Sequential Unification and Aggressive Lookahead Mechanisms for Data Memory Accesses

Abstract

Recent work in hybrid data address and value prediction has successfully increased the accuracy of data prefetching. However, many predictable data are still found to be missing from cache. Detail investigation showed that this is mainly due to two reasons: (i) partial cache hit for data being prefetched, and (ii) abortion of highly accurate prefetch requests by demand fetch requests. To improve this situation, we propose two mechanisms to reduce the startup latency of prefetch requests. They are the sequential unification of prefetch and demand requests and the aggressive lookahead mechanisms. The basic idea behind these two mechanisms is to combine accurate data prefetching with current demand fetching whenever the prefetch accuracy is expected to be high. Simulation of these two mechanisms on RPT (Reference Prediction Table - one of the most cited selective data prefetching schemes [2,3]) using SPEC95 showed that significant reduction in the data reference latency, ranging from a few percent to 60%, can be obtained. Furthermore, the additional hardware support for this scheme is very simple, thus making the mechanisms attractive for practical cache implementation.