Design and analysis of parallel Monte Carlo algorithms
SIAM Journal on Scientific and Statistical Computing - Papers from the Second Conference on Parallel Processing for Scientific Computin
Discrete event simulations and parallel processing: statistical properties
SIAM Journal on Scientific and Statistical Computing
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
Analysis if initial transient deletion for parallel steady-state simulations
SIAM Journal on Scientific and Statistical Computing
Experiments in concurrent stochastic simulation: the EcliPSe paradigm
Journal of Parallel and Distributed Computing
Eliminating the boundary effect of a large-scale personal communication service network simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A node simulation tool for bandwidth allocation and CAC in ATM networks
ISCC '97 Proceedings of the 2nd IEEE Symposium on Computers and Communications (ISCC '97)
Aurora: An Approach to High Throughput Parallel Simulation
Proceedings of the 20th Workshop on Principles of Advanced and Distributed Simulation
On Parallel Stochastic Simulation of Diffusive Systems
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
A scalable framework for parallel discrete event simulations on desktop grids
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Experiences on parallel replicated discrete-event simulation on a GRID
GCC'05 Proceedings of the 4th international conference on Grid and Cooperative Computing
Goal-Directed Grid-Enabled Computing for Legacy Simulations
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
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Parallel independent replicated simulation (PIRS) is an effective approach to speed up the simulation processes. In a PIRS, a single simulation run is executed by multiple computers in parallel. The statistical properties for a PIRS may be affected by the scheduling policies. For an unbiased PIRS scheduling policy, a reliable distributed computing environment is required. We consider an unbiased PIRS scheduling policy on a distributed platform such as a network of workstations. We observe that including more computing resources may degrade the performance of PIRS. Simple rules are proposed to select processors for PIRS.