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Degree of Scalability: Scalable Reconfigurable Mesh Algorithms for Multiple Addition and Matrix–vector Multiplication by Ramachandran Vaidyanathan; Jerry L Trahan; Chun-ming Lu is a Computer Science article available to read on EtoBox.

What is Degree of Scalability: Scalable Reconfigurable Mesh Algorithms for Multiple Addition and Matrix–vector Multiplication about?

The usual concern when scaling an algorithm on a parallel model of computation is preserving efficiency while increasing or decreasing the number of processors. Many algorithms for reconfigurable models, however, attain constant time at the expense of an inefficient algorithm. For these algorithms, scaling down the number of processors while preserving inefficiency is no benefit once constant time execution is lost. In fact, one can often accelerate the efficiency of these algorithms while reducing the number of processors. To quantify this improvement in efficiency, this paper introduces the measure of degree of scalability to complement the insight obtained from efficiency for such algorithms. Demonstrating the utility of this measure, we present new reconfigurable mesh (R-Mesh) algorithms for multiple addition and matrix-vector multiplication, improving both the number of processors and the degree of scalability compared to previous algorithms. We also extend these results to floating point number operands, which have previously received little attention on the R-Mesh.

Who reads Degree of Scalability: Scalable Reconfigurable Mesh Algorithms for Multiple Addition and Matrix–vector Multiplication?

Author

Ramachandran Vaidyanathan; Jerry L Trahan; Chun-ming Lu

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0167-8191)

Published

2003

Language

EN

Field

Computer Science (Physical Sciences)