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Your compiled cuda program is submitted via a script that slurm's sbatch command can read. Use a text editor to create a file called, device_query.sh. Here we run the deviceQuery command:
| #!/bin/bash #SBATCH --partition=gpu #SBATCH -c 2 #SBATCH --output=gpu.%N.%j.out #SBATCH --error=gpu.%N.%j.err module load cuda/6.5.12 deviceQuery > my_device_results.out |
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To submit this file to the gpu partition, run:
> sbatch device_query.sh
What gpu libraries are available on the cluster for linear algebra methods?
Cuda has support and additional support can be found in Cula routines. Cula addresses dense and sparse matrix related methods and access is via the module environment. To see what is current:
> module available
Cula install directory is /opt/shared/cula/
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