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GuoJie Li, B.W. Wah, "Computational Efficiency of Parallel Combinatorial ORTree Searches," IEEE Transactions on Software Engineering, vol. 16, no. 1, pp. 1331, January, 1990.  
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@article{ 10.1109/32.44360, author = {GuoJie Li and B.W. Wah}, title = {Computational Efficiency of Parallel Combinatorial ORTree Searches}, journal ={IEEE Transactions on Software Engineering}, volume = {16}, number = {1}, issn = {00985589}, year = {1990}, pages = {1331}, doi = {http://doi.ieeecomputersociety.org/10.1109/32.44360}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Software Engineering TI  Computational Efficiency of Parallel Combinatorial ORTree Searches IS  1 SN  00985589 SP13 EP31 EPD  1331 A1  GuoJie Li, A1  B.W. Wah, PY  1990 KW  near linear speedup; parallel combinatorial ORtree searches; performance; error allowance function; dominance relation; search strategies; simulation; sufficient conditions; combinatorial mathematics; database management systems; decision theory; parallel processing; performance evaluation; theorem proving; trees (mathematics). VL  16 JA  IEEE Transactions on Software Engineering ER   
The performance of parallel combinatorial ORtree searches is analytically evaluated. This performance depends on the complexity of the problem to be solved, the error allowance function, the dominance relation, and the search strategies. The exact performance may be difficult to predict due to the nondeterminism and anomalies of parallelism. The authors derive the performance bounds of parallel ORtree searches with respect to the bestfirst, depthfirst, and breadthfirst strategies, and verify these bounds by simulation. They show that a nearlinear speedup can be achieved with respect to a large number of processors for parallel ORtree searches. Using the bounds developed, the authors derive sufficient conditions for assuring that parallelism will not degrade performance and necessary conditions for allowing parallelism to have a speedup greater than the ratio of the numbers of processors. These bounds and conditions provide the theoretical foundation for determining the number of processors required to assure a nearlinear speedup.
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