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

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

7 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2012 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012
DOIs
StatePublished - Dec 1 2012
Externally publishedYes
Event2012 24th International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012 - Salt Lake City, UT, United States
Duration: Nov 10 2012Nov 16 2012

Publication series

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

Conference

Conference2012 24th International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012
CountryUnited States
CitySalt Lake City, UT
Period11/10/1211/16/12

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Software

Fingerprint Dive into the research topics of 'Novel views of performance data to analyze large-scale adaptive applications'. Together they form a unique fingerprint.

  • Cite this

    Bhatele, A., Gamblin, T., Isaacs, K. E., Gunney, B. T. N., Schulz, M., Bremer, P. T., & Hamann, B. (2012). Novel views of performance data to analyze large-scale adaptive applications. In 2012 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2012 [6468450] (International Conference for High Performance Computing, Networking, Storage and Analysis, SC). https://doi.org/10.1109/SC.2012.80