Authors: Jean Frédéric Myoupo; Vianney Kengne Tchendji
Addresses: Laboratoire MIS, Université de Picardie Jules Verne, 33 rue Saint Leu, 80039 Amiens, France ' Laboratoire MIS, Université de Picardie Jules Verne, 33 rue Saint Leu, 80039 Amiens, France; Department of Computer Science, University of Yaounde 1, P.O. Box 876 C.C.U., Yaounde, Cameroon
Abstract: This paper presents an efficient coarse grain multicomputer (CGM) parallel algorithm for the cost of the optimal binary search tree problem (OBST problem). In the previous best CGM algorithm for this problem, the size of the local memory of each processor is not bounded. And even, in the worst case, its running time reduces to the one of Knuth's sequential algorithm for the same problem, bringing no gain by parallelising OBST. Our CGM algorithm uses Knuth's sequential algorithm for local computations to perform in time as well as the best previous CGM algorithm. Moreover, each processor can process at most two blocks and thus avoid the severe drawback raised above of the previous work.
Keywords: parallel processing; coarse grain multicomputers; CGM; dynamic programming; optimal binary search tree; OBST.
International Journal of High Performance Computing and Networking, 2014 Vol.7 No.4, pp.269 - 280
Available online: 11 Jun 2014Full-text access for editors Access for subscribers Purchase this article Comment on this article