Document Type
Conference Proceeding
Publication Date
1-1-2022
Abstract
Octo-Tiger, a large-scale 3D AMR code for the merger of stars, uses a combination of HPX, Kokkos and explicit SIMD types, aiming to achieve performance-portability for a broad range of heterogeneous hardware. However, on A64FX CPUs, we encountered several missing pieces, hindering performance by causing problems with the SIMD vectorization. Therefore, we add std:experimental:simd as an option to use in Octo-Tiger's Kokkos kernels alongside Kokkos SIMD, and further add a new SVE (Scalable Vector Extensions) SIMD backend. Additionally, we amend missing SIMD implementations in the Kokkos kernels within Octo-Tiger's hydro solver. We test our changes by running Octo-Tiger on three different CPUs: An A64FX, an Intel Icelake and an AMD EPYC CPU, evaluating SIMD speedup and node-level performance. We get a good SIMD speedup on the A64FX CPU, as well as noticeable speedups on the other two CPU platforms. However, we also experience a scaling issue on the EPYC CPU.
Publication Source (Journal or Book title)
Proceedings of 2022 ACM/IEEE 7th International Workshop on Extreme Scale Programming Models and Middleware, ESPM2 2022, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis
First Page
10
Last Page
19
Recommended Citation
Dais, G., Singanaboina, S., Diehl, P., Kaiser, H., & Pfluger, D. (2022). From Merging Frameworks to Merging Stars: Experiences using HPX, Kokkos and SIMD Types. Proceedings of 2022 ACM/IEEE 7th International Workshop on Extreme Scale Programming Models and Middleware, ESPM2 2022, Held in conjunction with SC 2022: The International Conference for High Performance Computing, Networking, Storage and Analysis, 10-19. https://doi.org/10.1109/ESPM256814.2022.00007