Towards adaptive caching for parallel and discrete event simulation

We investigate factors affecting the performance of caching to speed up discrete event simulation. Walsh and Sirer have shown that a variant of function caching (staged simulation) can improve the performance of simulation in a networking application. However, the effectiveness of caching depends significantly on cache size, the cost of consulting the cache, the hit rate, and the cost of completing the computation in case of a cache miss. We hypothesize that adaptive techniques can be used to optimize caching parameters and demonstrate an adaptive scheme that decides whether to utilize caching depending on observed cache performance and event processing times. We focus on evaluating quantitative relationships, using our own caching implementation with the P-Hold synthetic workload application running on the GTW simulation kernel. Experiments show that as the cache size is increased, performance improves to a point, then degrades, and also that the adaptive technique can substantially improve speedup.