Dynamic software cache coherence strategies use information about program sharing behaviour to manage caches at run-time and at a granularity defined by the application. The program-level information is obtained through annotations placed into the application by the user or the compiler. The coherence protocols may range from simple static algorithms to dynamic algorithms that use run-time data structures similar to the directories used in hardware strategies. In this paper, we present an analytic study of five dynamic software cache coherence algorithms and compare these to a representative hardware coherence strategy. The analytic model is constructed using four input parameters --- write probability, locality, granularity, and system size --- and solved by analysis of a Markov chain. We show that the fundamental tradeoffs between the different hardware and software strategies are captured in this model. The results of the study show that hardware schemes perform better for fine-grained data structures for much of the parameter space that we study. However, for coarse-grained data structures, various software algorithms are dominant over most of the parameter space. Further, hardware strategies are found to be more susceptible to the effects of contention, and also perform worse for the asymmetric workload that we study.

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The effective management of caches is critical to the performance of applications on shared-memory multiprocessors. In this paper, we discuss a technique for software cache coherence tht is based upon the integration of a program-level abstraction for shared data with software cache management . The program-level abstraction, called Shared Regions, explicitly relates synchronization objects with the data they protect. Cache coherence algorithms are presented which use the information provided by shared region primitives, and ensure that shared regions are always cacheable by the processors accessing them. Measurements and experiments of the Shared Region approach on a shared-memory multiprocessors accessing them. Measurements and experiments of the Shared Region approach on a shared-memory multiprocessor are shown. Comparisons with other software based coherence strategies, including a user-controlled strategy and an operating system-based strategy, show that this approach is able to deliver better performance, with relatively low corresponding overhead and only a small increase in the programming effort. Compared to a compiler-based coherence strategy, the Shared Regions approach still performs better than a compiler that can achieve 90% accuracy in allowing cacheing, as long as the regions are a few hundred bytes or larger, or they are re-used a few times in the cache.

The increasing need for data sharing in large-scale distributed systems may place a heavy burden on critical resources such as file servers and networks. Our examination of the workload in one large commercial engineering environment shows that wide-spread sharing of unstable files among tens to hundreds of users is common. Traditional client-based file cacheing techniques are not scalable in such environments.