Distance-adaptive update protocols for scalable shared-memory multiprocessors

While update protocols generally induce lower miss rates than invalidate protocols, they tend to generate much traffic. This is one of the reasons why they are considered less cost-effectively scalable than invalidate protocols and, as a result, are avoided in most existing designs of scalable shared-memory multiprocessors. However, given the increasing relative cost of cache misses, update protocols are becoming more worthy of exploration. In this paper, we present a model of sharing that is key to investigating the performance of optimized update protocols: the Update Distance Model. The model gives insight into the update patterns that optimized protocols need to handle. Using this model, we design a new family of protocols that we call Distance-Adaptive Protocols. In these schemes, the directory records the update patterns observed and then uses them to selectively send updates and invalidations to processors. As a result, traffic and miss rates are kept low. We present an implementation of these protocols based on a dynamic pointer scheme. A performance comparison between one of these protocols and efficient invalidate and delayed competitive-update protocols over five applications shows that the new protocol decreases the execution time by an average of 15% and 10% respectively.