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面向开放ISA的超级计算:RISC-V、Arm与x86架构在HPC工作负载上的比较研究

arXiv:2610.32632v1 发布类型:新 摘要:RISC‑V 正在成为高性能计算(HPC)领域的候选架构,但其与成熟的 x86 和 Arm 处理器相比的竞争力仍难以评估,因为现有研究采用的平台、工作负载和方法各不相同,且很少考虑能效。我们的工作基于统一的软件栈和评估方法,对当前主流的 HPC RISC‑V、Arm 和 x86 处理器进行了全面评测。我们详细分析了 Sophgo SG2044,并将其与 NVIDIA Grace CPU 超级芯片以及 Intel Xeon Platinum 8480+ 在四项 HPC 基准测试(STREAM、HPL、HPL‑MxP 和 HPCG)以及四款典型应用(iPIC3D、PLUTO、OpenFOAM 和 llama.cpp)上进行了对比。用于本研究的 HPL‑MxP 版本链接至 OpenBLAS,并以此为基础进行构建和测试……

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Abstract:RISC-V is emerging as a candidate architecture for high-performance computing (HPC), but its competitiveness against established x86 and Arm processors remains difficult to assess because existing studies use different platforms, workloads, and methodologies, and rarely consider energy efficiency. Our work provides an evaluation of contemporary HPC RISC-V, Arm, and x86 processors using a common software stack and methodology. We characterize the Sophgo SG2044 and compare it with the NVIDIA Grace CPU Superchip and Intel Xeon Platinum 8480+ across four HPC benchmarks (STREAM, HPL, HPL-MxP, and HPCG) and four representative applications (iPIC3D, PLUTO, OpenFOAM, and this http URL). The version of HPL-MxP linked to OpenBLAS built and used for this work is made available as open-source software. The SG2044 reaches 8.02 GFLOP/s of FP64 performance and 7.8 GB/s of memory bandwidth per core, increasing to 294 GFLOP/s and 107 GB/s at 64 cores. L2-cache-aware process placement enables near-linear scaling up to 16 cores, beyond which memory-bandwidth saturation limits further gains. Across generations of RISC-V hardware, in the context of the Monte Cimone (MC) project, the SG2044-based MCv3 doubles both single-core performance and peak memory bandwidth relative to MCv2, while improving memory bandwidth, node-level FP64 performance, and energy efficiency by approximately 100x, 158x, and 10x, over MCv1. Against the Arm and x86 systems, the SG2044 shows 8-15x less absolute performance, reflecting its narrower vector resources and less advanced technology node, but delivers competitive scaling and energy efficiency on several workloads. Its most notable result is LLM decode, where 64-core execution provides the highest relative scaling and energy efficiency among the evaluated platforms while exceeding Intel in throughput. Our results show that RISC-V processors are closing the gap with the competition.

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