Markov Decision Processes

Jacek, Nicholas, Meng-Chieh Chiu, Benjamin Marlin, and Eliot J. B. Moss. "Assessing the Limits of Program-Specific Garbage Collection Performance." Programming Language Design and Implementation. 2016. Abstractp584-jacek.pdf

Distinguished Paper Award

We consider the ultimate limits of program-specific garbage collector performance for real programs. We first characterize the GC schedule optimization problem using Markov Decision Processes (MDPs). Based on this characterization, we develop a method of determining, for a given program run and heap size, an optimal schedule of collections for a non-generational collector. We further explore the limits of performance of a generational collector, where it is not feasible to search the space of schedules to prove optimality. Still, we show significant improvements with Least Squares Policy Iteration, a reinforcement learning technique for solving MDPs. We demonstrate that there is considerable promise to reduce garbage collection costs by developing program-specific collection policies.