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Parallel computing for probabilistic fatigue analysisThis paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.
Document ID
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Sues, Robert H.
(NASA Lewis Research Center Cleveland, OH, United States)
Lua, Yuan J.
(NASA Lewis Research Center Cleveland, OH, United States)
Smith, Mark D.
(Applied Research Associates, Inc. Raleigh, NC, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1993
Publication Information
Publication: In: AIAA(ASME)ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 34th and AIAA/ASME Adaptive Structures Forum, La Jolla, CA, Apr. 19-22, 1993, Technical Papers. Pt. 3 (A93-33876 1
Publisher: American Institute of Aeronautics and Astronautics
Subject Category
Computer Systems
Report/Patent Number
AIAA PAPER 93-1499
Accession Number
Funding Number(s)
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