We briefly review some key scientific and parallel processing issues in a selection of some 84 existing applications of parallel machines. We include the MIMD hypercube transputer array, BBN Butterfly, and the SIMD ICL DAP, Goodyear MPP and Connection Machine from Thinking Machines. We use a space-time analogy to classify problems and show how a division into synchronous, loosely synchronous and asynchronous problems is helpful. This classifies problems into those suitable for SIMD or MIMD machines and isolates the asynchronous class as that for which major uncertainties as to possible parallelism exist. Interestingly about half of the scientific applications run excellently on SIMD machines with the other half able to take especial advantage of the MIMD architecture.

What have we learnt from using real parallel machines to solve real problems

Two versions of an algorithm for finding the eigenvalues of symmetric, tridiagonal matrices are described. They are based on the use of the Sturm sequences and the bisection algorithm. The algorithms were implemented on the FPS T-Series. Some speedup factor results are presented.

A hybrid hypercube algorithm for the symmetric tridiagonal eigenvalue problem

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A hybrid hypercube algorithm for the symmetric tridiagonal eigenvalue problem