Parallel simplex algorithms and loop spreading

Thesis/Dissertation · Fri Jan 01 04:00:00 EST 1988

OSTI ID:6473052

Wu, Y

Parallel solutions for two classes of linear programs are presented. First we parallelized the two-phase revised simplex algorithm and showed that it is possible to get linear improvement in performance. The simplex algorithm is the best known algorithm for solving linear programs, and we claim our result is the best one which can be achieved. Next we study the parallelization of the decomposed simplex algorithm. One of our new parallel algorithms has achieved 2*P time of performance improvement over the decomposed simplex algorithm using P processors. Meanwhile, we discovered a particular variation of the decomposed simplex algorithm which can run 2 times faster than the original one. The new parallel algorithm linearly speedups the fast sequential algorithm. As in any parallel program, unbalanced processor load causes performance of the parallel decomposed simplex algorithm to drop significantly when the size of the input data is not a multiple of the number of available processors. To remove this limitation, we invented a load; balance technique called Loop Spreading that evenly distributes parallel tasks on multiple processors without a drop in performance even when the size of the input data is not a multiple of the number of processors. Loop Spreading is a general technique that can be used automatically by a compiler to balance processor load in any language that supports parallel loop constructs.

• Research Organization: Oregon State Univ., Corvallis, OR (USA)
• OSTI ID: 6473052
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
990300 -- Information Handling
ALGORITHMS
ARRAY PROCESSORS
COMPUTER ARCHITECTURE
DATA PROCESSING
INFORMATION SYSTEMS
LINEAR PROGRAMMING
MATHEMATICAL LOGIC
PARALLEL PROCESSING
PROCESSING
PROGRAMMING
TASK SCHEDULING