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远大前景:评估RVV 1.0在高性能计算中的实际性能

Great Expectations: Benchmarking the Real-World Performance of RVV 1.0 in HPC

Stepan Nassyr, Prateek Chawla, Daniel Seibel, Jayesh Badwaik, Kaveh Haghighi Mood, Andreas Herten

arXiv 2608.28097首次发表:更新:

AI 中文总结

本文通过对多款支持RVV 1.0的硬件开展HPC基准测试,将其性能与NVIDIA Grace对比,发现RVV 1.0性能优于标量执行,但仍存在硬件实现挑战,需克服障碍才能成为HPC主流技术。

AI 中文摘要

在RISC-V向量扩展(RVV 1.0)获批后,新商用硅芯片已开始采用该扩展。本文通过对支持RVV 1.0的最新硬件(SiFive X280(Tenstorrent Blackhole)、SpacemiT X60(K1)及X100/A100(K3)、T-Head C920v2(Sophon SG2044))进行基准测试,重新探讨RISC-V在高性能计算(HPC)领域的可行性。我们采用标准HPC基准测试(BLAS、FFTW、HPL、HPCG)及合成工作负载(STREAM、FMA吞吐量)评估这些平台,并将其与最先进的HPC ARM64芯片(NVIDIA Grace)对比。研究发现,RVV 1.0相比标量执行能带来显著性能提升,但仍存在硬件特定实现挑战。我们详细阐述这些性能特征,并探讨RISC-V(包括RVV)成为HPC主流技术需克服的剩余障碍。

英文摘要

Following the ratification of the RISC-V Vector Extension (RVV 1.0), new commercially available silicon has been adopting the extension. This paper revisits the question of RISC-V viability for High-Performance-Computing (HPC) by benchmarking the latest RVV 1.0-capable hardware (SiFive X280 (Tenstorrent Blackhole), SpacemiT X60 (K1) and X100/A100 (K3), and T-Head C920v2 (Sophon SG2044)). We assess these platforms using standard HPC benchmarks (BLAS, FFTW, HPL, HPCG) and synthetic workloads (STREAM, FMA throughput) and compare them to a state-of-the-art HPC ARM64 chip (NVIDIA Grace). Our findings show that while RVV 1.0 delivers significant performance improvements over scalar execution, hardware-specific implementation challenges remain. We detail these performance characteristics and discuss the remaining hurdles for RISC-V, including RVV, to become a mainstay in the HPC landscape.

CommentsAccepted for International workshop on RISC-V for HPC at ISC26

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