Title: Derivative Estimates Parallel Simulation Algorithm Based on Performance Potentials for a Class of CQNs
Abstract: An efficient parallel simulation algorithm is presented for the application of Markov Performance Potential theory to the sensitivity analysis of a class of closed queuing networks. According to the feature of parameter matrix computation, which occupies more than 70% CPU time, a new processor partitioning pattern on matrix entries, Screwy Partitioning, is introdnced, which can make complete load balance among all processors on this part. Inview of the large amount of communication cost to broadcast the data of simulated sample path, we use the Common Random Number (CRN) is adopted to let all processors generate the same sample path, large amount of broadcasting cost by adding a just little workload. In addition, since the two parts of matrix computation that occupy more than 90% CPU time do not need communication cost to exchange matrix's entries, this algorithm is widely applicable to various types of parallel computers. The simulation experiments on an SPMD parallel computer show that this algorithm can achieve near linear speedup.
Publication Year: 1999
Publication Date: 1999-01-01
Language: en
Type: article
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