Waste Not, Want Not: Adaptive Garbage Collection in a Shared Environment

Limiting the amount of memory available to a program can hamstring its performance, however in a garbage collected environment allowing too large of a heap size can also be detrimental. Because garbage collection will occasionally access the entire heap, having a significant amount of virtual memory becomes expensive. Determining the appropriate size for a program's heap is not only important, but difficult in light of various virtual machines, operating systems, and levels of multi-programming with which the program may be run. We present a model for program memory usage with which we can show how effective multi-programming is likely to be. In addition, we present an automated system for adding control at the program level that allows runtime adaptation of a program's heap size. The process is fully automatic and requires no extra coding on the part of programmers. We discuss two adaptive schemes: The first acts independently, and while performing competitively, system behaves politely in a multi-programmed environment. The second scheme explicitly cooperates when multiple instances are running. Both schemes are evaluated in terms of their response time, throughput, and fairness