Overview of Brown-GPU

Brown-GPU is Purdue's newest Community Cluster and is optimized for communities running traditional, tightly-coupled science and engineering applications. Brown-GPU built through a partnership with Dell and Intel in March 2018. Brown-GPU consists of Dell compute nodes with two 12-core Intel Xeon Gold "Sky Lake" processors (24 cores per node), 96 GB of memory, and three Tesla P100 GPUs. All nodes have 100 Gbps EDR Infiniband interconnect and a 5-year warranty.

To purchase access to Brown-GPU today, go to the Cluster Access Purchase page. Please subscribe to our Community Cluster Program Mailing List to stay informed on the latest purchasing developments or contact us via email at rcac-cluster-purchase@lists.purdue.edu if you have any questions.

Brown-GPU Namesake

Brown-GPU is named in honor of Herbert C. Brown, Nobel Laureate and Professor of Chemistry. More information about his life and impact on Purdue is available in an ITaP Biography of Herbert C. Brown.

Brown-GPU Detailed Hardware Specification

All Brown-GPU nodes have 24 processor cores, 96 GB of RAM, and 100 Gbps Infiniband interconnects.
Front-Ends Number of Nodes Processors per Node Cores per Node Memory per Node Retires in
With GPU 1 Two Sky Lake CPUs @ 2.60GHz with three Tesla P100 GPUs 24 192 GB 2023
Sub-Cluster Number of Nodes Processors per Node Cores per Node Memory per Node Retires in
A 15 Two Sky Lake CPUs @ 2.60GHz with three Tesla P100 GPUs 24 192 GB 2023

Brown-GPU nodes run CentOS 7 and use Moab Workload Manager 8 and TORQUE Resource Manager 5 as the portable batch system (PBS) for resource and job management. The application of operating system patches occurs as security needs dictate. All nodes allow for unlimited stack usage, as well as unlimited core dump size (though disk space and server quotas may still be a limiting factor).

On Brown-GPU, ITaP recommends the following set of compiler, math library, and message-passing library for parallel code:

  • Intel 17.0.1.132
  • MKL
  • Intel MPI

This compiler and these libraries are loaded by default. To load the recommended set again:

$ module load rcac

To verify what you loaded:

$ module list

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