Task-Aware Garbage Collection in a Multi-Tasking Virtual Machine

Sunil Soman, Laurent Daynes, and Chandra Krintz
2006 International Symposium on Memory Management (ISMM'06), June 2006, Ottawa, Canada (Co-located with PLDI'06)



A multi-tasking virtual machine (MVM) executes multiple programs in isolation, within a single operating system process. The goal of a MVM is to improve startup time, overall system throughput, and performance, by effective reuse and sharing of system resources across programs (tasks). However, multitasking also mandates a memory management system capable of offering a guarantee of isolation with respect to garbage collection costs, accounting of memory usage, and timely reclamation of heap resources upon task termination.

To this end, we investigate and evaluate, novel task-aware extensions to a state-of-the-art MVM garbage collector (GC). Our task-aware GC exploits the generational garbage collection hypothesis, in the context of multiple tasks, to provide performance isolation by maintaining task-private young generations. Task aware GC facilitates concurrent per-task allocation and promotion, and minimizes synchronization and scanning overhead. In addition, we efficiently track per-task heap usage to enable GC-free reclamation upon task termination. Moreover, we couple these techniques with a light-weight synchronization mechanism that enables per-task minor collection, concurrently with allocation by other tasks.

We empirically evaluate the efficiency, scalability, and throughput that our task-aware GC system enables.