balancer:
- -h, --help: Prints the manual for the application (recommended to pipe it to less).
- -j, --jobs: Defines the number of jobs/threads to run in parallel.
- -u, --ungroup: By default, stdout/stderr buffers are grouped in the order that they are received.
- -n, --no-shell: Disables executing commands within the platform's shell for a performance boost.
- Double quotes and backslashes are used to allow spaces in inputs, similar to standard shells.
- -v, --verbose: Prints information about running processes.
- --num-cpu-cores: Prints the number of CPU cores in the system and exits.
Available syntax options for the placeholders values are: - {}: Each occurrence will be replaced with the name of the input. - {.}: Each occurrence will be replaced with the input, with the extension removed. - {/}: Each occurrence will be replaced with the base name of the input. - {/.}: Each occurrence will be replaced with the base name of the input, with the extension removed. - {//}: Each occurrence will be replaced with the directory name of the input. - {%}: Each occurrence will be replaced with the slot number. - {#}: Each occurrence will be replaced with the job number. - {#^}: Each occurrence will be replaced with the total number of jobs.
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.
sh
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.
sh
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:
```sh
for file in *; do echo $file; done
parallel 'echo {}' ::: * ```
There are a number of methods that you can use to install the application. I provide binary packages for AMD64 systems that are available for download:
I have a personal Gentoo layman overlay that provides this application for installation.
Debian packages are provided on the releases page. If a release is not available, it's because I haven't built it yet with cargo deb.
sh
wget https://github.com/mmstick/parallel/releases/download/0.2.1/parallel_0.2.1_amd64.tar.xz
tar xf parallel_0.2.1.tar.xz
sudo install parallel /usr/local/bin
All of the dependencies are vendored locally, so it is possible to build the packages without Internet access.
If you would like to install the latest release directly to ~/.cargo/bin using the official method.
sh
cargo install parallel
If you would like to install the latest git release:
sh
cargo install --git https://github.com/mmstick/parallel parallel
If you would like to install it system-wide.
sh
wget https://github.com/mmstick/parallel/archive/master.zip
unzip master.zip
cd parallel-master
cargo build --release
sudo install target/release/parallel /usr/local/bin