Accelerating stencils on the Tenstorrent Grayskull RISC-V accelerator
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912048469770240 |
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| author | Brown, Nick Barton, Ryan |
| author_facet | Brown, Nick Barton, Ryan |
| contents | The RISC-V Instruction Set Architecture (ISA) has enjoyed phenomenal growth in recent years, however it still to gain popularity in HPC. Whilst adopting RISC-V CPU solutions in HPC might be some way off, RISC-V based PCIe accelerators offer a middle ground where vendors benefit from the flexibility of RISC-V yet fit into existing systems.
In this paper we focus on the Tenstorrent Grayskull PCIe RISC-V based accelerator which, built upon Tensix cores, decouples data movement from compute. Using the Jacobi iterative method as a vehicle, we explore the suitability of stencils on the Grayskull e150. We explore best practice in structuring these codes for the accelerator and demonstrate that the e150 provides similar performance to a Xeon Platinum CPU (albeit BF16 vs FP32) but the e150 uses around five times less energy. Over four e150s we obtain around four times the CPU performance, again at around five times less energy. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2409_18835 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Accelerating stencils on the Tenstorrent Grayskull RISC-V accelerator Brown, Nick Barton, Ryan Distributed, Parallel, and Cluster Computing The RISC-V Instruction Set Architecture (ISA) has enjoyed phenomenal growth in recent years, however it still to gain popularity in HPC. Whilst adopting RISC-V CPU solutions in HPC might be some way off, RISC-V based PCIe accelerators offer a middle ground where vendors benefit from the flexibility of RISC-V yet fit into existing systems. In this paper we focus on the Tenstorrent Grayskull PCIe RISC-V based accelerator which, built upon Tensix cores, decouples data movement from compute. Using the Jacobi iterative method as a vehicle, we explore the suitability of stencils on the Grayskull e150. We explore best practice in structuring these codes for the accelerator and demonstrate that the e150 provides similar performance to a Xeon Platinum CPU (albeit BF16 vs FP32) but the e150 uses around five times less energy. Over four e150s we obtain around four times the CPU performance, again at around five times less energy. |
| title | Accelerating stencils on the Tenstorrent Grayskull RISC-V accelerator |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2409.18835 |