Optimizing Adaptive Synchronization in Parallel Simulators for Large-scale Parallel Systems and Applications

This paper addresses the optimization of parallel simulators for large-scale parallel systems and applications. Such simulators are often based on parallel discrete event simulation with conservative or optimistic protocols to synchronize the simulating processes. The paper considers how available future information about events and application behaviors can be efficiently extracted and further exploited to improve the performance of adaptive optimistic protocols. First, we extract information about future events and their dependencies in application traces to guide adaptive adjustments of time window in trace-driven parallel simulation. Second, we use information about application behaviors, specifically the iterative behavior found in many applications, to avoid the unnecessary adjustments of time window. These techniques are implemented in the BigSim simulator and tested by real-world and standard benchmark applications including Jacobi3D and HPL. The results show that our optimization approaches can reduce the execution times of simulation ranging from 11% up to 32%. Moreover, our methods are easy to implement and don't need to augment compilers or even modify the core codes of parallel simulators.