LSF is currently a de-facto standard in managing computing queues. Many inexpensive CPU or GPU clusters uses LSF. Majority of current academic HPC codes are using MPI for their core computations. While the parallelisation/distribution of the computational tasks are achived by the core MPI codes, LSF batch job script, usually can invoke via shell, is still a serial code. See here. This may bring a bottleneck in case that the batch script needs to run large set of commands in sequence, that can be done in distributed way.
Idle CPUs
An example task could be that your parallel code generates large set of output files and you require to further process them, such as compressing all data files produced by processes. Once you launch $n$ processes, after completion of the MPI code, running compression over the $n$ data files will be processed in a single process. This will not only waste $n-1$ cpu time waiting idle, it will waste our wall clock time $n-1$ fold while compression is performed sequentially. To overcome this limitation LSF has introduced a tool called blaunch, for distributing the tasks. The documentation provided by IBM is really fantastic. However it lacks a simple example for novice users. In this post I provide a simple example that compresses $n$ data files using $n$ distributed processes.
Job distribution via blaunch
The first step in doing this task, we need to figure our what hostnames we are currently running with the LSF job script. This can be obtained using $LSF_HOSTS environment variable. The second step is to write this information into hosts file that can be read by blaunch. A compression script should be provided in a seperate file. This is an important point. Because whole concept of blaunch is that it distributes the given command to all available processes. Note that, LSF process is running your script not the distributed host processes, at least what it is transparently. Knowing this fact, we can only differentiate the process ID outside of our job submit script using $LSF_PM_TASKID.
Here is a possible portion of the job script, using BASH,
1 2 3 4 5 | cd /mydata rm hosts.txt export myhosts=($LSB_HOSTS) for hostName in ${myhosts[*]};do echo $hostName >> hosts.txt ; done blaunch -u hosts.txt compress.sh |
As you can see we don't use $LSF_PM_TASKID in the job script, rather in the compression script that is going to be launch in one of the distributed process:
1 2 3 4 5 | export trajF=(`find . -name '*.dat'`) # ${trajF[ii]}; ii=`expr $ii + 1`;done # This line should be removed (see comments) export ii=`expr $LSF_PM_TASKID - 1` echo ${trajF[$ii]} xz -4e --format=lzma ${trajF[$ii]} |
We assume that commands are available in the BASH environment. Note that we use bash array to identify file names and your output convention should match with the identification.
Conclusion
We have provided a simple working example of launching parallel shell script tasks using blaunch. A similar approach is presented here. An alternating approach to this could be using GNU Parallel , which is discussed here.
