Material identification algorithms for parallel systems

Michael Kahn, Sotirios G. Ziavras

Research output: Contribution to journalArticlepeer-review

Abstract

The direct binary hypercube interconnection network has been widely used in the design of parallel computer systems, because it has low diameter, and can effectively emulate commonly used structures such as binary trees, rings, and meshes. However, the hypercube has the disadvantage of high VLSI complexity due to the increase in the number of communication ports and channels per PE (processing element) with an increase in the dimension of the hypercube. This complexity is a major drawback of the hypercube because it limits its potential for scalability. Ziavras has introduced the reduced hypercube (RH) interconnection network. The RH reduces VLSI complexity without compromising performance. The RH is obtained from a regular hypercube by a uniform reduction in the number of edges for each hypercube node. The main objective of this paper is to demonstrate the feasibility of the RH in implementing material identification algorithms using X-ray fluorescence. Relevant algorithms are developed for the PRAM and the hypercube also, for comparative analysis. The algorithms rely heavily on the binary tree emulation capabilities of these systems. The results indicate that the RH is capable of providing hypercube-like performance at a significantly reduced complexity/cost.

Original languageEnglish (US)
Pages (from-to)325-341
Number of pages17
JournalComputers and Electrical Engineering
Volume22
Issue number5
DOIs
StatePublished - Sep 1996

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)
  • Electrical and Electronic Engineering

Keywords

  • Computer architecture
  • Hypercube
  • Interconnection networks
  • Material identification
  • Parallel processing
  • Performance analysis
  • Reduced hypercube
  • Scalability
  • VLSI complexity

Fingerprint Dive into the research topics of 'Material identification algorithms for parallel systems'. Together they form a unique fingerprint.

Cite this