Optimization of Finite-Differencing Kernels for Numerical Relativity Applications
Keyword(s):
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.
2020 ◽
Vol 255
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pp. 107245
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Keyword(s):
2021 ◽
2020 ◽
Vol 372
◽
pp. 112722
2003 ◽
Vol 20
(20)
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pp. L245-L251
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