Efficient Object Sampling via Weak References

Abstract

The performance of automatic memory management may be improved if the policies used in allocating and collecting objects had knowledge of the lifetimes of objects. To date, approaches to the pretenuring of objects in older generations have relied on profile-driven feedback gathered from trace runs. This feedback has been used to specialize allocation sites in a program. These approaches suffer from a number of limitations. We propose an alternative that through efficient sampling of objects allows for on-line adaption of allocation sites to improve the efficiency of the memory system. In doing so, we make use of a facility already present in many collectors such as those found in Java™ virtual machines: weak references. By judiciously tracking a subset of allocated objects with weak references, we are able to gather the necessary statistics to make better object-placement decisions.