Reference filtering for distributed simulation of shared memory multiprocessors

This paper proposes a method to reduce the amount of the memory references generated by the front-end of our distributed execution-driven simulator for shared memory multiprocessors named Shaman. The simulator consists of a front-end to execute programs in parallel and a backend, driven by the memory references from the front-end, to simulate the behavior of the memory system of a target multiprocessor for high-performance simulation. The front-end runs on a PC cluster using software DSM technique and partially simulates the coherent cache of the target system. The key idea of the reference reduction is to use the caches in the front-end as a filter of the references. We prove that the filtering for a memory block is safe if it is accessed in data-race-free manner as the whole. We also show a method to detect racing blocks to inactivate the filtering. The preliminary experiment with SPLASH-2 kernels shows up to 99.6% of references are filtered out and redundant references are less than 1.4%