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High Performance Computing Cluster

High Performance Computing

WTAMU now houses a recently acquired DELL high-performance compute cluster (NSF CC* GROWTH, #2018841) with 13 computational nodes, and 1 head node and 1 login node. Each computational node is equipped with 2x 32-core AMD EPYC processors. Three of the computational nodes are also equipped with 2x NVIDIA TESLA V100s GPUs. The cluster is designed to permit traditional MPI-based computation (molecular dynamics, fluid dynamics, solid mechanics, quantum chemistry) on 10 compute nodes and GPU-based computation (machine learning, data science, gpu-accelerated applications) on the remaining 3 compute nodes. All the nodes are connected by a high speed Mellanox Infiniband switch.

The major goals of the project are:

  • Develop cyberinfrastructure (CI, equipment and personnel) for computational and AI research for campus researchers.
  • Provide HPC computational resources for students to meet STEM educational goals.
  • Develop courses/course components that can harness CI facilities and spearhead CI workforce development.
  • Develop research programs and publish work that can capitalize on CI resources.
  • Share computational resources nationally across institutions and contribute to national cyberinfrastructure.

This cluster is open for use for all WTAMU faculty, students and staff. Investigators interested in gaining access to the cluster for research and faculty interested in utilizing the cluster for course-work can apply for HPC access in Agiloft. https://itsm.wtamu.edu

Please cite WTAMU HPC resources in any relevant published work. It can look like the following:

This work relied on computations performed on the WTAMU HPC cluster, which was funded by the National Science Foundation (NSF CC* GROWTH 2018841).

For any questions, please contact Dr. Anirban Pal (Principal Investigator) at apal@wtamu.edu or itsc@wtamu.edu.

LEARN HOW TO USE WTAMU-HPC

Run Python programs with CPU/GPU:

WTAMU-HPC Workshop (Markdown, Recording, 04/22/2022)

Texas A&M HPC resources and training: https://hprc.tamu.edu/training/

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