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Evaluating Performance Portability of a Seismic Survey Simulation across GPU Architectures
DescriptionWith the increasing use of graphic processing units (GPUs) from various vendors in oil and gas companies, achieving code portability has become essential. This capability allows for evaluating performance across diverse GPU vendors, facilitating well-informed decisions, and promoting competition and innovation in GPU technologies. We have made significant contributions in addressing the challenge of achieving performance portability for Fletcher, an anisotropic wave propagation modeling application across GPUs from NVIDIA and AMD. Our first contribution involves the implementation of Fletcher on GPUs using ten variations of portable programming models, including HIP, CUDA, Kokkos, and RAJA. Our second contribution is a comprehensive evaluation of these implementations across five generations of GPUs from NVIDIA and AMD, assessing performance and performance-portability. A series of extensive experiments demonstrated that HIP outperforms the assessed programming models regarding performance portability across all evaluated GPUs. Specifically, it performs 7.9% better than Kokkos and 8.8% better than RAJA.