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Generating Fast FFT Kernels on CPUs via FFT-Specific Intrinsics

Published: 21 February 2023 Publication History

Abstract

This paper proposes an algorithm-specific instruction (ASI)-based fast Fourier transform (FFT) code generation framework, named FFTASI, to generate unified architecture independent butterfly kernels that can be transformed into architecture-dependent kernels by establishing the mapping between ASIs and architecture-specific instructions for various hardware platforms. FFTASI strikes a good balance between performance and productivity on CPUs.

References

[1]
Krste Asanovic, Ras Bodik, James Demmel, Tony Keaveny, Kurt Keutzer, John D Kubiatowicz, Edward A Lee, Nelson Morgan, George Necula, David A Patterson, et al. 2008. The parallel computing laboratory at UC Berkeley: A research agenda based on the Berkeley view. EECS Department, University of California, Berkeley, Tech. Rep (2008).
[2]
Matteo Frigo and Steven G. Johnson. 2005. The Design and Implementation of FFTW3. Proc. IEEE 93, 2 (2005), 216--231. Special issue on "Program Generation, Optimization, and Platform Adaptation".
[3]
Zhihao Li, Haipeng Jia, Yunquan Zhang, Tun Chen, Liang Yuan, Luning Cao, and Xiao Wang. 2019. AutoFPT: a template-based FFT codes auto-generation framework for ARM and X86 CPUs. In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis. 1--15.
[4]
Zhihao Li, Haipeng Jia, Yunquan Zhang, Tun Chen, Liang Yuan, and Richard Vuduc. 2020. Automatic generation of high-performance fft kernels on arm and x86 cpus. IEEE Transactions on Parallel and Distributed Systems 31, 8 (2020), 1925--1941.

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Published In

cover image ACM Conferences
PPoPP '23: Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
February 2023
480 pages
ISBN:9798400700156
DOI:10.1145/3572848
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 February 2023

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Author Tags

  1. FFT
  2. FFTASI
  3. RISC-V
  4. SVE
  5. code generation

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  • Poster

Funding Sources

  • National Natural Science Foundation of China

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PPoPP '23

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Overall Acceptance Rate 230 of 1,014 submissions, 23%

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