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Controlling over-optimism in time-warp via CPU-based flow control

In standard optimistic parallel event simulation, no restriction exists on the maximum lag in simulation time between the fastest and slowest logical processes (LPs). Over-optimistic applications exhibit a large lag, which encourages rollback and may degrade performance. We investigate an approach for controlling over-optimism that classifies LPs as fast, medium, or slow and migrates fast and/or slow processes. Fast LPs are aggregated, forcing them to compete for CPU cycles. Slow LPs are dispersed, to limit their competition for CPU cycles. The approach was implemented on distributed Georgia Tech Time Warp (GTW) (Das et al. 1994) and experiments performed using the synthetic application P-Hold (Fujimoto 1990). For over-optimistic test cases, our approach was found to perform 1.25 to 2.75 times better than the standard approach in terms of useful work and to exhibit execution times shorter than or equal to the standard computation.