Publication | Closed Access
The garbage collection advantage
158
Citations
16
References
2004
Year
Unknown Venue
EngineeringSoftware SystemsComputer ArchitectureGarbage Collection TimeSoftware EngineeringHardware SystemsSoftware AnalysisGarbage Collection AdvantageProcessor SpeedCompilersParallel ComputingData ManagementMemory ManagementDynamic CompilationStatic AnalysisComputer EngineeringComputer ScienceInformation ManagementReal-time JavaStatic Program AnalysisProgram AnalysisReal-time SystemsTechnologyGarbage CollectionSystem SoftwareTransactional Memory
As improvements in processor speed continue to outpace improvements in cache and memory speed, poor locality increasingly degrades performance. Because copying garbage collectors move objects, they have an opportunity to improve locality. However, no static copying order is guaranteed to match program traversal orders. This paper introduces <i>online object reordering</i> (OOR) which includes a new dynamic, online class analysis for Java that detects program traversal patterns and exploits them in a copying collector. OOR uses run-time method sampling that drives just-in-time (JIT) compilation. For each <i>hot</i> (frequently executed) method, OOR analysis identifies the hot field accesses. At garbage collection time, the OOR collector then copies referents of hot fields together with their parent. Enhancements include static analysis to exclude accesses in cold basic blocks, heuristics that decay heat to respond to phase changes, and a separate space for hot objects. The overhead of OOR is on average negligible and always less than 2% on Java benchmarks in Jikes RVM with MMTk. We compare program performance of OOR to static class-oblivious copying orders (e.g., breadth and depth first). Performance variation due to static orders is often low, but can be up to 25%. In contrast, OOR matches or improves upon the best static order since its history-based copying tunes memory layout to program traversal.
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