ROSS: A high-performance, low-memory, modular Time Warp system

• Published in: Journal of parallel and distributed computing Vol. 62; no. 11; pp. 1648 - 1669
• Main Authors: Carothers, Christopher D., Bauer, David, Pearce, Shawn
• Format: Journal Article
• Language: English
• Published: San Diego, CA Elsevier Inc 01-11-2002; Elsevier
• Subjects: Applied sciences; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Discrete-event simulation; Exact sciences and technology; Parallel simulation; Reverse computation; Simulation; Software; Time warp; Time warp; Reverse computation; Parallel simulation; Discrete-event simulation; High performance; Parallel algorithm; Warping; Time warp simulation; Modular system; Wireless telecommunication; Time warps Reverse computation; Distributed memory multiprocessor system; Telecommunication network; System simulation; Fast algorithm; Large scale system; Discrete event system
• DOI: 10.1016/S0743-7315(02)00004-7
• EISSN: 1096-0848
• ISSN: 0743-7315

In this paper, we introduce a new Time Warp system called
ROSS:
Rensselaer’
s optimistic simulation system. ROSS is an extremely modular kernel that is capable of achieving event rates as high as 1,250,000 events per second when simulating a wireless telephone network model (PCS) on a quad processor PC server. In a head-to-head comparison, we observe that ROSS out performs the Georgia Tech Time Warp (GTW) system by up to 180% on a quad processor PC server and up to 200% on the SGI Origin 2000. ROSS only requires a small
constant amount of memory buffers greater than the amount needed by the sequential simulation for a constant number of processors. ROSS demonstrates for the first time that stable, highly efficient execution using little memory above what the sequential model would require is possible for low-event granularity simulation models. The driving force behind these high-performance and low-memory utilization results is the coupling of an efficient pointer-based implementation framework, Fujimoto's fast GVT algorithm for shared memory multiprocessors,
reverse computation and the introduction of
kernel processes (
KPs). KPs lower fossil collection overheads by aggregating processed event lists. This aspect allows fossil collection to be done with greater frequency, thus lowering the overall memory necessary to sustain stable, efficient parallel execution. These characteristics make ROSS an ideal system for use in large-scale networking simulation models. The principle conclusion drawn from this study is that the performance of an optimistic simulator is largely determined by its memory usage.