From Merging Frameworks to Merging Stars: Experiences using HPX, Kokkos and SIMD Types

Gregor Daiß, Srinivas Yadav Singanaboina, Patrick Diehl, H. Kaiser, D. Pflüger
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引用次数: 3

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.
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从合并框架到合并明星:使用HPX, Kokkos和SIMD类型的经验
Octo-Tiger是一种用于星合并的大规模3D AMR代码,它结合了HPX、Kokkos和显式SIMD类型,旨在实现广泛的异构硬件的性能可移植性。然而,在A64FX cpu上,我们遇到了几个缺失的部分,导致SIMD矢量化问题,从而影响了性能。因此,我们添加了std::experimental::simd作为Octo-Tiger的Kokkos内核中与Kokkos simd一起使用的选项,并进一步添加了一个新的SVE(可伸缩向量扩展)simd后端。此外,我们还在Octo-Tiger的hydro求解器中修改了Kokkos内核中缺失的SIMD实现。我们通过在三个不同的CPU上运行Octo-Tiger来测试我们的变化:一个A64FX,一个Intel Icelake和一个AMD EPYC CPU,评估SIMD加速和节点级性能。我们在A64FX CPU上获得了很好的SIMD加速,在其他两个CPU平台上也有明显的加速。然而,我们在EPYC CPU上也遇到了缩放问题。
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