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Conference Papers Year : 2010

Automatic Parallelization and Locality Optimization of Beamforming Algorithms

Abstract

This paper demonstrates the benefits of a global optimization strategy using a new automatic parallelization and locality optimization methodology for high performance embedded computing algorithms that occur in adaptive radar systems, for modern multi-core computing chips. As a baseline, the resulting performance was compared against the performance that could be obtained using highly optimized math libraries.
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Dates and versions

inria-00551070 , version 1 (02-01-2011)

Identifiers

  • HAL Id : inria-00551070 , version 1

Cite

Albert Hartono, Nicolas Vasilache, Cédric Bastoul, Allen Leung, Benoît Meister, et al.. Automatic Parallelization and Locality Optimization of Beamforming Algorithms. High Performance Embedded Computing Workshop (HPEC), Sep 2010, MIT Lincoln Laboratory, Lexington, Massachusetts, United States. ⟨inria-00551070⟩
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