MRI: Acquisition of a GPU Computing Cluster for UMass institute of Applied Life Sciences

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This effort, acquiring a Graphic Processing Unit (GPU)-enabled High-Performance Computing (HPC) cluster, enables computation intensive activities with the aim to leverage fundamental discoveries to enhance translational impacts. The Institute for Advanced Life Science (IALS) deals with big datasets where computation plays an integral role. The current cluster provided by the Massachusetts Green High Performance Computing Center (MGHPCC) is inadequate to meet current demands to support activities in many areas including atomistic and coarse-grained simulations, machine learning, and statistical analysis for next-generation bioinformatics and data science. Providing long-term stability for operation and management, the GPU cluster will serve 250 IALS-affiliated research labs across 27 departments and 7 colleges. The GPU facility offers high speed single and double precision operations as well as extreme parallelism, to enhance current activities that contribute to the open science movement.This infrastructure contributes to efforts to integrate regional education, outreach, diversity, and economic activities. The GPU facilities will be made available to researchers through Internet2 links and regional computing partnerships at MGHPCC. The hybrid GPU/CPU design, mixed precision speed, and machine learning-optimized architecture adds resources to continue development and distribution of powerful molecular modeling, ab initio dynamics and computational and statistical tools in open source packages, enabling rapid progress on problems of great societal import. Utilizing the infrastructure will most likely lead to new developments and discoveries including novel GPU-enabled modeling and simulation technologies that may elucidate molecular mechanism of drug delivery, computational design catalysts for renewable energy and chemical synthesis, advanced computational analysis tools for next generation informatics and big data, and improved understanding of risk and resistance to breast cancer.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.