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Title: Human-Parallel Computing.


Abstract not provided.

Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the DSO Proposers Day held June 22-23, 2016 in Arlington, VA.
Country of Publication:
United States

Citation Formats

Boslough, Mark B. Human-Parallel Computing.. United States: N. p., 2016. Web.
Boslough, Mark B. Human-Parallel Computing.. United States.
Boslough, Mark B. Mon . "Human-Parallel Computing.". United States. doi:.
title = {Human-Parallel Computing.},
author = {Boslough, Mark B.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Aug 01 00:00:00 EDT 2016},
month = {Mon Aug 01 00:00:00 EDT 2016}

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  • The authors describe an efficient method for computing a set of n linear simultaneous equations in o(n) time, on the proposed array processor system. The proposed system is composed of a large number of microprocessors and its layout is p*q square. The microprocessors (hereafter called processing elements, or PEs) are connected to the row and columnwise broadcast memories. 2 references.
  • The authors investigate the behaviour of a parallel computing system, consisting of a number of independent processors, which execute in parallel the numerical solution of a partial differential equation. As a measure of system they consider the speed gain obtained per iteration step on the parallel processors with respect to the one-processor execution of the equivalent task. For the performance evaluation of the parallel system they use a probabilistic model of the computation scheme, based upon several main assumptions concerning computation and communication times. They provide the exact solution of the model in the case of two processors and thenmore » develop a heuristic method allowing the approximate solution of the model in the case of three or more parallel processors. 8 references.« less
  • The present conference discusses topics in the fields of matrix computations, numerical methods, differential equations, parallel processing applications in science, computer languages and software systems for parallel processing, and parallel computer architectures. Attention is given to Gaussian techniques on shared memory multiprocessors, a novel parallel algorithm for linear triangular systems, parallel rapid elliptic solvers, parallel multivariate numerical integration, and the implementation of the acceptance-rejection method on parallel processors. Also discussed are a parallel multilevel FEM with hierarchical basis functions, the parallel processing of a domain decomposition method, the parallelization of adaptive grid domain mappings, the automated decomposition of FEM meshesmore » for hypercube computers, parallel vision algorithms, the programming of parallel architectures, iteration space tiling for memory hierarchies, the Cerberus multiprocessor simulator, and a parallel architecture for optical computing.« less
  • This book contains papers presented at a conference on parallel processing for scientific computing. Topics included are the following: WY representation of products of household matrices; a domain decomposed fast Poisson solver on a rectangle; multiprocessor fast fourier transform methods; asynchronous relaxations for the numerical solution of differential equations by parallel processors; solving equations of motion on a vertical tree machine; design and analysis of parallel Monte Carlo algorithms; adapting a navier-stokes code to the ICL-Dap; and hypercube algorithms and implementations.