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2022 IEEE/ACM 7th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2)最新文献

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Broad Performance Measurement Support for Asynchronous Multi-Tasking with APEX 广泛的性能测量支持异步多任务与APEX
2022 IEEE/ACM 7th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) Pub Date : 2022-11-01 DOI: 10.1109/ESPM256814.2022.00008
K. Huck
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引用次数: 1
A Selective Nesting Approach for the Sparse Multi-threaded Cholesky Factorization 稀疏多线程Cholesky分解的选择性嵌套方法
2022 IEEE/ACM 7th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) Pub Date : 2022-11-01 DOI: 10.1109/ESPM256814.2022.00006
Valentin Le Fèvre, Tetsuzo Usui, Marc Casas
{"title":"A Selective Nesting Approach for the Sparse Multi-threaded Cholesky Factorization","authors":"Valentin Le Fèvre, Tetsuzo Usui, Marc Casas","doi":"10.1109/ESPM256814.2022.00006","DOIUrl":"https://doi.org/10.1109/ESPM256814.2022.00006","url":null,"abstract":"Sparse linear algebra routines are fundamental building blocks of a large variety of scientific applications. Direct solvers, which are methods for solving linear systems via the factorization of matrices into products of triangular matrices, are commonly used in many contexts. The Cholesky factorization is the fastest direct method for symmetric and positive definite matrices. This paper presents selective nesting, a method to determine the optimal task granularity for the parallel Cholesky factorization based on the structure of sparse matrices. We propose the Opt-D algorithm, which automatically and dynamically applies selective nesting. Opt-D leverages matrix sparsity to drive complex task-based parallel workloads in the context of direct solvers. We run an extensive evaluation campaign considering a heterogeneous set of 35 sparse matrices and a parallel machine featuring the A64FX processor. Opt-D delivers an average performance speedup of 1.75× with respect to the best state-of-the-art parallel methods to run direct solvers.","PeriodicalId":340754,"journal":{"name":"2022 IEEE/ACM 7th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2)","volume":"25 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114037472","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
From Merging Frameworks to Merging Stars: Experiences using HPX, Kokkos and SIMD Types 从合并框架到合并明星:使用HPX, Kokkos和SIMD类型的经验
2022 IEEE/ACM 7th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2) Pub Date : 2022-09-26 DOI: 10.1109/ESPM256814.2022.00007
Gregor Daiß, Srinivas Yadav Singanaboina, Patrick Diehl, H. Kaiser, D. Pflüger
{"title":"From Merging Frameworks to Merging Stars: Experiences using HPX, Kokkos and SIMD Types","authors":"Gregor Daiß, Srinivas Yadav Singanaboina, Patrick Diehl, H. Kaiser, D. Pflüger","doi":"10.1109/ESPM256814.2022.00007","DOIUrl":"https://doi.org/10.1109/ESPM256814.2022.00007","url":null,"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.","PeriodicalId":340754,"journal":{"name":"2022 IEEE/ACM 7th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128881602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
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