...
Parallel Programming with R
| Info |
|---|
The are 10s of potential packages that could be used, as a starting point we’d direct your to here: CRAN Task View: High-Performance and Parallel Computing with R. One thing to consider with respect to what package you wish to explore is whether it provides multi-node functionality (such as Rmpi) or just multicore (parallel) on a single compute node, and/or cluster features. |
| Note |
|---|
Remember: Just asking for multiple nodes (and GPUs) won’t actually make your code run faster unless the underlying package can actually utilize them. |
...
| Info |
|---|
The It does not need to be installed. |
...
| Code Block |
|---|
# Create an interactive session that uses 8 cores: [salexan5@mblog2 ~]$ salloc -A arcc -t 10:00 -c 8 salloc: Granted job allocation 861904 salloc: Nodes mbcpu-001 are ready for job [salexan5@mbcpu@mbcpu-001 ~]$ module load gcc/13.2.0 r/4.4.0 # Check the slurm environment variable: SLURM_JOB_CPUS_PER_NODE [salexan5@mbcpu@mbcpu-001 ~]$ echo $SLURM_JOB_CPUS_PER_NODE 8 # What does R detect? [salexan5@mbcpu@mbcpu-001 ~]$ Rscript r_multicore.R $SLURM_JOB_CPUS_PER_NODE [1] "Num of Cores: 8" [1] "detectCores: 96" [1] "mc.cores: 8" |
...
Prev |
Workshop Home | Next |