Performance modeling for DFT algorithms in FFTW

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Performance modeling for DFT algorithms in FFTW

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International Conference on Supercomputing archive
Proceedings of the 23rd international conference on Supercomputing table of contents

Yorktown Heights, NY, USA

POSTER SESSION: Posters table of contents

Pages: 507-508

Year of Publication: 2009

ISBN:978-1-60558-498-0

Authors

Liang Gu	University of Delaware, Newark, DE, USA
Xiaoming Li	University of Delaware, Newark, DE, USA

Sponsors

ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 13, Downloads (12 Months): 78, Citation Count: 0

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ABSTRACT

Fast Fourier Transform in the West(FFTW) is one of the most successful adaptive Discrete Fourier Transform(DFT) libraries. The high-performance of FFTW mostly derives from its empirical search engine that includes all major DFT algorithms. We propose an adaptive model-driven FT performance prediction technique to replace the empirical search engine in FFTW. Our model achieves over 94% of the DFT performance and uses less than 5% of the search time compared with FFTW Exhaustive search on four test platforms.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	M. Frigo and S. G. Johnson. The design and implementation of fftw3. Proceeding of the IEEE, 93(2):216--231, February 2005.
	2	M. Püschel and J. M. F. M. etc. SPIRAL: Code generation for DSP transforms. Proceedings of the IEEE, 93(2):232--275, 2005.
	3	Rafael H. Saavedra , Alan J. Smith, Analysis of benchmark characteristics and benchmark performance prediction, ACM Transactions on Computer Systems (TOCS), v.14 n.4, p.344-384, Nov. 1996 [doi>10.1145/235543.235545]