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Heejo Lee, Jong Kim, Sung Je Hong, Sunggu Lee, "Processor Allocation and Task Scheduling of Matrix Chain Products on Parallel Systems," IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 4, pp. 394407, April, 2003.  
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@article{ 10.1109/TPDS.2003.1195411, author = {Heejo Lee and Jong Kim and Sung Je Hong and Sunggu Lee}, title = {Processor Allocation and Task Scheduling of Matrix Chain Products on Parallel Systems}, journal ={IEEE Transactions on Parallel and Distributed Systems}, volume = {14}, number = {4}, issn = {10459219}, year = {2003}, pages = {394407}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2003.1195411}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Parallel and Distributed Systems TI  Processor Allocation and Task Scheduling of Matrix Chain Products on Parallel Systems IS  4 SN  10459219 SP394 EP407 EPD  394407 A1  Heejo Lee, A1  Jong Kim, A1  Sung Je Hong, A1  Sunggu Lee, PY  2003 KW  Matrix chain product KW  parallel matrix multiplication KW  matrix chain scheduling problem KW  processor allocation KW  task scheduling. VL  14 JA  IEEE Transactions on Parallel and Distributed Systems ER   
Abstract—The problem of finding an optimal product sequence for sequential multiplication of a chain of matrices (the matrix chain ordering problem, MCOP) is wellknown and has been studied for a long time. In this paper, we consider the problem of finding an optimal product schedule for evaluating a chain of matrix products on a parallel computer (the matrix chain scheduling problem, MCSP). The difference between the MCSP and the MCOP is that the MCOP pertains to a product sequence for single processor systems and the MCSP pertains to a sequence of concurrent matrix products for parallel systems. The approach of parallelizing each matrix product after finding an optimal product sequence for single processor systems does not always guarantee the minimum evaluation time on parallel systems since each parallelized matrix product may use processors inefficiently. We introduce a new processor scheduling algorithm for the MCSP which reduces the evaluation time of a chain of matrix products on a parallel computer, even at the expense of a slight increase in the total number of operations. Given a chain of
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