Add to ORKG. Distributed and parallel simulation has been a popular research topic in recent years. The research has primarily concentrated on correctness and speedup of distributed simulation. The statistical output analysis that is an essential part of simulating stochastic systems has attained only small attention. Parallel simulation is often mentioned as an attractive alternative for steady-state simulations. However, empirical results are not widely reported. We describe an implementation of an method that combines independent simultaneous replications and the spectral method. We also present experimental results are based on 12 simulation models executed in a network of Sun SPARCstations. CR Categories and Subject Descriptors: I.6.6 [Simulation...
This paper investigates two parallel simulation methodologies, multiple replication and parallel reg...
Percentiles are convenient indices to characterize the entire range of the values of simulation outp...
Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian app...
A simple and effective way to exploit parallel processors in discrete event simulations is to run mu...
Abstract--This paper addresses statistical issues that arise in stochastic simulations of the steady...
The credibility of the final results from stochastic simulation has had limited discussion in the si...
none4noParallel and distributed simulations enable the analysis of complex systems by concurrently e...
Research in parallel simulation has been around for more than two decades. However, the number of pa...
With traditional event list techniques, evaluating a detailed discrete event simulation model can of...
Simulation results are often limited to mean values, even though this provides very limited informat...
Stochastic simulation of reaction kinetics has emerged as animportant computational tool in molecula...
Simulation results are often limited to mean values, even though this provides very limited infor- m...
Simulation output data analysis in performance evaluation studies of complex stochastic systems such...
TR-COSC 03/96Quantitative stochastic simulation is a useful tool for studying performance of stocha...
This study shows how the performance of a parallel simulation may be affected by the structure of th...
This paper investigates two parallel simulation methodologies, multiple replication and parallel reg...
Percentiles are convenient indices to characterize the entire range of the values of simulation outp...
Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian app...
A simple and effective way to exploit parallel processors in discrete event simulations is to run mu...
Abstract--This paper addresses statistical issues that arise in stochastic simulations of the steady...
The credibility of the final results from stochastic simulation has had limited discussion in the si...
none4noParallel and distributed simulations enable the analysis of complex systems by concurrently e...
Research in parallel simulation has been around for more than two decades. However, the number of pa...
With traditional event list techniques, evaluating a detailed discrete event simulation model can of...
Simulation results are often limited to mean values, even though this provides very limited informat...
Stochastic simulation of reaction kinetics has emerged as animportant computational tool in molecula...
Simulation results are often limited to mean values, even though this provides very limited infor- m...
Simulation output data analysis in performance evaluation studies of complex stochastic systems such...
TR-COSC 03/96Quantitative stochastic simulation is a useful tool for studying performance of stocha...
This study shows how the performance of a parallel simulation may be affected by the structure of th...
This paper investigates two parallel simulation methodologies, multiple replication and parallel reg...
Percentiles are convenient indices to characterize the entire range of the values of simulation outp...
Sequential Simulation is a well known method in geostatistical modelling. Following the Bayesian app...