Once my job has completed, I can reconnect to Gauss and launch MATLAB to get my output. Non-Interactive Demo (16 workers - requires 17) > can now close MATLAB, disconnect from Gauss, and wait for an email from the scheduler. Some key things to note about the R wrapper:Īssume the following test M file (~/test.m)
#GAUSS 2081 COMPRESSION DRIVER FULL#
Assuming sufficient resources are available on Gauss, jobs can run concurrently and the full simulation study could potentially be completed in 1 hour, rather than 100 hours. This will allow each R job to analyze a different dataset, the first job will analyze dataset 1, the second job will analyze dataset 2 and so forth. # Now, run the inner-part of Jim's old for-loop. Setwd("~/my_favourite_output_directory/")Ĭat(paste("Sinking output to: ",sinkfile,"\n",sep="")) R - vanilla -no-save -args 1 Lowest dataset number to be analyzed by this particular batch job What the jimsjob.sh script will do when submitted, as per the last line of the script, is submit 100 R jobs each receiving a different command-line argument i.e., it is equivalent to running: Please see the full SLURM documentation for more details.Īll Gauss users must use the cluster responsibly and fairly, be mindful of this when submitting large jobs The main elements of the script are just setting up Gauss, and can be customized in many different ways. Srun R -vanilla -no-save -args $ < /pathtojimsrscript/jimsrscript.R # this to do something different for each index): # Execute each of the jobs with a different index (the R script will then process #SBATCH Standard out and Standard Error output files with the job number in the name. # Email notifications (optional), type=BEGIN, END, FAIL, ALL # Tell Gauss how much memory per CPU your job will use: # Name of the job - you'll probably want to customize this. # (4) Ranges can be combined with specified job numbers. # (3) Zero can be included if specified separately. # (2) Negative numbers are not allowed in -range # (1) When specifying -array as a range it must start from a positive First, he will need a sbatch script, lets suppose this is saved as jimsjob.sh: Using an array job on Gauss, Jim can potentially save a lot of time with minimal changes to his code.
Suppose each dataset takes 1 hour for simulation and analysis, the full simulation study would take 100 hours. If he does this in a single R job he would do: He will then combine the results to study the properties of his procedure. He decides he would like to simulate 100 datasets, and fit each simulated dataset with his new method. Each job can receive customized argumentsįor example, suppose Jim wants to test his new statistical methodology, so he decides to conduct a simulation study.
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