Static Analysis for Identifying and Allocating Clusters of Immortal Objects

Long living objects lengthen the trace time which is a critical phase of the garbage collection process. However, it is possible to recognize object clusters i.e. groups of long living objects having approximately the same lifetime and treat them separately to reduce the load on the garbage collector and hence improve overall performance. Segregating objects this way leaves the heap for objects with shorter lifetimes and now a typical collection can find more garbage than before. In this paper, we describe a compile time analysis strategy to identify object clusters in programs. The result of the compile time analysis is the set of allocation sites that contribute towards allocating objects belonging to such clusters. All such allocation sites are replaced by a new allocation method that allocates objects into the cluster area rather than the heap. This study was carried out for a concurrent collector which we developed for Rotor, Microsoft’s Shared Source Implementation of .NET. We analyze the performance of the program with combinations of the cluster and stack allocation optimizations. Our results show that the clustering optimization reduces the number of collections by 66.5% on average, even eliminating the need for collection in some programs. As a result, the total pause time reduces by 62.8% on average. Using both stack allocation and the cluster optimizations brings down the number of collections by 91.5% thereby improving the total pause time by 79.33%.