Non-Recurring Engineering (NRE) Best Practices: A Case Study with the NERSC/NVIDIA OpenMP Contract

Authors: Christopher Daley (Lawrence Berkeley National Laboratory (LBNL)); Annemarie Southwell (NVIDIA Corporation); Rahulkumar Gayatri (Lawrence Berkeley National Laboratory (LBNL)); Scott Biersdorff, Craig Toepfer, and Guray Ozen (NVIDIA Corporation); and Nicholas Wright (Lawrence Berkeley National Laboratory (LBNL))

Abstract: The NERSC supercomputer, Perlmutter, consists of AMD CPUs and NVIDIA GPUs. NERSC users expect to be able to use OpenMP to take advantage of the highly capable GPUs. This paper describes how NERSC/NVIDIA constructed a Non-Recurring Engineering (NRE) contract to add OpenMP GPU-offload support to the NVIDIA HPC compilers. The paper describes how the contract incorporated the strengths of both parties and encouraged collaboration to improve the quality of the final deliverable. We include our best practices and how this particular contract took into account emerging OpenMP specifications, NERSC workload requirements and how to use OpenMP most efficiently on GPU hardware. This paper includes OpenMP application performance results obtained with the NVIDIA compilers distributed in the NVIDIA HPC SDK.


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