Batched DGEMMs for scientific codes running on long vector architectures
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866917889219493888 |
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| author | Banchelli, Fabio Garcia-Gasulla, Marta Mantovani, Filippo |
| author_facet | Banchelli, Fabio Garcia-Gasulla, Marta Mantovani, Filippo |
| contents | In this work, we evaluate the performance of SeisSol, a simulator of seismic wave phenomena and earthquake dynamics, on a RISC-V-based system utilizing a vector processing unit. We focus on GEMM libraries and address their limited ability to leverage long vector architectures by developing a batched DGEMM library in plain C. This library achieves speedups ranging from approximately 3.5x to 32.6x compared to the reference implementation. We then integrate the batched approach into the SeisSol application, ensuring portability across different CPU architectures. Lastly, we demonstrate that our implementation is portable to an Intel CPU, resulting in improved execution times in most cases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_06175 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Batched DGEMMs for scientific codes running on long vector architectures Banchelli, Fabio Garcia-Gasulla, Marta Mantovani, Filippo Distributed, Parallel, and Cluster Computing In this work, we evaluate the performance of SeisSol, a simulator of seismic wave phenomena and earthquake dynamics, on a RISC-V-based system utilizing a vector processing unit. We focus on GEMM libraries and address their limited ability to leverage long vector architectures by developing a batched DGEMM library in plain C. This library achieves speedups ranging from approximately 3.5x to 32.6x compared to the reference implementation. We then integrate the batched approach into the SeisSol application, ensuring portability across different CPU architectures. Lastly, we demonstrate that our implementation is portable to an Intel CPU, resulting in improved execution times in most cases. |
| title | Batched DGEMMs for scientific codes running on long vector architectures |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2501.06175 |