Journal ArticleDOI
Experience with pipelined multiple instruction streams
H.F. Jordan
- Vol. 72, Iss: 1, pp 113-123
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TLDR
The architecture and programming environment of the HEP is introduced and a range of scientific applications programs for which parallel versions have been produced, tested, and analyzed on this computer are surveyed.Abstract:
Pipelining has been used to implement efficient, high-speed vector computers. It is also an effective method for implementing multiprocessors. The Heterogeneous Element Processor (HEP) built by Denelcor Incorporated is the first commercially available computer system to use pipelining to implement multiple processes. This paper introduces the architecture and programming environment of the HEP and surveys a range of scientific applications programs for which parallel versions have been produced, tested, and analyzed on this computer. In all cases, the ideal of one instruction completion every pipeline step time is closely approached. Speed limitations in the parallel programs are more often a result of the extra code necessary to ensure synchronization than of actual synchronization lockout at execution time. The pipelined multiple instruction stream architecture is shown to cover a wide range of applications with good utilization of the parallel hardware.read more
Citations
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Solution of Partial Differential Equations on Vector and Parallel Computers
James M. Ortega,Robert G. Voigt +1 more
TL;DR: The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms.
Journal ArticleDOI
Parallel Cholesky factorization on a shared-memory multiprocessor☆
TL;DR: A parallel algorithm is developed for Cholesky factorization on a shared-memory multiprocessor based on self-scheduling of a pool of tasks and the most promising variant, which the authors call column-Cholesky, is identified and implemented for the Denelcor HEP multiproprocessor.
Journal ArticleDOI
On some parallel banded system solvers
Jack Dongarra,Ahmed H. Sameh +1 more
TL;DR: Algorithms for solving narrow banded systems and the Helmholtz difference equations that are suitable for multiprocessing systems are described and highlight the large grain parallelism inherent in the problems.
Journal ArticleDOI
Computational models and task scheduling for parallel sparse Cholesky factorization
TL;DR: A new medium-grained model based on column-oriented tasks is introduced, and it is shown to correspond structurally to the filled graph of the given sparse matrix and give an overall scheme for parallel sparse Cholesky factorization, appropriate for parallel machines with shared-memory architecture like the Denelcor HEP.
Parallel Cholesky factorization on a shared-memory multiprocessor. Final report, 1 October 1986-30 September 1987
A. George,M.T. Heath,J. Liu +2 more
TL;DR: In this article, a parallel algorithm for Cholesky factorization on a shared-memory multiprocessor is presented. The algorithm is based on self-scheduling of a pool of tasks.
References
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Some Computer Organizations and Their Effectiveness
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Parallel Prefix Computation
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Journal ArticleDOI
Design of a Massively Parallel Processor
TL;DR: The massively parallel processor (MPP) as discussed by the authors was designed to process satellite imagery at high rates, achieving 8-bit integer data, addition can occur at 6553 million operations per second (MOPS) and multiplication at 1861 MOPS.
Journal ArticleDOI
The Elimination form of the Inverse and its Application to Linear Programming
TL;DR: In this article, a form of inverse which is especially convenient to obtain and use for matrices with a high percentage of zeros is discussed, and the application of this form in linear programming is also discussed.
Journal ArticleDOI
A Survey of Parallel Algorithms in Numerical Linear Algebra.
TL;DR: A comprehensive survey of parallel techniques for problems in linear algebra is given, specific topics include: relevant computer models and their consequences for programs, evaluation of arithmetic expressions, solution of general and special linear systems of equations, and computation of eigenvalues.