High Productivity Computing Systems (HPCS) Library Study Effort

Abstract

The research team explores a rich feature set, large algorithmic variety, and detailed implementation considerations for one of the most fundamental computational kernels of computational science: LU factorization of a dense matrix by Gaussian elimination with partial pivoting. For the target implementation platforms and systems, they analyze and compare established shared and distributed memory environments as well as relatively new Partitioned Global Address Space programming languages, which include those coming from the High Productivity Computing Systems (HPCS) project. To give quantitative measures of each hardware platform metrics, combined with implementation characteristics, they compare scalability, raw and relative performance as well as the source code features, functionality, and absolute size breakdown as measured by Source Lines of Code (SLOC).

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2008
Accession Number
ADA481262

Entities

People

  • Jack Dongarra
  • James Demmel
  • Parry Husbands
  • Piotr Luszczek

Organizations

  • University of Tennessee system

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • C Programming Language
  • Computer Programming
  • Computers
  • Computing System Architectures
  • Environment
  • High Level Languages
  • High Performance Computing
  • Instruction Set Architecture
  • Language
  • Linear Algebra
  • Multithreading
  • Programming Languages
  • Software Development
  • Software Development Tools
  • Software Metrics
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Life Cycle Cost Analysis
  • Linear Algebra
  • Software Engineering.

Technology Areas

  • Space