Towards an Automatic and Application-Based EigensolverSelection

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The computation of eigenvalues and eigenvectors is an important and often time-consuming phase in computer simulations. Recent efforts in the development of eigensolver libraries have given users good algorithms without the need for users to spend much time in programming. Yet, given the variety of numerical algorithms that are available to domain scientists, choosing the ''best'' algorithm suited for a particular application is a daunting task. As simulations become increasingly sophisticated and larger, it becomes infeasible for a user to try out every reasonable algorithm configuration in a timely fashion. Therefore, there is a need for an intelligent engine that ... continued below

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Zhang, Yeliang; Li, Xiaoye S. & Marques, Osni September 9, 2005.

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Description

The computation of eigenvalues and eigenvectors is an important and often time-consuming phase in computer simulations. Recent efforts in the development of eigensolver libraries have given users good algorithms without the need for users to spend much time in programming. Yet, given the variety of numerical algorithms that are available to domain scientists, choosing the ''best'' algorithm suited for a particular application is a daunting task. As simulations become increasingly sophisticated and larger, it becomes infeasible for a user to try out every reasonable algorithm configuration in a timely fashion. Therefore, there is a need for an intelligent engine that can guide the user through the maze of various solvers with various configurations. In this paper, we present a methodology and a software architecture aiming at determining the best solver based on the application type and the matrix properties. We combine a decision tree and an intelligent engine to select a solver and a preconditioner combination for the application submitted by the user. We also discuss how our system interface is implemented with third party numerical libraries. In the case study, we demonstrate the feasibility and usefulness of our system with a simplified linear solving system. Our experiments show that our proposed intelligent engine is quite adept in choosing a suitable algorithm for different applications.

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  • LACSI Symposium 2005, Santa Fe, NM, October11-13, 2005

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  • Report No.: LBNL--58949
  • Grant Number: DE-AC02-05CH11231
  • Office of Scientific & Technical Information Report Number: 885240
  • Archival Resource Key: ark:/67531/metadc874176

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Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • September 9, 2005

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  • Sept. 21, 2016, 2:29 a.m.

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  • Sept. 29, 2016, 7:15 p.m.

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Zhang, Yeliang; Li, Xiaoye S. & Marques, Osni. Towards an Automatic and Application-Based EigensolverSelection, article, September 9, 2005; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc874176/: accessed April 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.