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GNU Parallel 20161222 ('Castro') released


From: Ole Tange
Subject: GNU Parallel 20161222 ('Castro') released
Date: Thu, 22 Dec 2016 14:31:10 +0100

GNU Parallel 20161222 ('Castro') has been released. It is available
for download at: http://ftpmirror.gnu.org/parallel/

* --results foo.csv will save output as a CSV-file. Can be directly
imported into R or LibreCalc.

* When using --pipepart a negative --block-size is not interpreted as
a block size but as the number of blocks each jobslot should have.

* --sqlmaster/--sqlandworker will append jobs to the DBURL if the
DBURL is prepended with +.

* GNU Parallel was cited in: A cloud-based workflow to quantify
transcript-expression levels in public cancer compendia
http://www.nature.com/articles/srep39259

* GNU Parallel was cited in: Learning string distance with smoothing
for OCR spelling correction
http://paperity.org/p/78557440/learning-string-distance-with-smoothing-for-ocr-spelling-correction

* GNU Parallel was cited in: Transient compute clustering with GNU
Parallel and sshfs
https://gist.github.com/Brainiarc7/24c966c8a001061ee86cc4bc05826bf4

* GNU Parallel was cited in: Determination of crystal structures of
proteins of unknown identity using a marathon molecular replacement
procedure: Structure of Stenotrophomonas maltophilia phosphate-binding
protein 
https://www.researchgate.net/publication/308186413_Determination_of_crystal_structures_of_proteins_of_unknown_identity_using_a_marathon_molecular_replacement_procedure_Structure_of_Stenotrophomonas_maltophilia_phosphate-binding_protein

* GNU Parallel was cited in: The Outer Solar System Origins Survey: I.
Design and First-Quarter Discoveries
https://arxiv.org/pdf/1511.02895v2.pdf

* GNU Parallel was cited in: Large-scale benchmarking reveals false
discoveries and count transformation sensitivity in 16S rRNA gene
amplicon data analysis methods used in microbiome studies
http://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-016-0208-8

* GNU Parallel was cited in: Decomposing Images into Layers via
RGB-space Geometry
https://cs.gmu.edu/~ygingold/singleimage/Decomposing%20Images%20into%20Layers%20via%20RGB-space%20Geometry%20(Tan%20et%20al%202016%20TOG)%20small.pdf

* 4 Ways to Batch Convert Your PNG to JPG and Vice-Versa
http://www.tecmint.com/linux-image-conversion-tools/

* All's Fair in Love and Distributed Storage
http://cohesity.com/blog/alls-fair-love-distributed-storage/

* How can I use GNU Parallel to run a lot of commands in parallel
https://www.msi.umn.edu/support/faq/how-can-i-use-gnu-parallel-run-lot-commands-parallel

* 정해영의 블로그 - JEONG Haeyoung's blog
http://blog.genoglobe.com/2016/11/gnu-parallel.html

* 在Linux下将PNG和JPG批量互转的四种方法 http://os.51cto.com/art/201612/524182.htm

* Running in parallel http://tomkimpson.com/howto/gnuparallel/

* Taco Bell Parallel Programming
https://giorgos.sealabs.net/taco-bell-parallel-programming.html

* 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/
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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