Synthesizing efficient out-of-core programs for block recursive algorithms using block-cyclic data distributions

This paper presents a framework for synthesizing I/O-efficient out-of-core programs for block recursive algorithms, such as the fast Fourier transform and matrix transpositions. the programs are synthesized from tensor (Kronecker) product representations of algorithms. These programs are optimized f...

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Vydáno v:Proceedings of the 1996 ICPP Workshop on Challenges for Parallel Processing Ročník 2; s. 142 - 149 vol.2
Hlavní autoři: Zhiyong Li, Reif, J.H., Gupta, K.S.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 1996
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ISBN:9780818676239, 081867623X
ISSN:0190-3918
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Abstract This paper presents a framework for synthesizing I/O-efficient out-of-core programs for block recursive algorithms, such as the fast Fourier transform and matrix transpositions. the programs are synthesized from tensor (Kronecker) product representations of algorithms. These programs are optimized for a striped two-level memory model where in the out-of-core data can have block-cyclic distributions on multiple disks.
AbstractList This paper presents a framework for synthesizing I/O-efficient out-of-core programs for block recursive algorithms, such as the fast Fourier transform and matrix transpositions. the programs are synthesized from tensor (Kronecker) product representations of algorithms. These programs are optimized for a striped two-level memory model where in the out-of-core data can have block-cyclic distributions on multiple disks.
Author Zhiyong Li
Reif, J.H.
Gupta, K.S.
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  givenname: K.S.
  surname: Gupta
  fullname: Gupta, K.S.
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Snippet This paper presents a framework for synthesizing I/O-efficient out-of-core programs for block recursive algorithms, such as the fast Fourier transform and...
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StartPage 142
SubjectTerms Communication networks
Computational fluid dynamics
Computer applications
Computer science
Concurrent computing
Contracts
Dynamic programming
Fast Fourier transforms
Hardware
Tensile stress
Title Synthesizing efficient out-of-core programs for block recursive algorithms using block-cyclic data distributions
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