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GNU Parallel 20160822 ('Og Nomekop') released
GNU Parallel 20160822 ('Og Nomekop') released
Mon, 22 Aug 2016 00:19:01 +0200
GNU Parallel 20160822 ('Og Nomekop') has been released. It is
available for download at: http://ftpmirror.gnu.org/parallel/
Haiku of the month:
Want to monitor
many job outputs at once:
New in this release:
* --tmuxpane opens jobs in panes in tmux. Useful if you want to
monitor progress of less than 100 simultaneous jobs.
* --linebuffer now treats \r as line ending, too.
* Perl changes forces use of floats to be given with leading zero, so
0.1 and not .1
* --xapply renamed to --link.
* Support for pdksh will fade until someone packages it for Ubuntu 16.04
* GNU Parallel was cited in: Exome sequencing of geographically
diverse barley landraces and wild relatives gives insights into
* GNU Parallel was cited in: Vision-Enhanced Lidar Odometry and
* Easy parallelization with GNU parallel
* Facebook V: Predicting Check Ins, Winner's Interview: 2nd Place,
* Parallel import http://www.manitou-mail.org/blog/2016/07/parallel-import/
* Large file batch processing using NodeJs and GNU Parallel
* Bug fixes and man page updates.
GNU Parallel - For people who live life in the parallel lane.
= About GNU Parallel =
GNU Parallel is a shell tool for executing jobs in parallel using one
or more computers. A job can be a single command or a small script
that has to be run for each of the lines in the input. The typical
input is a list of files, a list of hosts, a list of users, a list of
URLs, or a list of tables. A job can also be a command that reads from
a pipe. GNU Parallel can then split the input and pipe it into
commands in parallel.
If you use xargs and tee today you will find GNU Parallel very easy to
use as GNU Parallel is written to have the same options as xargs. If
you write loops in shell, you will find GNU Parallel may be able to
replace most of the loops and make them run faster by running several
jobs in parallel. GNU Parallel can even replace nested loops.
GNU Parallel makes sure output from the commands is the same output as
you would get had you run the commands sequentially. This makes it
possible to use output from GNU Parallel as input for other programs.
You can find more about GNU Parallel at: http://www.gnu.org/s/parallel/
You can install GNU Parallel in just 10 seconds with: (wget -O -
pi.dk/3 || curl pi.dk/3/) | bash
Watch the intro video on http://www.youtube.com/playlist?list=PL284C9FF2488BC6D1
Walk through the tutorial (man parallel_tutorial). Your commandline
will love you for it.
When using programs that use GNU Parallel to process data for
publication please cite:
O. Tange (2011): GNU Parallel - The Command-Line Power Tool, ;login:
The USENIX Magazine, February 2011:42-47.
If you like GNU Parallel:
* Give a demo at your local user group/team/colleagues
* Post the intro videos on Reddit/Diaspora*/forums/blogs/
* Get the merchandise https://www.gnu.org/s/parallel/merchandise.html
* Request or write a review for your favourite blog or magazine
* Request or build a package for your favourite distribution (if it is
not already there)
* Invite me for your next conference
If you use programs that use GNU Parallel for research:
* Please cite GNU Parallel in you publications (use --citation)
If GNU Parallel saves you money:
* (Have your company) donate to FSF https://my.fsf.org/donate/
= About GNU SQL =
GNU sql aims to give a simple, unified interface for accessing
databases through all the different databases' command line clients.
So far the focus has been on giving a common way to specify login
information (protocol, username, password, hostname, and port number),
size (database and table size), and running queries.
The database is addressed using a DBURL. If commands are left out you
will get that database's interactive shell.
When using GNU SQL for a publication please cite:
O. Tange (2011): GNU SQL - A Command Line Tool for Accessing Different
Databases Using DBURLs, ;login: The USENIX Magazine, April 2011:29-32.
= About GNU Niceload =
GNU niceload slows down a program when the computer load average (or
other system activity) is above a certain limit. When the limit is
reached the program will be suspended for some time. If the limit is a
soft limit the program will be allowed to run for short amounts of
time before being suspended again. If the limit is a hard limit the
program will only be allowed to run when the system is below the
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