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Title: Poor man`s parallelism in environmental management

Abstract

Poor man`s parallelism is a term to describe the harnessing of commonly available computational approaches containing a high degree of implicit or explicit parallelism with distributed computer resources to produce a large gain in processing time. The distinguishing features of poor man`s techniques are their accessibility and relatively low cost. In some circumstances, the clever exploitation of existing hardware and software may achieve as much improvement in the timely completion of tasks as do high-end, state-of-the-art parallel technologies. The ANN-GA approach to the optimization of environmental remediation strategies is an example of poor man`s parallelism: it integrates two well-known computational technologies, artificial neural networks (ANNs) and the genetic algorithm (GA), with a simple scheme for exploiting a network of Unix workstations to solve a nonlinear combinatorial optimization problem. Although this work has been motivated by the need to tame a computational tiger rather than to experiment with different flavors of parallelism, the approach has reached a level of maturity where it is instructive to examine how parallelism is embodied in its various components. It also stands as a demonstration of how even resource-lean organizations can take advantage of parallelism to solve problems.

Authors:
;
Publication Date:
Research Org.:
Lawrence Livermore National Lab., CA (United States)
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
123223
Report Number(s):
UCRL-JC-119732; CONF-9506275-1
ON: DE96001937; TRN: 95:008023
DOE Contract Number:  
W-7405-ENG-48
Resource Type:
Conference
Resource Relation:
Conference: 2. congress on computing in civil engineering, Atlanta, GA (United States), 5-7 Jun 1995; Other Information: PBD: Feb 1995
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING AND POLICY; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; REMEDIAL ACTION; DECISION MAKING; MATHEMATICAL MODELS; ALGORITHMS; USES; NEURAL NETWORKS

Citation Formats

Johnson, V.M., and Rogers, L.L. Poor man`s parallelism in environmental management. United States: N. p., 1995. Web.
Johnson, V.M., & Rogers, L.L. Poor man`s parallelism in environmental management. United States.
Johnson, V.M., and Rogers, L.L. Wed . "Poor man`s parallelism in environmental management". United States. https://www.osti.gov/servlets/purl/123223.
@article{osti_123223,
title = {Poor man`s parallelism in environmental management},
author = {Johnson, V.M. and Rogers, L.L.},
abstractNote = {Poor man`s parallelism is a term to describe the harnessing of commonly available computational approaches containing a high degree of implicit or explicit parallelism with distributed computer resources to produce a large gain in processing time. The distinguishing features of poor man`s techniques are their accessibility and relatively low cost. In some circumstances, the clever exploitation of existing hardware and software may achieve as much improvement in the timely completion of tasks as do high-end, state-of-the-art parallel technologies. The ANN-GA approach to the optimization of environmental remediation strategies is an example of poor man`s parallelism: it integrates two well-known computational technologies, artificial neural networks (ANNs) and the genetic algorithm (GA), with a simple scheme for exploiting a network of Unix workstations to solve a nonlinear combinatorial optimization problem. Although this work has been motivated by the need to tame a computational tiger rather than to experiment with different flavors of parallelism, the approach has reached a level of maturity where it is instructive to examine how parallelism is embodied in its various components. It also stands as a demonstration of how even resource-lean organizations can take advantage of parallelism to solve problems.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1995},
month = {2}
}

Conference:
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