Parallel computing for probabilistic fatigue analysis

Conference · Fri Jan 01 00:00:00 EST 1993

OSTI ID:6300095

Sues, R H; Lua, Y J; Smith, M D

This 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. 10 refs.

• OSTI ID: 6300095
• Report Number(s): AIAA-Paper-93-1499; CONF-9304186-; CNN: NAS3-26576
• Resource Relation: Conference: 34. American Institute of Aeronautics and Astronautics/American Society of Mechanical Engineers (AIAA/ASME) adaptive structures conference, La Jolla, CA (United States), 19-22 Apr 1993; Other Information: 1659-1669
• Country of Publication: United States
• Language: English

Related Subjects

36 MATERIALS SCIENCE
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
ALGORITHMS
EFFICIENCY
FATIGUE
FORECASTING
STRESS ANALYSIS
COMPOSITE MATERIALS
COMPUTER ARCHITECTURE
COMPUTERIZED SIMULATION
PARALLEL PROCESSING
MATERIALS
MATHEMATICAL LOGIC
MECHANICAL PROPERTIES
PROGRAMMING
SIMULATION
360603* - Materials- Properties
990200 - Mathematics & Computers