Exploring Fast Fourier Transforms on the Tenstorrent Wormhole

Fuente: arXiv
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Main Authors: Brown, Nick, Davies, Jake, LeClair, Felix
Format: Preprint
Published: 2025
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author Brown, Nick
Davies, Jake
LeClair, Felix
author_facet Brown, Nick
Davies, Jake
LeClair, Felix
contents Whilst numerous areas of computing have adopted the RISC-V Instruction Set Architecture (ISA) wholesale in recent years, it is yet to become widespread in HPC. RISC-V accelerators offer a compelling option where the HPC community can benefit from the specialisation offered by the open nature of the standard but without the extensive ecosystem changes required when adopting RISC-V CPUs. In this paper we explore porting the Cooley-Tukey Fast Fourier Transform (FFT) algorithm to the Tenstorrent Wormhole PCIe RISC-V based accelerator. Built upon Tenstorrent's Tensix architecture, this technology decouples the movement of data from compute, potentially offering increased control to the programmer. Exploring different optimisation techniques to address the bottlenecks inherent in data movement, we demonstrate that for a 2D FFT whilst the Wormhole n300 is slower than a server-grade 24-core Xeon Platinum CPU, the Wormhole draws around 8 times less power and consumes around 2.8 times less energy than the CPU when computing the Fourier transform.
format Preprint
id arxiv_https___arxiv_org_abs_2506_15437
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Exploring Fast Fourier Transforms on the Tenstorrent Wormhole
Brown, Nick
Davies, Jake
LeClair, Felix
Distributed, Parallel, and Cluster Computing
Whilst numerous areas of computing have adopted the RISC-V Instruction Set Architecture (ISA) wholesale in recent years, it is yet to become widespread in HPC. RISC-V accelerators offer a compelling option where the HPC community can benefit from the specialisation offered by the open nature of the standard but without the extensive ecosystem changes required when adopting RISC-V CPUs. In this paper we explore porting the Cooley-Tukey Fast Fourier Transform (FFT) algorithm to the Tenstorrent Wormhole PCIe RISC-V based accelerator. Built upon Tenstorrent's Tensix architecture, this technology decouples the movement of data from compute, potentially offering increased control to the programmer. Exploring different optimisation techniques to address the bottlenecks inherent in data movement, we demonstrate that for a 2D FFT whilst the Wormhole n300 is slower than a server-grade 24-core Xeon Platinum CPU, the Wormhole draws around 8 times less power and consumes around 2.8 times less energy than the CPU when computing the Fourier transform.
title Exploring Fast Fourier Transforms on the Tenstorrent Wormhole
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2506.15437