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Spiral: A Generator for Platform-Adapted Libraries of Signal Processing Alogorithms
Journal article   Peer reviewed

Spiral: A Generator for Platform-Adapted Libraries of Signal Processing Alogorithms

Markus Püschel, José M. F. Moura, Bryan Singer, Jianxin Xiong, Jeremy Johnson, David Padua, Manuela Veloso, Robert W. Johnson and Jamila Danielle Johnson
The international journal of high performance computing applications, v 18(1), pp 21-45
Feb 2004
DOI: https://doi.org/10.1177/1094342004041291

Abstract

signal transform automatic performance tuning domain-specific language DFT signal processing FFT optimization seach Fourier transform program generation
SPIRAL is a generator for libraries of fast software implementations of linear signal processing transforms. These libraries are adapted to the computing platform and can be re-optimized as the hardware is upgraded or replaced. This paper describes the main components of SPIRAL: the mathematical framework that concisely describes signal transforms and their fast algorithms; the formula generator that captures at the algorithmic level the degrees of freedom in expressing a particular signal processing transform; the formula translator that encapsulates the compilation degrees of freedom when translating a specific algorithm into an actual code implementation; and, finally, an intelligent search engine that finds within the large space of alternative formulas and implementations the “best” match to the given computing platform. We present empirical data that demonstrate the high performance of SPIRAL generated code.

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84 citations in Web of Science
124 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Computer Science, Hardware & Architecture
Computer Science, Interdisciplinary Applications
Computer Science, Theory & Methods
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