Asynchronous parallel pattern search for nonlinear optimization

Technical Report · Sat Jan 01 00:00:00 EST 2000

DOI:https://doi.org/10.2172/751003· OSTI ID:751003

Hough, P D; Kolda, T G; Torczon, V J

Parallel pattern search (PPS) can be quite useful for engineering optimization problems characterized by a small number of variables (say 10--50) and by expensive objective function evaluations such as complex simulations that take from minutes to hours to run. However, PPS, which was originally designed for execution on homogeneous and tightly-coupled parallel machine, is not well suited to the more heterogeneous, loosely-coupled, and even fault-prone parallel systems available today. Specifically, PPS is hindered by synchronization penalties and cannot recover in the event of a failure. The authors introduce a new asynchronous and fault tolerant parallel pattern search (AAPS) method and demonstrate its effectiveness on both simple test problems as well as some engineering optimization problems

• Research Organization: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
• Sponsoring Organization: US Department of Energy (US)
• DOE Contract Number: AC04-94AL85000
• OSTI ID: 751003
• Report Number(s): SAND2000-8213; TRN: AH200020%%81
• Resource Relation: Other Information: PBD: 1 Jan 2000
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
42 ENGINEERING
PARALLEL PROCESSING
FAULT TOLERANT COMPUTERS
COMPUTER ARCHITECTURE
ENGINEERING
OPTIMIZATION
DISTRIBUTED DATA PROCESSING
ASYNCHRONOUS PARALLEL OPTIMIZATION
PATTERN SEARCH
DIRECT SEARCH
FAULT TOLERANCE
DISTRIBUTED COMPUTING
CLUSTER COMPUTING