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Matrix algebra routines for the Acorn Archimedes microcomputer: example applications.

A Fielding1

  • 1Department of Biological Sciences, Manchester Polytechnic, UK.

Computer Applications in the Biosciences : CABIOS
|August 1, 1988
PubMed
Summary

New matrix algebra routines for the Acorn Archimedes microcomputer run quickly in interpreted BASIC. This enables complex computations like reciprocal averaging and principal components analysis directly within BASIC programs.

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Area of Science:

  • Computer Science
  • Scientific Computing
  • Numerical Analysis

Background:

  • Matrix algebra is computationally intensive.
  • Interpreted programming languages like BASIC traditionally have limitations in performance for complex calculations.
  • The Acorn Archimedes microcomputer offers potential for enhanced processing capabilities.

Purpose of the Study:

  • To develop and evaluate a set of matrix algebra routines for the Acorn Archimedes.
  • To assess the performance of these routines when implemented as BASICV procedures.
  • To demonstrate the feasibility of performing advanced matrix computations within an interpreted BASIC environment.

Main Methods:

  • Implementation of matrix algebra routines as BASICV procedures.
  • Performance benchmarking of the implemented procedures on the Acorn Archimedes.

Related Experiment Videos

  • Application of the routines to demonstrate reciprocal averaging and principal components analysis.

    • Main Results:

    • The developed BASICV matrix algebra procedures exhibit high execution speeds.
    • Programs requiring matrix computations can be efficiently written and run in interpreted BASIC.
    • Successful demonstration of complex applications like reciprocal averaging and principal components analysis.

    Conclusions:

    • The matrix algebra routines provide a viable and performant solution for scientific computing on the Acorn Archimedes.
    • Interpreted BASIC, augmented with these procedures, becomes a practical tool for matrix-intensive tasks.
    • The findings open possibilities for wider adoption of BASIC for scientific applications requiring matrix operations.