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David M. Nicol, Jason Liu, "Composite Synchronization in Parallel DiscreteEvent Simulation," IEEE Transactions on Parallel and Distributed Systems, vol. 13, no. 5, pp. 433446, May, 2002.  
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@article{ 10.1109/TPDS.2002.1003854, author = {David M. Nicol and Jason Liu}, title = {Composite Synchronization in Parallel DiscreteEvent Simulation}, journal ={IEEE Transactions on Parallel and Distributed Systems}, volume = {13}, number = {5}, issn = {10459219}, year = {2002}, pages = {433446}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPDS.2002.1003854}, 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  Composite Synchronization in Parallel DiscreteEvent Simulation IS  5 SN  10459219 SP433 EP446 EPD  433446 A1  David M. Nicol, A1  Jason Liu, PY  2002 KW  Synchronization KW  simulation KW  parallel processing KW  performance KW  optimization. VL  13 JA  IEEE Transactions on Parallel and Distributed Systems ER   
This paper considers a technique for composing global (barrierstyle) and local (channel scanning) synchronization protocols within a single parallel discreteevent simulation. Composition is attractive because it allows one to tailor the synchronization mechanism to the model being simulated. We first motivate the problem by showing the large performance gap that can be introduced by a mismatch of model and synchronization method. Our solution calls for each channel between submodels to be classified as synchronous or asynchronous. We mathematically formulate the problem of optimally classifying channels and show that, in principle, the optimal classification can be obtained in time proportional to max C {x log C, V x N}, where C is the number of channels, V the number of unique minimal delays on those channels, and N is the number of submodels. We then demonstrate an implementation which finds an optimal solution at runtime and consider its performance on network topologies, including one of the global internet at the autonomous system level. We find that the automated method effectively determines channel assignments that maximize performance.
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