Quantifying Performance Bottlenecks of Stencil Computations Using the Execution-Cache-Memory Model

Holger Stengel, Jan Treibig, Georg Hager, Gerhard Wellein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

76 Scopus citations

Abstract

Stencil algorithms on regular lattices appear in many fields of computational science, and much effort has been put into optimized implementations. Such activities are usually not guided by performance models that provide estimates of expected speedup. Understanding the performance properties and bottlenecks by performance modeling enables a clear view on promising optimization opportunities. In this work we refine the recently developed Execution-Cache-Memory (ECM) model and use it to quantify the performance bottlenecks of stencil algorithms on a contemporary Intel processor. This includes applying the model to arrive at single-core performance and scalability predictions for typical "corner case" stencil loop kernels. Guided by the ECM model we accurately quantify the significance of "layer conditions," which are required to estimate the data traffic through the memory hierarchy, and study the impact of typical optimization approaches such as spatial blocking, strength reduction, and temporal blocking for their expected benefits. We also compare the ECM model to the widely known Roofline model.
Original languageEnglish (US)
Title of host publicationProceedings of the 29th ACM on International Conference on Supercomputing
PublisherACM
Pages207-216
Number of pages10
ISBN (Print)9781450335591
DOIs
StatePublished - Jun 8 2015
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2022-06-23
Acknowledgements: We thank Andrey Semin (Intel Germany) for useful discussions, Olaf Schenk (USI Lugano) for providing the “uxx” benchmark case, and Hatem Ltaief (KAUST) for providing the 3D long-range stencil case. Part of this work was supported by the DFG priority programme 1648 “SPPEXA” under the project “EXASTEEL.”
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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