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Parallel Computation of the Jacobian Matrix for Nonlinear Equation Solvers Using MATLABDemonstrating speedup for parallel code on a multicore shared memory PC can be challenging in MATLAB due to underlying parallel operations that are often opaque to the user. This can limit potential for improvement of serial code even for the so-called embarrassingly parallel applications. One such application is the computation of the Jacobian matrix inherent to most nonlinear equation solvers. Computation of this matrix represents the primary bottleneck in nonlinear solver speed such that commercial finite element (FE) and multi-body-dynamic (MBD) codes attempt to minimize computations. A timing study using MATLAB's Parallel Computing Toolbox was performed for numerical computation of the Jacobian. Several approaches for implementing parallel code were investigated while only the single program multiple data (spmd) method using composite objects provided positive results. Parallel code speedup is demonstrated but the goal of linear speedup through the addition of processors was not achieved due to PC architecture.
Document ID
20170007240
Acquisition Source
Langley Research Center
Document Type
Technical Memorandum (TM)
Authors
Rose, Geoffrey K.
(NASA Langley Research Center Hampton, VA, United States)
Nguyen, Duc T.
(Old Dominion Univ. Norfolk, VA, United States)
Newman, Brett A.
(Old Dominion Univ. Norfolk, VA, United States)
Date Acquired
August 2, 2017
Publication Date
January 7, 2017
Subject Category
Computer Programming And Software
Numerical Analysis
Report/Patent Number
NASA/TM-2017-219655
NF1676L-27699
L-20845
Funding Number(s)
WBS: WBS 845953.01.03.04
Distribution Limits
Public
Copyright
Public Use Permitted.
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