Novel views of performance data to analyze large-scale adaptive applications

Abhinav Bhatele, Todd Gamblin, Katherine E. Isaacs, Brian T.N. Gunney, Martin Schulz, Peer Timo Bremer, Bernd Hamann

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

11 Zitate (Scopus)

Abstract

Performance analysis of parallel scientific codes is becoming increasingly difficult due to the rapidly growing complexity of applications and architectures. Existing tools fall short in providing intuitive views that facilitate the process of performance debugging and tuning. In this paper, we extend recent ideas of projecting and visualizing performance data for faster, more intuitive analysis of applications. We collect detailed per-level and per-phase measurements for a dynamically load-balanced, structured AMR library and project per-core data collected in the hardware domain on to the application's communication topology. We show how our projections and visualizations lead to a rapid diagnosis of and mitigation strategy for a previously elusive scaling bottleneck in the library that is hard to detect using conventional tools. Our new insights have resulted in a 22% performance improvement for a 65,536-core run of the AMR library on an IBM Blue Gene/P system.

OriginalspracheEnglisch
Titel2012 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012
DOIs
PublikationsstatusVeröffentlicht - 2012
Extern publiziertJa
Veranstaltung2012 24th International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012 - Salt Lake City, UT, USA/Vereinigte Staaten
Dauer: 10 Nov. 201216 Nov. 2012

Publikationsreihe

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

Konferenz

Konferenz2012 24th International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012
Land/GebietUSA/Vereinigte Staaten
OrtSalt Lake City, UT
Zeitraum10/11/1216/11/12

Fingerprint

Untersuchen Sie die Forschungsthemen von „Novel views of performance data to analyze large-scale adaptive applications“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren