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Media type:
E-Article
Title:
Optimization of Finite-Differencing Kernels for Numerical Relativity Applications
Contributor:
Alfieri, Roberto;
Bernuzzi, Sebastiano;
Perego, Albino;
Radice, David
Published:
MDPI AG, 2018
Published in:
Journal of Low Power Electronics and Applications, 8 (2018) 2, Seite 15
Language:
English
DOI:
10.3390/jlpea8020015
ISSN:
2079-9268
Origination:
Footnote:
Description:
A simple optimization strategy for the computation of 3D finite-differencing kernels on many-cores architectures is proposed. The 3D finite-differencing computation is split direction-by-direction and exploits two level of parallelism: in-core vectorization and multi-threads shared-memory parallelization. The main application of this method is to accelerate the high-order stencil computations in numerical relativity codes. Our proposed method provides substantial speedup in computations involving tensor contractions and 3D stencil calculations on different processor microarchitectures, including Intel Knight Landing.