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YaskSite : Stencil Optimization Techniques Applied to Explicit ODE Methods on Modern Architectures

Title data

Alappat, Christie L. ; Seiferth, Johannes ; Hager, Georg ; Korch, Matthias ; Rauber, Thomas ; Wellein, Gerhard:
YaskSite : Stencil Optimization Techniques Applied to Explicit ODE Methods on Modern Architectures.
In: Lee, Jae W. ; Soffa, Mary Lou ; Zaks, Ayal (ed.): 2021 IEEE/ACM International Symposium on Code Generation and Optimization (CGO) : Proceedings. - Piscataway, NJ , 2021 . - pp. 174-186
ISBN 978-1-7281-8613-9
DOI: https://doi.org/10.1109/CGO51591.2021.9370316

Project information

Project title:
Project's official titleProject's id
Selbstadaption für zeitschrittbasierte Simulationstechniken auf heterogenen HPC-Systemen (SeASiTe)01IH16012A, 01IH16012C

Project financing: Bundesministerium für Bildung und Forschung

Abstract in another language

The landscape of multi-core architectures is growing more complex and diverse. Optimal application performance tuning parameters can vary widely across CPUs, and finding them in a possibly multidimensional parameter search space can be time consuming, expensive and potentially infeasible. In this work, we introduce YaskSite, a tool capable of tackling these challenges for stencil computations. YaskSite is built upon Intel's YASK framework. It combines YASK's flexibility to deal with different target architectures with the Execution-Cache-Memory performance model, which enables identifying optimal performance parameters analytically without the need to run the code. Further we show that YaskSite's features can be exploited by external tuning frameworks to reliably select the most efficient kernel(s) for the application at hand. To demonstrate this, we integrate YaskSite into Offsite, an offline tuner for explicit ordinary differential equation methods, and show that the generated performance predictions are reliable and accurate, leading to considerable performance gains at minimal code generation time and autotuning costs on the latest Intel Cascade Lake and AMD Rome CPUs.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science II > Chair Applied Computer Science II - Univ.-Prof. Dr. Thomas Rauber
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 18 Jul 2022 07:10
Last Modified: 18 Jul 2022 07:10
URI: https://eref.uni-bayreuth.de/id/eprint/70579