|FROM ||Ruben Safir
|SUBJECT ||Re: [Learn] GNU Parallel 20161022 ('Matthew') released [stable]
|From learn-bounces-at-nylxs.com Sun Nov 6 18:20:37 2016
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From: Ruben Safir
Date: Sun, 6 Nov 2016 18:20:34 -0500
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Subject: Re: [Learn] GNU Parallel 20161022 ('Matthew') released [stable]
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On Sat, 22 Oct 2016 09:11:29 -0700, ole.tange wrote:
> GNU Parallel 20161022 ('Matthew') [stable] has been released. It is
> available for download at: http://ftpmirror.gnu.org/parallel/
> No new functionality was introduced so this is a good candidate for a
> stable release.
> Haiku of the month:
> Speed is good for you Multi speed is better still Use GNU Parallel
> -- Ole Tange
> New in this release:
> * First command no longer gets stdin as it causes unpredictable issues.
> * GNU Parallel was cited in: Efficiently parallelized modeling of
> tightly focused, large bandwidth laser pulses
> * How to crunch lots of geodata in parallel
> * GNU parallel is my new toaster
> * 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
> 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/
> Identi.ca/Google+/Twitter/Facebook/Linkedin/mailing lists * 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 limit.
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