Compile-time based performance prediction

Calin Cascaval, Luiz De Rose, David A. Padua, Daniel A. Reed

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


In this paper we present results we obtained using a compiler to predict performance of scientific codes. The compiler, Polaris [3], is both the primary tool for estimating the performance of a range of codes, and the beneficiary of the results obtained from predicting the program behavior at compile time. We show that a simple compile-time model, augmented with profiling data obtained using very light instrumentation, can be accurate within 20% (on average) of the measured performance for codes using both dense and sparse computational methods.

Original languageEnglish (US)
Title of host publicationLanguages and Compilers for Parallel Computing - 12th International Workshop, LCPC 1999, Proceedings
EditorsLarry Carter, Jeanne Ferrante
Number of pages15
ISBN (Print)9783540678588
StatePublished - 2000
Event12th International Workshop on Languages and Compilers for Parallel Computing, LCPC 1999 - La Jolla, United States
Duration: Aug 4 1999Aug 6 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other12th International Workshop on Languages and Compilers for Parallel Computing, LCPC 1999
Country/TerritoryUnited States
CityLa Jolla

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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