There are some applications that benefit from GPU computing. These applications will usually use the CUDA libraries to take advantage of GPU computing.
Access to the BlueBEAR GPU Service
To request access to the GPU nodes please contact us through the IT Service Portal. We may ask for more information about the types of applications you are looking to use on these nodes prior to granting access to this service.
Using the BlueBEAR GPU Service
To use one of the gpu nodes, add
#SBATCH --qos bbgpu
#SBATCH --account [projectname]
#SBATCH --gres [gputype]
to your job submission script, where
[projectname] is a project that has access to the GPU service; and
[gputype] is the type of GPU you wish to use in your job - specified in the form
gpu:p100:1 to request one NVidia P100 per node in your job
. If, when you submit a GPU job, you receive an error message of
sbatch: error: Batch job submission failed: Invalid qos specification
then either you are not a member of a project that has access to the GPU service or the project you specified does not have access to the GPU service.
The two nodes in the standard GPU Service have the following configuration:
- 2 x 24 core haswell CPU (X86_64) CPUs
- One NVIDIA Tesla P100, 16GB Tensor Core GPU
- 120 GB system memory
BEAR AI Service
The BEAR AI service is our IBM POWER9 AI cluster. Please see the BEAR AI page for more details on this service and how to request access.