Paralation Views: Abstractions for Efficient Scientific Computing on the Connection Machine

Abstract

An ideal parallel programming language for scientific applications should provide flexible abstraction mechanisms for writing organized and readable programs, encourage a modular programming style that permits using libraries of tested routines, and, above all, permit the programming to write efficient programs for the target machine. We use these criteria to evaluate the languages Lisp, Connection Machine Lisp, and Paralation Lisp for writing scientific programs on the Connection Machine. As a vehicle for this exploration, we fix a particular non-trivial algorithm (LU decomposition with partial pivoting) and study code for implementing it in the three languages. Keywords: Programming languages; Parallel programming languages; SIMD architectures; Connection machine; Scientific programming; Data abstraction. (JES)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1989
Accession Number
ADA213935

Entities

People

  • Kenneth J. Goldman

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Classification
  • Collisions
  • Computations
  • Computer Programming
  • Computer Science
  • Computers
  • Coordinate Systems
  • Data Sets
  • High Level Languages
  • Information Processing
  • Language
  • Lisp Programming Language
  • Military Research
  • Programming Languages
  • Security

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Linguistics
  • Parallel and Distributed Computing.