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cluster.functions <- makeClusterFunctionsSlurm(template="batchtools.slurm.tmpl") | ||
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#!/bin/bash | ||
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## Job Resource Interface Definition | ||
## | ||
## ntasks [integer(1)]: Number of required tasks, | ||
## Set larger than 1 if you want to further parallelize | ||
## with MPI within your job. | ||
## ncpus [integer(1)]: Number of required cpus per task, | ||
## Set larger than 1 if you want to further parallelize | ||
## with multicore/parallel within each task. | ||
## walltime [integer(1)]: Walltime for this job, in minutes. | ||
## Must be at least 1 minute. | ||
## memory [integer(1)]: Memory in megabytes for each cpu. | ||
## Must be at least 100 (when I tried lower values my | ||
## jobs did not start at all). | ||
## | ||
## Default resources can be set in your .batchtools.conf.R by defining the variable | ||
## 'default.resources' as a named list. | ||
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<% | ||
# relative paths are not handled well by Slurm | ||
log.file = normalizePath(log.file, winslash = "/", mustWork = FALSE) | ||
-%> | ||
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#SBATCH --job-name=<%= job.name %> | ||
#SBATCH --output=<%= log.file %> | ||
#SBATCH --error=<%= log.file %> | ||
#SBATCH --time=<%= ceiling(resources$walltime / 1) %> | ||
#SBATCH --ntasks=1 | ||
#SBATCH --cpus-per-task=<%= resources$ncpus %> | ||
#SBATCH --mem-per-cpu=<%= resources$memory %> | ||
<%= if (!is.null(resources$partition)) sprintf(paste0("#SBATCH --partition='", resources$partition, "'")) %> | ||
<%= if (array.jobs) sprintf("#SBATCH --array=1-%i", nrow(jobs)) else "" %> | ||
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## specify which queue on biocluster, one of 'batch', 'highmem', 'intel', 'gpu', 'mygroup' | ||
##SBATCH -p short | ||
##SBATCH -p batch | ||
##SBATCH -p intel | ||
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## Initialize work environment like | ||
## source /etc/profile | ||
## module add ... | ||
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## Export value of DEBUGME environemnt var to slave | ||
export DEBUGME=<%= Sys.getenv("DEBUGME") %> | ||
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## Run R: | ||
## we merge R output with stdout from SLURM, which gets then logged via --output option | ||
Rscript -e 'batchtools::doJobCollection("<%= uri %>")' | ||
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