Self-adapting numerical software and automatic tuning of heuristics

Jack Dongarra, Victor Eijkhout

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

7 Scopus citations

Abstract

Self-Adapting Numerical Software (SANS) systems aim to bridge the knowledge gap that exists between the expertise of domain scientists, and the know-how that is needed to fulfill efficiently their computational demands. This know-how extends to algorith choice, computational grid utilization, and use of properly optimized kernels. A SANS system is a piece of meta software that mediates between the application program and the computational platform so that application scientists - with disparate levels of knowledge of algorithmic and programmatic complexities of the underlying numerical software - can easily realize numerical solvers and efficiently solve their problem. The main component of a SANS system is an Intelligent Agent that automates method selection based on data, algorithm and system attributes. The IA uses heuristics to make its decisions. In this paper we explain how the heuristics of the IA can be tuned over time by redundant testing and using the nature of many applications.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter M. A. Sloot, David Abramson, Alexander V. Bogdanov, Yuriy E. Gorbachev, Jack J. Dongarra, Albert Y. Zomaya
PublisherSpringer Verlag
Pages759-767
Number of pages9
ISBN (Print)3540401970, 9783540401971
DOIs
StatePublished - 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2660
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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