Exploring Fast Fourier Transforms on the Tenstorrent Wormhole
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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.
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Cited by 2 Pith papers
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Stencil kernels on Tenstorrent Wormhole match CPU speed in isolation but lag overall due to PCIe and initialization overheads, with lower energy use for large inputs via the Axpy mapping.
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Assessing Performance and Porting Strategies for Gravitational $N$-Body Simulations on the RISC-V-Based Tenstorrent Wormhole\textsuperscript{\texttrademark}
Three scaling strategies for an N-body code on Tenstorrent Wormhole accelerators are compared via execution time and energy measurements, identifying the configuration with the best efficiency-performance balance.
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