PDAC: A data parallel algorithm for the performance analysis of closed queueing networks A parallel distribution analysis by chain algorithm (PDAC) is presented for the performance analysis of closed, multiple class queueing networks. The PDAC algorithm uses data parallel computation of the summation indices needed to compute the joint queue length probabilities. The computational cost of the PDAC algorithm is shown to be of polynomial order with a lower degree than the cost of the serial implementation of the DAC algorithm. Examples are presented comparing the PDAC algorithm with the DAC algorithm of illustrate its advantages and limitations.
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References in zbMATH (referenced in 5 articles , 1 standard article )
Showing results 1 to 5 of 5.
- de’ Michieli Vitturi, Mattia; Esposti Ongaro, Tomaso; Neri, Augusto; Salvetti, Maria Vittoria; Beux, François: An immersed boundary method for compressible multiphase flows: application to the dynamics of pyroclastic density currents (2007)
- Plotkin, Tanya: Fuzzy sets and algorithms of distributed task allocation for cooperative agents (2001)
- Kraus, Sarit; Plotkin, Tatjana: Algorithms of distributed task allocation for cooperative agents (2000)
- Hanson, F.B.; Mei, Jing-Dong; Tier, Charles; Xu, Huihuang: PDAC: A data parallel algorithm for the performance analysis of closed queueing networks (1993)
- Mathur, Kapil K.; Johnsson, S.Lennart: The finite element method on a data parallel computing system (1989)