2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation (1996)
May 22, 1996 to May 24, 1996
Krishnan Kumaran , Lucent Technologies , Bell Labs Innovations
Boris Lubachevsky , Lucent Technologies , Bell Labs Innovations
Anwar Elwalid , Lucent Technologies , Bell Labs Innovations
We simulate models of ATM communication systems on a massively parallel SIMD computer. Fast simulations of ATM models are needed because the regimes of interest usually involve high volumes of traffic and low failure rates. Unexpected practical and theoretical difficulties, partly due to the massive parallelism and SIMD aspects, were encountered and we show how to cope with them. In a replica-parallel simulation of an ATM system, large variations in computed statistics are caused by small differences in the distribution of employed random number generators. A comparison of these distributions using a secondary statistical measure served to disambiguate the results. It was also found that time-parallel simulations of ATM systems with Markov sources can be efficiently performed using parallel prefix methods only when the sources have a small number of states, while more complex sources require end-state matching for efficient simulation. We discovered that, with the proper choice of initial state distributions and partial regeneration points, the time and memory requirements can be much improved. Our simulations were carried out on the MasPar MP-1216 system with 16,384 processors, which was compared against an SGI workstation. We achieved about 60%-70% efficiency (speed-up of approx 35 compared to the ideal of approx 51).
replica-parallel, time-parallel, parallel prefix, markov sources, order statistics, random sampling
Krishnan Kumaran, Boris Lubachevsky, Anwar Elwalid, "Massively Parallel Simulations of ATM Systems", 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation, vol. 00, no. , pp. 0039, 1996, doi:10.1109/PADS.1996.761561