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arXiv · 2608.28076

Performance Evaluation of Fast Fourier Transforms on Emerging RISC-V Hardware with Vector Extension Support

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

This manuscript presents a performance evaluation of Fast Fourier Transform (FFT) implementations on emerging processors supporting the RISC-V Vector Extension (RVV 1.0). By introducing juFFTe, a light-weight high-performance library for discrete Fourier transforms, it is demonstrated how effective vectorization of performance-critical FFT kernels can be achieved on RVV-enabled hardware. Comprehensive benchmarks on three RVV 1.0-ready processors, the SiFive X280, the X100 core of the SpacemiT K3 and the C920v2 core of the Sophon SG2044, reveal substantial performance improvements of juFFTe (https://github.com/FZJ-JSC/juFFTe) over the widely used FFTW3 library. Although RVV-enabled platforms show promising results at this stage of development, a comparison with AMD's Zen 5 architecture indicates that RISC-V needs further maturing to reach the performance of established micro-architectures.

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Daniel Seibel, Kaveh Haghighi Mood, Jayesh Badwaik, Prateek Chawla, Stepan Nassyr, Andreas Herten. 2026-08-28. Performance Evaluation of Fast Fourier Transforms on Emerging RISC-V Hardware with Vector Extension Support. https://arxiv.org/abs/2608.28076

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