Performance model for parallel mathematical libraries based on historical knowledgebase

I. Salawdeh*, E. César, A. Morajko, T. Margalef, E. Luque

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)


Scientific and mathematical parallel libraries offer a high level of abstraction to programmers. However, it is still difficult to select the proper parameters and algorithms to maximize the application performance. This work proposes a performance model for dynamically adjusting applications written with the PETSc library. This model is based on historical performance information and data mining techniques. Finally, we demonstrate the validity of the proposed model through real experimentations.

Original languageAmerican English
Pages (from-to)110-119
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publication statusPublished - 2008


  • Dynamic mathematical model
  • Mathematical Performance
  • Performance Model
  • PETSc Performance


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