Fast Conservative Garbage Collection

Garbage collectors are exact or conservative. An exact collector identifies all references precisely and may move referents and update references, whereas a conservative collector treats one or more of stack, register, and heap references as ambiguous. Ambiguous references constrain collectors in two ways. (1) Since they may be pointers, the collectors must retain referents. (2) Since they may be values, the collectors cannot modify them, pinning their referents.

We explore conservative collectors for managed languages, with ambiguous stacks and registers. We show that for Java benchmarks they retain and pin remarkably few heap objects: <0.01% are falsely retained and 0.03% are pinned. The larger effect is collector design. Prior conservative collectors (1) use mark-sweep and unnecessarily forgo moving all objects, or (2) use mostly copying and pin entire pages. Compared to generational collection, overheads are substantial: 12% and 45% respectively. We introduce high performance conservative Immix and reference counting (RC). Immix is a mark-region collector with fine line-grain pinning and opportunistic copying of unambiguous referents. Deferred RC simply needs an object map to deliver the first conservative RC. We implement six exact collectors and their conservative counterparts. Conservative Immix and RC come within 2 to 3% of their exact counterparts. In particular, conservative RC Immix is slightly faster than a well-tuned exact generational collector. These findings show that for managed languages, conservative collection is compatible with high performance.

发言人详细信息

Rifat Shahriyar is a PhD student at Australian National University. He is supervised by Steve Blackburn and Kathryn McKinley. He is also working as an Assistant Professor in Bangladesh University of Engineering and Technology. His research interests are memory management specially garbage collection, virtual machine design & implementation, and programming language.

专题：
Microsoft Research Talks
日期：
演讲者：
Rifat Shahriyar
所属机构：
Australian National University

系列： Microsoft Research Talks