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Lessons in Programming Model Comparisons Using OpenMP and CUDA for Targetting GPUs

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Lessons in Programming Model Comparisons Using OpenMP and CUDA for Targetting GPUs
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CC Attribution 2.0 Belgium:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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In this talk we explore two programming models for GPU accelerated computing in a Fortran application: OpenMP with target directives and CUDA. We use an example application Riemann problem, a common problem in fluid dynamics, as our testing ground. This example application is implemented in GenASiS, a code being developed for astrophysics simulations. While OpenMP and CUDA are supported on the Summit supercomputer, its successor, an exascale supercomputer Frontier, will support OpenMP and translate CUDA-like models via HIP. In this work, we study and describe the differences and trade-offs between these programming models in terms of efforts and performance. Our hope is to provide insights on productivity and portability issues within these programming models.