A Multi-level Optimization Strategy to Improve the Performance of Stencil Computation - Archive ouverte HAL Access content directly
Journal Articles Procedia Computer Science Year : 2017

A Multi-level Optimization Strategy to Improve the Performance of Stencil Computation

Abstract

Stencil computation represents an important numerical kernel in scientific computing. Leveraging multi-core or many-core parallelism to optimize such operations represents a major challenge due to both the bandwidth demand and the low arithmetic intensity. The situation is worsened by the complexity of current architectures and the potential impact of various mechanisms (cache memory, vectorization, compilation). In this paper, we describe a multi-level optimization strategy that combines manual vectorization, space tiling and stencil composition. A major effort of this study is to compare our results with the Pochoir framework. We evaluate our methodology with a set of three different compilers (Intel, Clang and GCC) on two recent generations of Intel multi-core platforms. Our results show a good match with the theoretical performance models (i.e. roofline models). We also outperform Pochoir performance by a factor of x2.5 in the best case.
Fichier principal
Vignette du fichier
1-s2.0-S1877050917308153-main.pdf (689.31 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03702849 , version 1 (23-06-2022)

Identifiers

Cite

Gauthier Sornet, Fabrice Dupros, Sylvain Jubertie. A Multi-level Optimization Strategy to Improve the Performance of Stencil Computation. Procedia Computer Science, 2017, 108, pp.1083 - 1092. ⟨10.1016/j.procs.2017.05.217⟩. ⟨hal-03702849⟩
33 View
70 Download

Altmetric

Share

Gmail Facebook X LinkedIn More