Difference between revisions of "Submitting Jobs"
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It will set the properties of gpu resources required by the job | It will set the properties of gpu resources required by the job | ||
− | + | '''Example 1''' | |
[bhatiag@ds-lg-01 ~]$ bsub -gpu "num=2:mode=shared:mps=yes" – python.py | [bhatiag@ds-lg-01 ~]$ bsub -gpu "num=2:mode=shared:mps=yes" – python.py | ||
Job <5979> is submitted to queue <gpu>. | Job <5979> is submitted to queue <gpu>. | ||
Line 32: | Line 32: | ||
You can check the job status using <code>bjobs</code> | You can check the job status using <code>bjobs</code> | ||
− | + | '''Example 2''' | |
+ | Consider a bash script <code>python.sh</code> with following commands into it | ||
+ | #!/bin/bash | ||
+ | source . /opt/anaconda2/etc/profile.d/conda.sh | ||
+ | conda activate py36 | ||
+ | python example.py | ||
+ | |||
+ | See [[Writing Script]] for more information | ||
+ | |||
+ | Submit the job <code>python.sh</code> using following command | ||
[bhatiag@ds-lg-01 ~]$ bsub -oo "output.txt" -gpu "num=1:mode=exclusive_process:mps=yes" "python.sh" | [bhatiag@ds-lg-01 ~]$ bsub -oo "output.txt" -gpu "num=1:mode=exclusive_process:mps=yes" "python.sh" | ||
Job <5980> is submitted to queue <gpu>. | Job <5980> is submitted to queue <gpu>. | ||
− | output | + | Output file <code>output.txt</code> will contain |
[bhatiag@ds-lg-01 ~]$ cat output.txt | [bhatiag@ds-lg-01 ~]$ cat output.txt | ||
Sender: LSF System <lsfadmin@ds-cmgpu-06> | Sender: LSF System <lsfadmin@ds-cmgpu-06> | ||
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Turnaround time : 3 sec. | Turnaround time : 3 sec. | ||
The output (if any) follows: | The output (if any) follows: | ||
− | Display whatever in your python script | + | '''Display whatever in your python script''' |
Latest revision as of 18:50, 4 December 2020
Jobs can be submitted using bsub command. For more information on bsub , go to bsub You can also check Running jobs for more detail.
Some example:
1. bsub -Is -gpu - bash
This command will submit an interactive job to gpu queue and creates a pseudo-terminal with shell mode when the job starts. Also, it will provide you the jobid.
for example
[bhatiag@ds-lg-01 ~]$ bsub -Is -gpu - bash Job <5972> is submitted to queue <gpu>. <<Waiting for dispatch ...>> <<Starting on ds-cmgpu-05>>
2. bsub -gpu - scriptname
It will submit the script to gpu queue
for example
[bhatiag@ds-lg-01 ~]$ bsub -gpu - python.py Job <5978> is submitted to queue <gpu>.
3. bsub -gpu "num=2:mode=shared:mps=yes" – scriptname
It will set the properties of gpu resources required by the job
Example 1
[bhatiag@ds-lg-01 ~]$ bsub -gpu "num=2:mode=shared:mps=yes" – python.py Job <5979> is submitted to queue <gpu>.
You can check the job status using bjobs
Example 2
Consider a bash script python.sh
with following commands into it
#!/bin/bash source . /opt/anaconda2/etc/profile.d/conda.sh conda activate py36 python example.py
See Writing Script for more information
Submit the job python.sh
using following command
[bhatiag@ds-lg-01 ~]$ bsub -oo "output.txt" -gpu "num=1:mode=exclusive_process:mps=yes" "python.sh" Job <5980> is submitted to queue <gpu>.
Output file output.txt
will contain
[bhatiag@ds-lg-01 ~]$ cat output.txt Sender: LSF System <lsfadmin@ds-cmgpu-06> Subject: Job 5980: <python.sh> in cluster <DeepSenseLSFCluster> Exited Job <python.sh> was submitted from host <ds-lg-01> by user <bhatiag> in cluster <DeepSenseLSFCluster> at Fri Dec 4 14:28:37 2020 Job was executed on host(s) <ds-cmgpu-06>, in queue <gpu>, as user <bhatiag> in cluster <DeepSenseLSFCluster> at Fri Dec 4 14:28:37 2020 </users/faculty/bhatiag> was used as the home directory. </users/faculty/bhatiag> was used as the working directory. Started at Fri Dec 4 14:28:37 2020 Terminated at Fri Dec 4 14:28:40 2020 Results reported at Fri Dec 4 14:28:40 2020 Your job looked like: ------------------------------------------------------------ # LSBATCH: User input python.sh ------------------------------------------------------------ Exited with exit code 127. Resource usage summary: CPU time : 0.05 sec. Max Memory : 6 MB Average Memory : 6.00 MB Total Requested Memory : - Delta Memory : - Max Swap : - Max Processes : 1 Max Threads : 1 Run time : 3 sec. Turnaround time : 3 sec. The output (if any) follows: Display whatever in your python script