I have a bash script that takes as input three arrays with equal length: METHODS
, INFILES
and OUTFILES
.
This script will let METHODS[i]
solves problem INFILES[i]
and saves the result to OUTFILES[i]
, for all indices i
(0 <= i <= length-1
).
Each element in METHODS
is a string of the form:
$HOME/program/solver -a <method>
where solver is a program that can be called as follows:
$HOME/program/solver -a <method> -m <input file> -o <output file> --timeout <timeout in seconds>
The script solves all the problems in parallel and set the runtime limit for each instance to 1 hour (some methods can solve some problems very quickly though), as follows:
#!/bin/bash
source METHODS
source INFILES
source OUTFILES
start=`date +%s`
## Solve in PARALLEL
for index in ${!OUTFILES[*]}; do
(alg=${METHODS[$index]}
infile=${INFILES[$index]}
outfile=${OUTFILES[$index]}
${!alg} -m $infile -o $outfile --timeout 3600) &
done
wait
end=`date +%s`
runtime=$((end-start))
echo "Total runtime = $runtime (s)"
echo "Total number of processes = ${#OUTFILES[@]}"
In the above I have length = 619
. I submitted this bash to a cluster with 70 available processors, which should take at maximum 9 hours to finish all the tasks. This is not the case in reality, however. When using the top
command to investigate, I found that only two or three processes are running (state = R
) while all the others are sleeping (state = D
).
What am I doing wrong please?
Furthermore, I have learnt that GNU parallel would be much better for running parallel jobs. How can I use it for the above task?
Thank you very much for your help!
Update: My first try with GNU parallel:
The idea is to write all the commands to a file and then use GNU parallel to execute them:
#!/bin/bash
source METHODS
source INFILES
source OUTFILES
start=`date +%s`
## Write to file
firstline=true
for index in ${!OUTFILES[*]}; do
(alg=${METHODS[$index]}
infile=${INFILES[$index]}
outfile=${OUTFILES[$index]}
if [ "$firstline" = true ] ; then
echo "${!alg} -m $infile -o $outfile --timeout 3600" > commands.txt
firstline=false
else
echo "${!alg} -m $infile -o $outfile --timeout 3600" >> commands.txt
fi
done
## Solve in PARALLEL
time parallel :::: commands.txt
end=`date +%s`
runtime=$((end-start))
echo "Total runtime = $runtime (s)"
echo "Total number of processes = ${#OUTFILES[@]}"
What do you think?
Update 2: I'm using GNU parallel and having the same problem. Here's the output of top
:
top - 02:05:25 up 178 days, 8:16, 2 users, load average: 62.59, 59.90, 53.29
Tasks: 596 total, 7 running, 589 sleeping, 0 stopped, 0 zombie
Cpu(s): 12.9%us, 0.9%sy, 0.0%ni, 63.3%id, 22.9%wa, 0.0%hi, 0.1%si, 0.0%st
Mem: 264139632k total, 260564864k used, 3574768k free, 4564k buffers
Swap: 268420092k total, 80593460k used, 187826632k free, 53392k cached
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
28542 khue 20 0 7012m 5.6g 1816 R 100 2.2 12:50.22 opengm_min_sum
28553 khue 20 0 11.6g 11g 1668 R 100 4.4 17:37.37 opengm_min_sum
28544 khue 20 0 13.6g 8.6g 2004 R 100 3.4 12:41.67 opengm_min_sum
28549 khue 20 0 13.6g 8.7g 2000 R 100 3.5 2:54.36 opengm_min_sum
28551 khue 20 0 11.6g 11g 1668 R 100 4.4 19:48.36 opengm_min_sum
28528 khue 20 0 6934m 4.9g 1732 R 29 1.9 1:01.13 opengm_min_sum
28563 khue 20 0 7722m 6.7g 1680 D 2 2.7 0:56.74 opengm_min_sum
28566 khue 20 0 8764m 7.9g 1680 D 2 3.1 1:00.13 opengm_min_sum
28530 khue 20 0 5686m 4.8g 1732 D 1 1.9 0:56.23 opengm_min_sum
28534 khue 20 0 5776m 4.6g 1744 D 1 1.8 0:53.46 opengm_min_sum
28539 khue 20 0 6742m 5.0g 1732 D 1 2.0 0:58.95 opengm_min_sum
28548 khue 20 0 5776m 4.7g 1744 D 1 1.9 0:55.67 opengm_min_sum
28559 khue 20 0 8258m 7.1g 1680 D 1 2.8 0:57.90 opengm_min_sum
28564 khue 20 0 10.6g 10g 1680 D 1 4.0 1:08.75 opengm_min_sum
28529 khue 20 0 5686m 4.4g 1732 D 1 1.7 1:05.55 opengm_min_sum
28531 khue 20 0 4338m 3.6g 1724 D 1 1.4 0:57.72 opengm_min_sum
28533 khue 20 0 6064m 5.2g 1744 D 1 2.1 1:05.19 opengm_min_sum
(opengm_min_sum
is the solver
above)
I guess that some processes consume so much resource that the others do not have anything left and enter the D state?
wait
and encountering the same problem. How should I investigate further to see what is wrong?work
and less I/O or else get more or faster disks.ps
andtop
only show you what is happening at the instant something is being run. If a program is reading a lot of data then there is a good chance that at the instanttop
is running it will be waiting for the disk. I know nothing about your problem but it looks like you have a machine which is fast enough but doesn't have enough memory for you to run all of your programs at the same time and doesn't have enough I/O bandwidth. If you access the data sequentially maybe compressing it will help? Remember to give me credit in your PhD!