Locality-preserving load-balancing mechanisms for synchronous simulations on shared-memory multiprocessors

Many synchronous algorithms have been proposed for parallel and discrete simulations. However the actual performance of these algorithms has been far from ideal, especially when event granularity is small. Barring the case of low parallelism in the given simulation models, one of the main reasons of low speedups is in the uneven load distribution among processors. We present several new locality-preserving load balancing mechanisms for synchronous simulations on shared-memory multiprocessors. We show both theoretically and empirically that some of these mechanisms incur very low overhead. The results confirm that one of the new mechanisms is indeed more efficient and scalable than common existing approaches.