Dynamic high-level scripting in parallel applications

Filippo Gioachin, Laxmikant V. Kalé

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

Abstract

Parallel applications typically run in batch mode, sometimes after long waits in a scheduler queue. In some situations, it would be desirable to interactively add new functionality to the running application, without having to recompile and rerun it. For example, a debugger could upload code to perform consistency checks, or a data analyst could upload code to perform new statistical tests. This paper presents a scalable technique to dynamically insert code into running parallel applications. We describe and evaluate an implementation of this idea that allows a user to upload Python code into running parallel applications. This uploaded code will run in concert with the main code. We prove the effectiveness of this technique in two case studies: parallel debugging to support introspection and data analysis of large cosmological datasets.

Original languageEnglish (US)
Title of host publicationIPDPS 2009 - Proceedings of the 2009 IEEE International Parallel and Distributed Processing Symposium
DOIs
StatePublished - Nov 25 2009
Event23rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2009 - Rome, Italy
Duration: May 23 2009May 29 2009

Publication series

NameIPDPS 2009 - Proceedings of the 2009 IEEE International Parallel and Distributed Processing Symposium

Other

Other23rd IEEE International Parallel and Distributed Processing Symposium, IPDPS 2009
Country/TerritoryItaly
CityRome
Period5/23/095/29/09

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Hardware and Architecture
  • Software

Fingerprint

Dive into the research topics of 'Dynamic high-level scripting in parallel applications'. Together they form a unique fingerprint.

Cite this