A Machine Learning Framework for Performance Coverage Analysis of Proxy Applications

Tanzima Z. Islam, Jayaraman J. Thiagarajan, Abhinav Bhatele, Martin Schulz, Todd Gamblin

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

17 Zitate (Scopus)

Abstract

Proxy applications are written to represent subsets of performance behaviors of larger, and more complex applications that often have distribution restrictions. They enable easy evaluation of these behaviors across systems, e.g., for procurement or co-design purposes. However, the intended correlation between the performance behaviors of proxy applications and their parent codes is often based solely on the developer's intuition. In this paper, we present novel machine learning techniques to methodically quantify the coverage of performance behaviors of parent codes by their proxy applications. We have developed a framework, VERITAS, to answer these questions in the context of on-node performance: A) which hardware resources are covered by a proxy application and how well, and b) which resources are important, but not covered. We present our techniques in the context of two benchmarks, STREAM and DGEMM, and two production applications, OpenMC and CMTnek, and their respective proxy applications.

OriginalspracheEnglisch
TitelProceedings of SC 2016
UntertitelThe International Conference for High Performance Computing, Networking, Storage and Analysis
Herausgeber (Verlag)IEEE Computer Society
Seiten538-549
Seitenumfang12
ISBN (elektronisch)9781467388153
DOIs
PublikationsstatusVeröffentlicht - 2 Juli 2016
Extern publiziertJa
Veranstaltung2016 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2016 - Salt Lake City, USA/Vereinigte Staaten
Dauer: 13 Nov. 201618 Nov. 2016

Publikationsreihe

NameInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC
Band0
ISSN (Print)2167-4329
ISSN (elektronisch)2167-4337

Konferenz

Konferenz2016 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2016
Land/GebietUSA/Vereinigte Staaten
OrtSalt Lake City
Zeitraum13/11/1618/11/16

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