The Acceleration of Structural Microarchitectural Simulation via Scheduling
نویسنده
چکیده
Microarchitects rely upon simulation to evaluate design alternatives, yet constructing an accurate simulator by hand is a difficult and time-consuming process because simulators are usually written in sequential languages while the system being modeled is concurrent. Structural modeling can mitigate this difficulty by allowing the microarchitect to specify the simulation model in a concurrent, structural form; a simulator compiler then generates a simulator from the model. However, the resulting simulators are generally slower than those produced by hand. The thesis of this dissertation is that simulation speed improvements can be obtained by careful scheduling of the work to be performed by the simulator onto single or multiple processors. For scheduling onto single processors, this dissertation presents an evaluation of previously proposed scheduling mechanisms in the context of a structural microarchitectural simulation framework which uses a particular model of computation, the Heterogeneous Synchronous Reactive (HSR) model, and improvements to these mechanisms which make them more effective or more feasible for microarchitectural models. A static scheduling technique known as partitioned scheduling is shown to offer the most performance improvement: up to 2.08 speedup. This work furthermore proves that the the Discrete Event model of computation can be statically scheduled using partitioned scheduling when restricted in ways that are commonly assumed in microarchitectural simulation. For scheduling onto multiple processors, this dissertation presents the first automatic parallelization of simulators using the HSR model of computation. It shows that effective parallelization requires techniques to avoid waiting due to locks and to improve cache locality. Two novel heuristics for lock mitigation and two for cache locality improvement are introduced and evaluated on three different parallel systems. The combination of lock mitigation and locality improvement is shown to allow superlinear speedup for some models: up to 7.56 for four processors.
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