This tutorial shows off much of GNU Parallel's functionality. The tutorial is meant to learn the options in GNU Parallel. The tutorial is not to show realistic examples from the real world.
Spend an hour walking through the tutorial. Your command line will love you for it.
To run this tutorial you must have the following:
Install the newest version with:
(wget -O - pi.dk/3 || curl pi.dk/3/) | bash
This will also install the newest version of the tutorial:
man parallel_tutorial
Most of the tutorial will work on older versions, too.
The file can be generated by:
parallel -k echo ::: A B C > abc-file
The file can be generated by:
parallel -k echo ::: D E F > def-file
The file can be generated by:
perl -e 'printf "A\0B\0C\0"' > abc0-file
The file can be generated by:
perl -e 'printf "A_B_C_"' > abc_-file
The file can be generated by:
perl -e 'printf "f1\tf2\nA\tB\nC\tD\n"' > tsv-file.tsv
The file can be generated by:
perl -e 'for(1..30000){print "$_\n"}' > num30000
The file can be generated by:
perl -e 'for(1..1000000){print "$_\n"}' > num1000000
The file can be generated by:
(echo %head1; echo %head2; perl -e 'for(1..10){print "$_\n"}') > num_%header
SERVER1=server.example.com SERVER2=server2.example.net
You must be able to:
ssh $SERVER1 echo works ssh $SERVER2 echo works
It can be setup by running 'ssh-keygen -t dsa; ssh-copy-id $SERVER1' and using an empty pass phrase.
GNU Parallel reads input from input sources. These can be files, the command line, and stdin (standard input or a pipe).
Input can be read from the command line:
parallel echo ::: A B C
Output (the order may be different because the jobs are run in parallel):
A B C
The input source can be a file:
parallel -a abc-file echo
Output: Same as above.
STDIN (standard input) can be the input source:
cat abc-file | parallel echo
Output: Same as above.
GNU Parallel can take multiple input sources given on the command line. GNU Parallel then generates all combinations of the input sources:
parallel echo ::: A B C ::: D E F
Output (the order may be different):
A D A E A F B D B E B F C D C E C F
The input sources can be files:
parallel -a abc-file -a def-file echo
Output: Same as above.
STDIN (standard input) can be one of the input sources using '-':
cat abc-file | parallel -a - -a def-file echo
Output: Same as above.
Instead of -a files can be given after '::::':
cat abc-file | parallel echo :::: - def-file
Output: Same as above.
::: and :::: can be mixed:
parallel echo ::: A B C :::: def-file
Output: Same as above.
With --xapply you can get one argument from each input source:
parallel --xapply echo ::: A B C ::: D E F
Output (the order may be different):
A D B E C F
If one of the input sources is too short, its values will wrap:
parallel --xapply echo ::: A B C D E ::: F G
Output (the order may be different):
A F B G C F D G E F
GNU Parallel can use other separators than ::: or ::::. This is typically useful if ::: or :::: is used in the command to run:
parallel --arg-sep ,, echo ,, A B C :::: def-file
Output (the order may be different):
A D A E A F B D B E B F C D C E C F
Changing the argument file separator:
parallel --arg-file-sep // echo ::: A B C // def-file
Output: Same as above.
GNU Parallel will normally treat a full line as a single argument: It uses \n as argument delimiter. This can be changed with -d:
parallel -d _ echo :::: abc_-file
Output (the order may be different):
A B C
NULL can be given as \0:
parallel -d '\0' echo :::: abc0-file
Output: Same as above.
A shorthand for -d '\0' is -0 (this will often be used to read files from find ... -print0):
parallel -0 echo :::: abc0-file
Output: Same as above.
GNU Parallel can stop reading when it encounters a certain value:
parallel -E stop echo ::: A B stop C D
Output:
A B
Using --no-run-if-empty GNU Parallel will skip empty lines.
(echo 1; echo; echo 2) | parallel --no-run-if-empty echo
Output:
1 2
If no command is given after parallel the arguments themselves are treated as commands:
parallel ::: ls 'echo foo' pwd
Output (the order may be different):
[list of files in current dir] foo [/path/to/current/working/dir]
The command can be a script, a binary or a Bash function if the function is exported using 'export -f':
# Only works in Bash and only if $SHELL=.../bash
my_func() {
echo in my_func $1
}
export -f my_func
parallel my_func ::: 1 2 3
Output (the order may be different):
in my_func 1 in my_func 2 in my_func 3
GNU Parallel has several replacement strings. If no replacement strings are used the default is to append {}:
parallel echo ::: A/B.C
Output:
A/B.C
The default replacement string is {}:
parallel echo {} ::: A/B.C
Output:
A/B.C
The replacement string {.} removes the extension:
parallel echo {.} ::: A/B.C
Output:
A/B
The replacement string {/} removes the path:
parallel echo {/} ::: A/B.C
Output:
B.C
The replacement string {//} keeps only the path:
parallel echo {//} ::: A/B.C
Output:
A
The replacement string {/.} removes the path and the extension:
parallel echo {/.} ::: A/B.C
Output:
B
The replacement string {#} gives the job number:
parallel echo {#} ::: A B C
Output (the order may be different):
1 2 3
The replacement string {%} gives the job slot number (between 1 and number of jobs to run in parallel):
parallel -j 2 echo {%} ::: A B C
Output (the order may be different):
1 2 1
The replacement string {} can be changed with -I:
parallel -I ,, echo ,, ::: A/B.C
Output:
A/B.C
The replacement string {.} can be changed with --extensionreplace:
parallel --extensionreplace ,, echo ,, ::: A/B.C
Output:
A/B
The replacement string {/} can be replaced with --basenamereplace:
parallel --basenamereplace ,, echo ,, ::: A/B.C
Output:
B.C
The replacement string {//} can be changed with --dirnamereplace:
parallel --dirnamereplace ,, echo ,, ::: A/B.C
Output:
A
The replacement string {/.} can be changed with --basenameextensionreplace:
parallel --basenameextensionreplace ,, echo ,, ::: A/B.C
Output:
B
The replacement string {#} can be changed with --seqreplace:
parallel --seqreplace ,, echo ,, ::: A B C
Output (the order may be different):
1 2 3
The replacement string {%} can be changed with --slotreplace:
parallel -j2 --slotreplace ,, echo ,, ::: A B C
Output (the order may be different):
1 2 1
With multiple input sources the argument from the individual input sources can be access with {number}:
parallel echo {1} and {2} ::: A B ::: C D
Output (the order may be different):
A and C A and D B and C B and D
The positional replacement strings can also be modified using / // /. and .:
parallel echo /={1/} //={1//} /.={1/.} .={1.} ::: A/B.C D/E.F
Output (the order may be different):
/=B.C //=A /.=B .=A/B /=E.F //=D /.=E .=D/E
If a position is negative, it will refer to the input source counted from behind:
parallel echo 1={1} 2={2} 3={3} -1={-1} -2={-2} -3={-3} ::: A B ::: C D ::: E F
Output (the order may be different):
1=A 2=C 3=E -1=E -2=C -3=A 1=A 2=C 3=F -1=F -2=C -3=A 1=A 2=D 3=E -1=E -2=D -3=A 1=A 2=D 3=F -1=F -2=D -3=A 1=B 2=C 3=E -1=E -2=C -3=B 1=B 2=C 3=F -1=F -2=C -3=B 1=B 2=D 3=E -1=E -2=D -3=B 1=B 2=D 3=F -1=F -2=D -3=B
The columns in a file can be bound to positional replacement strings using --colsep. Here the columns are separated with TAB (\t):
parallel --colsep '\t' echo 1={1} 2={2} :::: tsv-file.tsv
Output (the order may be different):
1=f1 2=f2 1=A 2=B 1=C 2=D
With --header GNU Parallel will use the first value of the input source as the name of the replacement string. Only the non-modified version {} is supported:
parallel --header : echo f1={f1} f2={f2} ::: f1 A B ::: f2 C D
Output (the order may be different):
f1=A f2=C f1=A f2=D f1=B f2=C f1=B f2=D
It is useful with --colsep for processing files with TAB separated values:
parallel --header : --colsep '\t' echo f1={f1} f2={f2} :::: tsv-file.tsv
Output (the order may be different):
f1=A f2=B f1=C f2=D
With --xargs will GNU Parallel fit as many arguments as possible on a single line:
cat num30000 | parallel --xargs echo | wc -l
Output:
2
The 30000 arguments fitted on 2 lines.
The maximal length of a single line can be set with -s. With a maximal line length of 10000 chars 17 commands will be run:
cat num30000 | parallel --xargs -s 10000 echo | wc -l
Output:
17
For better parallelism GNU Parallel can distribute the arguments between all the parallel jobs when end of file is met.
Below GNU Parallel reads the last argument when generating the second job. When GNU Parallel reads the last argument, it spreads all the arguments for the second job over 4 jobs instead, as 4 parallel jobs are requested.
The first job will be the same as the --xargs example above, but the second job will be split into 4 evenly sized jobs, resulting in a total of 5 jobs:
cat num30000 | parallel --jobs 4 -m echo | wc -l
Output:
5
This is even more visible when running 4 jobs with 10 arguments. The 10 arguments are being spread over 4 jobs:
parallel --jobs 4 -m echo ::: {1..10}
Output:
1 2 3 4 5 6 7 8 9 10
A replacement string can be part of a word. -m will not repeat the context:
parallel --jobs 4 -m echo pre-{}-post ::: A B C D E F G
Output (the order may be different):
pre-A B-post pre-C D-post pre-E F-post pre-G-post
To repeat the context use -X which otherwise works like -m:
parallel --jobs 4 -X echo pre-{}-post ::: A B C D E F G
Output (the order may be different):
pre-A-post pre-B-post pre-C-post pre-D-post pre-E-post pre-F-post pre-G-post
To limit the number of arguments use -N:
parallel -N3 echo ::: A B C D E F G H
Output (the order may be different):
A B C D E F G H
-N also sets the positional replacement strings:
parallel -N3 echo 1={1} 2={2} 3={3} ::: A B C D E F G H
Output (the order may be different):
1=A 2=B 3=C 1=D 2=E 3=F 1=G 2=H 3=
-N0 reads 1 argument but inserts none:
parallel -N0 echo foo ::: 1 2 3
Output:
foo foo foo
Command lines that contain special characters may need to be protected from the shell.
The perl program 'print "@ARGV\n"' basically works like echo.
perl -e 'print "@ARGV\n"' A
Output:
A
To run that in parallel the command needs to be quoted:
parallel perl -e 'print "@ARGV\n"' ::: This wont work
Output:
[Nothing]
To quote the command use -q:
parallel -q perl -e 'print "@ARGV\n"' ::: This works
Output (the order may be different):
This works
Or you can quote the critical part using \':
parallel perl -e \''print "@ARGV\n"'\' ::: This works, too
Output (the order may be different):
This works, too
GNU Parallel can also \-quote full lines. Simply run:
parallel --shellquote parallel: Warning: Input is read from the terminal. Only experts do this on purpose. Press CTRL-D to exit. perl -e 'print "@ARGV\n"' [CTRL-D]
Output:
perl\ -e\ \'print\ \"@ARGV\\n\"\'
This can then be used as the command:
parallel perl\ -e\ \'print\ \"@ARGV\\n\"\' ::: This also works
Output (the order may be different):
This also works
Space can be trimmed on the arguments using --trim:
parallel --trim r echo pre-{}-post ::: ' A '
Output:
pre- A-post
To trim on the left side:
parallel --trim l echo pre-{}-post ::: ' A '
Output:
pre-A -post
To trim on the both sides:
parallel --trim lr echo pre-{}-post ::: ' A '
Output:
pre-A-post
The output can prefixed with the argument:
parallel --tag echo foo-{} ::: A B C
Output (the order may be different):
A foo-A B foo-B C foo-C
To prefix it with another string use --tagstring:
parallel --tagstring {}-bar echo foo-{} ::: A B C
Output (the order may be different):
A-bar foo-A B-bar foo-B C-bar foo-C
To see what commands will be run without running them:
parallel --dryrun echo {} ::: A B C
Output (the order may be different):
echo A echo B echo C
To print the command before running them use --verbose:
parallel --verbose echo {} ::: A B C
Output (the order may be different):
echo A echo B A echo C B C
GNU Parallel will postpone the output until the command completes:
parallel -j2 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1
Output:
2-start 2-middle 2-end 1-start 1-middle 1-end 4-start 4-middle 4-end
To get the output immediately use --ungroup:
parallel -j2 --ungroup 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1
Output:
4-start 42-start 2-middle 2-end 1-start 1-middle 1-end -middle 4-end
--ungroup is fast, but can cause half a line from one job to be mixed with half a line of another job. That has happend in the second line, where the line '4-middle' is mixed with '2-start'.
To avoid this use --linebuffer (which, however, is much slower):
parallel -j2 --linebuffer 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1
Output:
4-start 2-start 2-middle 2-end 1-start 1-middle 1-end 4-middle 4-end
To force the output in the same order as the arguments use --keep-order/-k:
parallel -j2 -k 'printf "%s-start\n%s" {} {};sleep {};printf "%s\n" -middle;echo {}-end' ::: 4 2 1
Output:
4-start 4-middle 4-end 2-start 2-middle 2-end 1-start 1-middle 1-end
GNU Parallel can save the output of each job into files:
parallel --files ::: A B C
Output will be similar to:
/tmp/pAh6uWuQCg.par /tmp/opjhZCzAX4.par /tmp/W0AT_Rph2o.par
By default GNU Parallel will cache the output in files in /tmp. This can be changed by setting $TMPDIR or --tmpdir:
parallel --tmpdir /var/tmp --files ::: A B C
Output will be similar to:
/var/tmp/N_vk7phQRc.par /var/tmp/7zA4Ccf3wZ.par /var/tmp/LIuKgF_2LP.par
Or:
TMPDIR=/var/tmp parallel --files ::: A B C
Output: Same as above.
The output files can be saved in a structured way using --results:
parallel --results outdir echo ::: A B C
Output:
A B C
but also these files were generated containing the standard output (stdout) and standard error (stderr):
outdir/1/A/stderr outdir/1/A/stdout outdir/1/B/stderr outdir/1/B/stdout outdir/1/C/stderr outdir/1/C/stdout
This is useful if you are running multiple variables:
parallel --header : --results outdir echo ::: f1 A B ::: f2 C D
Generated files:
outdir/f1/A/f2/C/stderr outdir/f1/A/f2/C/stdout outdir/f1/A/f2/D/stderr outdir/f1/A/f2/D/stdout outdir/f1/B/f2/C/stderr outdir/f1/B/f2/C/stdout outdir/f1/B/f2/D/stderr outdir/f1/B/f2/D/stdout
The directories are named after the variables and their values.
The number of concurrent jobs is given with --jobs/-j:
/usr/bin/time parallel -N0 -j64 sleep 1 ::: {1..128}
With 64 jobs in parallel the 128 sleeps will take 2-8 seconds to run - depending on how fast your machine is.
By default --jobs is the same as the number of CPU cores. So this:
/usr/bin/time parallel -N0 sleep 1 ::: {1..128}
should take twice the time of running 2 jobs per CPU core:
/usr/bin/time parallel -N0 --jobs 200% sleep 1 ::: {1..128}
--jobs 0 will run as many jobs in parallel as possible:
/usr/bin/time parallel -N0 --jobs 0 sleep 1 ::: {1..128}
which should take 1-7 seconds depending on how fast your machine is.
--jobs can read from a file which is re-read when a job finishes:
echo 50% > my_jobs
/usr/bin/time parallel -N0 --jobs my_jobs sleep 1 ::: {1..128} &
sleep 1
echo 0 > my_jobs
wait
The first second only 50% of the CPU cores will run a job. The '0' is put into my_jobs and then the rest of the jobs will be started in parallel.
Instead of basing the percentage on the number of CPU cores GNU Parallel can base it on the number of CPUs:
parallel --use-cpus-instead-of-cores -N0 sleep 1 ::: {1..128}
GNU Parallel can ask the user if a command should be run using --interactive:
parallel --interactive echo ::: 1 2 3
Output:
echo 1 ?...y echo 2 ?...n 1 echo 3 ?...y 3
GNU Parallel can be used to put arguments on the command line for an interactive command such as emacs to edit one file at a time:
parallel --tty emacs ::: 1 2 3
Or give multiple argument in one go to open multiple files:
parallel -X --tty vi ::: 1 2 3
Some jobs do heavy I/O when they start. To avoid a thundering herd GNU Parallel can delay starting new jobs. --delay X will make sure there is at least X seconds between each start:
parallel --delay 2.5 echo Starting {}\;date ::: 1 2 3
Output:
Starting 1 Thu Aug 15 16:24:33 CEST 2013 Starting 2 Thu Aug 15 16:24:35 CEST 2013 Starting 3 Thu Aug 15 16:24:38 CEST 2013
If jobs taking more than a certain amount of time are known to fail, they can be stopped with --timeout:
parallel --timeout 2.1 sleep {}\; echo {} ::: 1 2 3 4
Output:
1 2
GNU Parallel can compute the median runtime for jobs and kill those that take more than 200% of the median runtime:
parallel --timeout 200% sleep {}\; echo {} ::: 2.1 2.2 3 7 2.3
Output:
2.1 2.2 3 2.3
Based on the runtime of completed jobs GNU Parallel can estimate the total runtime:
parallel --eta sleep ::: 1 3 2 2 1 3 3 2 1
Output:
Computers / CPU cores / Max jobs to run 1:local / 2 / 2
Computer:jobs running/jobs completed/%of started jobs/Average seconds to complete ETA: 2s 0left 1.11avg local:0/9/100%/1.1s
GNU Parallel can give progress information with --progress:
parallel --progress sleep ::: 1 3 2 2 1 3 3 2 1
Output:
Computers / CPU cores / Max jobs to run 1:local / 2 / 2
Computer:jobs running/jobs completed/%of started jobs/Average seconds to complete local:0/9/100%/1.1s
A logfile of the jobs completed so far can be generated with --joblog:
parallel --joblog /tmp/log exit ::: 1 2 3 0 cat /tmp/log
Output:
Seq Host Starttime Runtime Send Receive Exitval Signal Command 1 : 1376577364.974 0.008 0 0 1 0 exit 1 2 : 1376577364.982 0.013 0 0 2 0 exit 2 3 : 1376577364.990 0.013 0 0 3 0 exit 3 4 : 1376577365.003 0.003 0 0 0 0 exit 0
The log contains the job sequence, which host the job was run on, the start time and run time, how much data was transferred if the job was run on a remote host, the exit value, the signal that killed the job, and finally the command being run.
With a joblog GNU Parallel can be stopped and later pickup where it left off. It it important that the input of the completed jobs is unchanged.
parallel --joblog /tmp/log exit ::: 1 2 3 0 cat /tmp/log parallel --resume --joblog /tmp/log exit ::: 1 2 3 0 0 0 cat /tmp/log
Output:
Seq Host Starttime Runtime Send Receive Exitval Signal Command 1 : 1376580069.544 0.008 0 0 1 0 exit 1 2 : 1376580069.552 0.009 0 0 2 0 exit 2 3 : 1376580069.560 0.012 0 0 3 0 exit 3 4 : 1376580069.571 0.005 0 0 0 0 exit 0
Seq Host Starttime Runtime Send Receive Exitval Signal Command 1 : 1376580069.544 0.008 0 0 1 0 exit 1 2 : 1376580069.552 0.009 0 0 2 0 exit 2 3 : 1376580069.560 0.012 0 0 3 0 exit 3 4 : 1376580069.571 0.005 0 0 0 0 exit 0 5 : 1376580070.028 0.009 0 0 0 0 exit 0 6 : 1376580070.038 0.007 0 0 0 0 exit 0
Note how the start time of the last 2 jobs is clearly from the second run.
With --resume-failed GNU Parallel will re-run the jobs that failed:
parallel --resume-failed --joblog /tmp/log exit ::: 1 2 3 0 0 0 cat /tmp/log
Output:
Seq Host Starttime Runtime Send Receive Exitval Signal Command 1 : 1376580069.544 0.008 0 0 1 0 exit 1 2 : 1376580069.552 0.009 0 0 2 0 exit 2 3 : 1376580069.560 0.012 0 0 3 0 exit 3 4 : 1376580069.571 0.005 0 0 0 0 exit 0 5 : 1376580070.028 0.009 0 0 0 0 exit 0 6 : 1376580070.038 0.007 0 0 0 0 exit 0 1 : 1376580154.433 0.010 0 0 1 0 exit 1 2 : 1376580154.444 0.022 0 0 2 0 exit 2 3 : 1376580154.466 0.005 0 0 3 0 exit 3
Note how seq 1 2 3 have been repeated because they had exit value != 0.
For certain jobs there is no need to continue if one of the jobs fails and has an exit code != 0. GNU Parallel will stop spawning new jobs with --halt 1:
parallel -j2 --halt 1 echo {}\; exit {} ::: 0 0 1 2 3
Output:
0 0 1 parallel: Starting no more jobs. Waiting for 2 jobs to finish. This job failed: echo 1; exit 1 2 parallel: Starting no more jobs. Waiting for 1 jobs to finish. This job failed: echo 2; exit 2
With --halt 2 the running jobs will be killed immediately:
parallel -j2 --halt 2 echo {}\; exit {} ::: 0 0 1 2 3
Output:
0 0 1 parallel: This job failed: echo 1; exit 1
GNU Parallel can retry the command with --retries. This is useful if a command fails for unkown reasons now and then.
parallel -k --retries 3 'echo tried {} >>/tmp/runs; echo completed {}; exit {}' ::: 1 2 0
cat /tmp/runs
Output:
completed 1 completed 2 completed 0
tried 1 tried 2 tried 1 tried 2 tried 1 tried 2 tried 0
Note how job 1 and 2 were tried 3 times, but 0 was not retried because it had exit code 0.
To avoid overloading systems GNU Parallel can look at the system load before starting another job:
parallel --load 100% echo load is less than {} job per cpu ::: 1
Output:
[when then load is less than the number of cpu cores] load is less than 1 job per cpu
GNU Parallel can also check if the system is swapping.
parallel --noswap echo the system is not swapping ::: now
Output:
[when then system is not swapping] the system is not swapping now
GNU Parallel can run the jobs with a nice value. This will work both locally and remotely.
parallel --nice 17 echo this is being run with nice -n ::: 17
Output:
this is being run with nice -n 17
GNU Parallel can run jobs on remote servers. It uses ssh to communicate with the remote machines.
The most basic sshlogin is -S host:
parallel -S $SERVER1 echo running on ::: $SERVER1
Output:
running on [$SERVER1]
To use a different username prepend the server with username@
parallel -S username@$SERVER1 echo running on ::: username@$SERVER1
Output:
running on [username@$SERVER1]
The special sshlogin ':' is the local machine:
parallel -S : echo running on ::: the_local_machine
Output:
running on the_local_machine
If ssh is not in $PATH it can be prepended to $SERVER1:
parallel -S '/usr/bin/ssh '$SERVER1 echo custom ::: ssh
Output:
custom ssh
Several servers can be given using multiple -S:
parallel -S $SERVER1 -S $SERVER2 echo ::: running on more hosts
Output (the order may be different):
running on more hosts
Or they can be separated by ,:
parallel -S $SERVER1,$SERVER2 echo ::: running on more hosts
Output: Same as above.
The can also be read from a file (replace user@ with the user on $SERVER2):
echo $SERVER1 > nodefile # Force 4 cores, special ssh-command, username echo 4//usr/bin/ssh user@$SERVER2 >> nodefile parallel --sshloginfile nodefile echo ::: running on more hosts
Output: Same as above.
The special --sshloginfile '..' reads from ~/.parallel/sshloginfile.
To force GNU Parallel to treat a server having a given number of CPU cores prepend #/ to the sshlogin:
parallel -S 4/$SERVER1 echo force {} cpus on server ::: 4
Output:
force 4 cpus on server
GNU Parallel can transfer the files to be processed to the remote host. It does that using rsync.
echo This is input_file > input_file parallel -S $SERVER1 --transfer cat ::: input_file
Output:
This is input_file
If the files is processed into another file, the resulting file can be transferred back:
echo This is input_file > input_file
parallel -S $SERVER1 --transfer --return {}.out cat {} ">"{}.out ::: input_file
cat input_file.out
Output: Same as above.
To remove the input and output file on the remote server use --cleanup:
echo This is input_file > input_file
parallel -S $SERVER1 --transfer --return {}.out --cleanup cat {} ">"{}.out ::: input_file
cat input_file.out
Output: Same as above.
There is a short hand for --transfer --return --cleanup called --trc:
echo This is input_file > input_file
parallel -S $SERVER1 --trc {}.out cat {} ">"{}.out ::: input_file
cat input_file.out
Output: Same as above.
Some jobs need a common database for all jobs. GNU Parallel can transfer that using --basefile which will transfer the file before the first job:
echo common data > common_file
parallel --basefile common_file -S $SERVER1 cat common_file\; echo {} ::: foo
Output:
common data foo
To remove it from the remote host after the last job use --cleanup.
The default working dir on the remote machines is the login dir. This can be changed with --workdir mydir.
Files transferred using --transfer and --return will be relative to mydir on remote computers, and the command will be executed in the dir mydir.
The special mydir value ... will create working dirs under ~/.parallel/tmp/ on the remote computers. If --cleanup is given these dirs will be removed.
The special mydir value . uses the current working dir. If the current working dir is beneath your home dir, the value . is treated as the relative path to your home dir. This means that if your home dir is different on remote computers (e.g. if your login is different) the relative path will still be relative to your home dir.
parallel -S $SERVER1 pwd ::: "" parallel --workdir . -S $SERVER1 pwd ::: "" parallel --workdir ... -S $SERVER1 pwd ::: ""
Output:
[the login dir on $SERVER1] [current dir relative on $SERVER1] [a dir in ~/.parallel/tmp/...]
If many jobs are started on the same server, sshd can be overloaded. GNU Parallel can insert a delay between each job run on the same server:
parallel -S $SERVER1 --sshdelay 0.2 echo ::: 1 2 3
Output (the order may be different):
1 2 3
Sshd will be less overloaded if using --controlmaster, which will multiplex ssh connections:
parallel --controlmaster -S $SERVER1 echo ::: 1 2 3
Output: Same as above.
In clusters with many hosts a few of the are often down. GNU Parallel can ignore those hosts. In this case the host 173.194.32.46 is down:
parallel --filter-hosts -S 173.194.32.46,$SERVER1 echo ::: bar
Output:
bar
GNU Parallel can run the same command on all the hosts:
parallel --onall -S $SERVER1,$SERVER2 echo ::: foo bar
Output (the order may be different):
foo bar foo bar
Often you will just want to run a single command on all hosts with out arguments. --nonall is a no argument --onall:
parallel --nonall -S $SERVER1,$SERVER2 echo foo bar
Output:
foo bar foo bar
When --tag is used with --nonall and --onall the --tagstring is the host:
parallel --nonall --tag -S $SERVER1,$SERVER2 echo foo bar
Output (the order may be different):
$SERVER1 foo bar $SERVER2 foo bar
--jobs sets the number of servers to log in to in parallel.
Using --env GNU Parallel can transfer an environment variable to the remote system.
MYVAR='foo bar' export MYVAR parallel --env MYVAR -S $SERVER1 echo '$MYVAR' ::: baz
Output:
foo bar baz
This works for functions too if your shell is Bash:
# This only works in Bash
my_func() {
echo in my_func $1
}
export -f my_func
parallel --env my_func -S $SERVER1 my_func ::: baz
Output:
in my_func baz
GNU Parallel can copy all defined variables and functions to the remote system. It just needs to record which ones to ignore in ~/.parallel/ignored_vars. Do that by running this once:
parallel --record-env cat ~/.parallel/ignored_vars
Output:
[list of variables to ignore - including $PATH and $HOME]
Now all new variables and functions defined will be copied when using --env _:
# The function is only copied if using Bash
my_func2() {
echo in my_func2 $VAR $1
}
export -f my_func2
VAR=foo
export VAR
parallel --env _ -S $SERVER1 'echo $VAR; my_func2' ::: bar
Output:
foo in my_func2 foo bar
--verbose will show the command that would be run on the local machine. When a job is run on a remote machine this is wrapped with ssh and possibly transferring files and environment variables, setting the workdir, and setting --nice value. -vv shows all of this.
parallel -vv -S $SERVER1 echo ::: bar
Output:
ssh -tt -oLogLevel=quiet lo 'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\; setenv PARALLEL_PID '$PARALLEL_PID' || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\; PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;' tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ bar;
bar
When the command gets more complex, the output is so hard to read, that it is only useful for debugging:
my_func3() {
echo in my_func $1 > $1.out
}
export -f my_func3
parallel -vv --workdir ... --nice 17 --env _ --trc {}.out -S $SERVER1 my_func3 {} ::: abc-file
Output will be similar to:
ssh server mkdir -p .parallel/tmp/hk-31483-1; rsync -rlDzR -essh ./abc-file server:.parallel/tmp/hk-31483-1;ssh -tt -oLogLevel=quiet server 'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\; setenv PARALLEL_PID '$PARALLEL_PID' || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\; PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;' tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;mkdir\ -p\ .parallel/tmp/hk-31483-1\;\ cd\ .parallel/tmp/hk-31483-1\ \&\&\ echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ my_func3\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\\\ \\\>\\\ \\\$1.out\"'
'\"\\\}\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \|\|\ export\ my_func3=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\\\ \\\>\\\ \\\$1.out\"'
'\"\\\}\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \&\&\ eval\ my_func3\"\$my_func3\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ my_func3\\\ abc-file;_EXIT_status=$?; mkdir -p .; rsync --rsync-path=cd\ .parallel/tmp/hk-31483-1/.\;\ rsync -rlDzR -essh server:abc-file.out .;ssh server rm\ -f\ .parallel/tmp/hk-31483-1/abc-file\;rm\ -f\ .parallel/tmp/hk-31483-1/abc-file.out\;rm -rf .parallel/tmp/hk-31483-1\;; exit $_EXIT_status;
The --pipe functionality puts GNU Parallel in a different mode: Instead of treating the data on stdin (standard input) as arguments for a command to run, the data will be sent to stdin (standard input) of the command.
The typical situation is:
command_A | command_B | command_C
where command_B is slow, and you want to speed up command_B.
By default GNU Parallel will start an instance of command_B, read a chunk of 1 MB, and pass that to the instance. Then start another instance, read another chunk, and pass that to the second instance.
cat num1000000 | parallel --pipe wc
Output (the order may be different):
165668 165668 1048571 149797 149797 1048579 149796 149796 1048572 149797 149797 1048579 149797 149797 1048579 149796 149796 1048572 85349 85349 597444
The size of the chunk is not exactly 1 MB because GNU Parallel only passes full lines - never half a line, thus the blocksize is only average 1 MB. You can change the block size to 2 MB with --block:
cat num1000000 | parallel --pipe --block 2M wc
Output (the order may be different):
315465 315465 2097150 299593 299593 2097151 299593 299593 2097151 85349 85349 597444
GNU Parallel treats each line as a record. If the order of record is unimportant (e.g. you need all lines processed, but you do not care which is processed first), then you can use --round-robin. Without --round-robin GNU Parallel will start a command per block; with --round-robin only the requested number of jobs will be started (--jobs). The records will then be distributed between the running jobs:
cat num1000000 | parallel --pipe -j4 --round-robin wc
Output will be similar to:
149797 149797 1048579 299593 299593 2097151 315465 315465 2097150 235145 235145 1646016
One of the 4 instances got a single record, 2 instances got 2 full records each, and one instance got 1 full and 1 partial record.
GNU Parallel sees the input as records. The default record is a single line.
Using -N140000 GNU Parallel will read 140000 records at a time:
cat num1000000 | parallel --pipe -N140000 wc
Output (the order may be different):
140000 140000 868895 140000 140000 980000 140000 140000 980000 140000 140000 980000 140000 140000 980000 140000 140000 980000 140000 140000 980000 20000 20000 140001
Notice that the last job could not get the full 140000 lines, but only 20000 lines.
If a record is 75 lines -L can be used:
cat num1000000 | parallel --pipe -L75 wc
Output (the order may be different):
165600 165600 1048095
149850 149850 1048950
149775 149775 1048425
149775 149775 1048425
149850 149850 1048950
149775 149775 1048425
85350 85350 597450
25 25 176
Notice GNU Parallel still reads a block of around 1 MB; but instead of passing full lines to 'wc' it passes full 75 lines at a time. This of course does not hold for the last job (which in this case got 25 lines).
GNU Parallel uses separators to determine where two record split.
--recstart gives the string that starts a record; --recend gives the string that ends a record. The default is --recend '\n' (newline).
If both --recend and --recstart are given, then the record will only split if the recend string is immediately followed by the recstart string.
Here the --recend is set to ', ':
echo /foo, bar/, /baz, qux/, | parallel -kN1 --recend ', ' --pipe echo JOB{#}\;cat\;echo END
Output:
JOB1 /foo, END JOB2 bar/, END JOB3 /baz, END JOB4 qux/, END
Here the --recstart is set to '/':
echo /foo, bar/, /baz, qux/, | parallel -kN1 --recstart '/' --pipe echo JOB{#}\;cat\;echo END
Output:
JOB1 /foo, barEND JOB2 /, END JOB3 /baz, quxEND JOB4 /, END
Here both --recend and --recstart are set:
echo /foo, bar/, /baz, qux/, | parallel -kN1 --recend ', ' --recstart '/' --pipe echo JOB{#}\;cat\;echo END
Output:
JOB1 /foo, bar/, END JOB2 /baz, qux/, END
Note the difference between setting one string and setting both strings.
With --regexp the --recend and --recstart will be treated as a regular expression:
echo foo,bar,_baz,__qux, | parallel -kN1 --regexp --recend ',_+' --pipe echo JOB{#}\;cat\;echo END
Output:
JOB1 foo,bar,_END JOB2 baz,__END JOB3 qux, END
GNU Parallel can remove the record separators with --remove-rec-sep/--rrs:
echo foo,bar,_baz,__qux, | parallel -kN1 --rrs --regexp --recend ',_+' --pipe echo JOB{#}\;cat\;echo END
Output:
JOB1 foo,barEND JOB2 bazEND JOB3 qux, END
If the input data has a header, the header can be repeated for each job by matching the header with --header. If headers start with %:
cat num_%header | parallel --header '(%.*\n)*' --pipe -N3 echo JOB{#}\;cat
Output (the order may be different):
JOB1 %head1 %head2 1 2 3 JOB2 %head1 %head2 4 5 6 JOB3 %head1 %head2 7 8 9 JOB4 %head1 %head2 10
If the header is 2 lines, --header 2 will work:
cat num_%header | parallel --header 2 --pipe -N3 echo JOB{#}\;cat
Output: Same as above.
GNU Parallel is often called as:
cat input_file | parallel command
With --shebang the input_file and parallel can be combined into the same script.
UNIX-scripts start with a shebang line like:
#!/bin/bash
GNU Parallel can do that, too. With --shebang the arguments can be listed in the file. The parallel command is the first line of the script:
#!/usr/bin/parallel --shebang -r echo
foo bar baz
Output (the order may be different):
foo bar baz
GNU Parallel is often called as:
cat input_file | parallel command parallel command ::: foo bar
If command is a script parallel can be combined into a single file so:
cat input_file | command command foo bar
will run the script in parallel.
This perl script perl_echo works like echo:
#!/usr/bin/perl
print "@ARGV\n"
It can be called as:
parallel perl_echo ::: foo bar
By changing the #!-line it can be run in parallel
#!/usr/bin/parallel --shebang-wrap /usr/bin/perl
print "@ARGV\n"
Thus this will work:
perl_echo foo bar
Output (the order may be different):
foo bar
This technique can be used for:
#!/usr/bin/parallel --shebang-wrap /usr/bin/perl
#!/usr/bin/parallel --shebang-wrap /usr/bin/python
#!/usr/bin/parallel --shebang-wrap /bin/bash
#!/usr/bin/parallel --shebang-wrap /usr/bin/Rscript --vanilla --slave
#!/usr/bin/parallel --shebang-wrap ARG={} /usr/bin/gnuplot
#!/usr/bin/parallel --shebang-wrap /usr/bin/ruby
GNU Parallel can work as a counting semaphore. This is slower and less efficient than its normal mode.
An alias for 'parallel --semaphore' is 'sem'. The default is to allow only one program to run at a time (technically called a mutex). The program is started in the background. Use --wait for all 'sem's to finish:
sem 'sleep 1; echo The first finished' &&
echo The first is now running in the background &&
sem 'sleep 1; echo The second finished' &&
echo The second is now running in the background
sem --wait
Output:
The first is now running in the background The first finished The second is now running in the background The second finished
The command can be run in the foreground with --fg:
sem --fg 'sleep 1; echo The first finished' &&
echo The first finished running in the foreground &&
sem --fg 'sleep 1; echo The second finished' &&
echo The second finished running in the foreground
sem --wait
The difference between this and just running the command, is that a mutex is set, so if other sems were running in the background only one would run at the same time.
To tell the difference between which semaphore is used, use --semaphorename/--id. Run this in one terminal:
sem --id my_id -u 'echo First started; sleep 10; echo The first finished'
and simultaneously this in another terminal:
sem --id my_id -u 'echo Second started; sleep 10; echo The second finished'
Note how the second will only be started when the first has finished.
A mutex is like having a single toilet: When it is in use everyone else will have to wait. A counting semaphore is like having multiple toilets: Several people can use the toilets, but when they all are in use, everyone else will have to wait.
sem can emulate a counting semaphore. Use --jobs to set the number of toilets:
sem --jobs 3 --id my_id -u 'echo First started; sleep 5; echo The first finished' && sem --jobs 3 --id my_id -u 'echo Second started; sleep 6; echo The second finished' && sem --jobs 3 --id my_id -u 'echo Third started; sleep 7; echo The third finished' && sem --jobs 3 --id my_id -u 'echo Fourth started; sleep 8; echo The fourth finished' && sem --wait --id my_id
Output:
First started Second started Third started The first finished Fourth started The second finished The third finished The fourth finished
GNU Parallel has some options to give short information about the configuration.
--help will print a summary of the most important options:
parallel --help
Output:
Usage:
parallel [options] [command [arguments]] < list_of_arguments
parallel [options] [command [arguments]] (::: arguments|:::: argfile(s))...
cat ... | parallel --pipe [options] [command [arguments]]
-j n Run n jobs in parallel
-k Keep same order
-X Multiple arguments with context replace
--colsep regexp Split input on regexp for positional replacements
{} {.} {/} {/.} {#} Replacement strings
{3} {3.} {3/} {3/.} Positional replacement strings
-S sshlogin Example: foo@server.example.com
--slf .. Use ~/.parallel/sshloginfile as the list of sshlogins
--trc {}.bar Shorthand for --transfer --return {}.bar --cleanup
--onall Run the given command with argument on all sshlogins
--nonall Run the given command with no arguments on all sshlogins
--pipe Split stdin (standard input) to multiple jobs.
--recend str Record end separator for --pipe.
--recstart str Record start separator for --pipe.
See 'man parallel' for details
When using GNU Parallel for a publication please cite:
O. Tange (2011): GNU Parallel - The Command-Line Power Tool,
;login: The USENIX Magazine, February 2011:42-47.
When asking for help, always report the full output of:
parallel --version
Output:
GNU parallel 20130822 Copyright (C) 2007,2008,2009,2010,2011,2012,2013 Ole Tange and Free Software Foundation, Inc. License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>; This is free software: you are free to change and redistribute it. GNU parallel comes with no warranty. Web site: http://www.gnu.org/software/parallel When using GNU Parallel for a publication please cite: O. Tange (2011): GNU Parallel - The Command-Line Power Tool, ;login: The USENIX Magazine, February 2011:42-47.
In scripts --minversion can be used to ensure the user has at least this version:
parallel --minversion 20130722 && echo Your version is at least 20130722.
Output:
20130722 Your version is at least 20130722.
If using GNU Parallel for research the BibTeX citation can be generated using --bibtex.
parallel --bibtex
Output:
@article{Tange2011a,
title = {GNU Parallel - The Command-Line Power Tool},
author = {O. Tange},
address = {Frederiksberg, Denmark},
journal = {;login: The USENIX Magazine},
month = {Feb},
number = {1},
volume = {36},
url = {http://www.gnu.org/s/parallel},
year = {2011},
pages = {42-47}
}
With --max-line-length-allowed GNU Parallel will report the maximal size of the command line:
parallel --max-line-length-allowed
Output (may vary on different systems):
131071
--number-of-cpus and --number-of-cores run system specific code to determine the number of CPUs and CPU cores on the system. On unsupported platforms they will return 1:
parallel --number-of-cpus parallel --number-of-cores
Output (may vary on different systems):
4 64
The defaults for GNU Parallel can be changed systemwise by putting the command line options in /etc/parallel/config. They can be changed for a user by putting them in ~/.parallel/config.
Profiles work the same way, but have to be referred to with --profile:
echo '-S :,'$SERVER1 > ~/.parallel/cluster echo '--nice 17' >> ~/.parallel/cluster echo '--filter-hosts' >> ~/.parallel/cluster echo '--timeout 300%' >> ~/.parallel/cluster echo '--env _' >> ~/.parallel/cluster parallel --profile cluster echo ::: A B C
Output:
A B C
Profiles can be combined:
echo '-vv --dry-run' > ~/.parallel/dryverbose parallel --profile dryverbose --profile cluster echo ::: A B C
Output:
ssh -tt -oLogLevel=quiet lo 'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\; setenv PARALLEL_PID '$PARALLEL_PID' || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\; PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;' tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ SERVER1\ lo\ \&\&\ setenv\ MYVAR\ foo\\\ bar\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
'\"\\\}\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \|\|\ export\ SERVER1=lo\ \&\&\ export\ MYVAR=foo\\\ bar\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
'\"\\\}\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \&\&\ eval\ my_func\"\$my_func\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ echo\\\ A;
ssh -tt -oLogLevel=quiet lo 'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\; setenv PARALLEL_PID '$PARALLEL_PID' || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\; PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;' tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ SERVER1\ lo\ \&\&\ setenv\ MYVAR\ foo\\\ bar\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
'\"\\\}\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \|\|\ export\ SERVER1=lo\ \&\&\ export\ MYVAR=foo\\\ bar\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
'\"\\\}\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \&\&\ eval\ my_func\"\$my_func\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ echo\\\ B;
ssh -tt -oLogLevel=quiet lo 'eval `echo $SHELL | grep "/t\{0,1\}csh" > /dev/null && echo setenv PARALLEL_SEQ '$PARALLEL_SEQ'\; setenv PARALLEL_PID '$PARALLEL_PID' || echo PARALLEL_SEQ='$PARALLEL_SEQ'\;export PARALLEL_SEQ\; PARALLEL_PID='$PARALLEL_PID'\;export PARALLEL_PID` ;' tty\ \>/dev/null\ \&\&\ stty\ isig\ -onlcr\ -echo\;echo\ \$SHELL\ \|\ grep\ \"/t\\\{0,1\\\}csh\"\ \>\ /dev/null\ \&\&\ setenv\ SERVER1\ lo\ \&\&\ setenv\ MYVAR\ foo\\\ bar\ \&\&\ setenv\ VAR\ foo\ \&\&\ setenv\ my_func\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
'\"\\\}\ \&\&\ setenv\ my_func2\ \\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \|\|\ export\ SERVER1=lo\ \&\&\ export\ MYVAR=foo\\\ bar\ \&\&\ export\ VAR=foo\ \&\&\ export\ my_func=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func\\\ \\\$1\"'
'\"\\\}\ \&\&\ export\ my_func2=\\\(\\\)\\\ \\\{\\\ \\\ echo\\\ in\\\ my_func2\\\ \\\$VAR\\\ \\\$1\"'
'\"\\\}\ \&\&\ eval\ my_func\"\$my_func\"\ \&\&\ eval\ my_func2\"\$my_func2\"\;\\nice\ -n17\ /bin/bash\ -c\ echo\\\ C;
I hope you have learned something from this tutorial.
If you like GNU Parallel:
Give a demo at your local user group/team/colleagues
Post the intro videos and the tutorial on Reddit, Diaspora*, forums, blogs, Identi.ca, Google+, Twitter, Facebook, Linkedin, mailing lists
Request or write a review for your favourite blog or magazine
Invite me for your next conference
If you use GNU Parallel for research:
Please cite GNU Parallel in you publications (use --bibtex)
If GNU Parallel saves you money:
(Have your company) donate to FSF https://my.fsf.org/donate/
(C) 20130822 Ole Tange GPLv3