Active correlation tracking

Abstract

We describe methods of identifying and exploiting sharing patterns in multi-threaded DSM applications. Active correlation tracking is used to determine the affinity, or amount of sharing, in pairs of threads. Thread affinities are combined to create correlation maps, which summarize sharing between all pairs of threads in the application. Correlation maps can be used in two ways. First, they can be used as an aid for performance tuning, Second, they can be used to estimate the impact on communication requirements of reconfiguring running applications through thread migration. Thread migration provides a way of tuning applications for which sharing information is not known a priori, and a means of adapting to dynamic algorithms or environments. We show that i) accurate thread affinities can be obtained without multiple rounds of migration, ii) thread affinities lead to good approximations of application communication requirements, iii) simple heuristics can use thread affinities to efficiently approximate optimal mappings of threads to nodes, and iv) good placement is essential for high performance.