The Economics of Garbage CollectionJeremy Singer, Richard Jones, Gavin Brown, Mikel Luján

Motivation

The main goals

• Determine allocation curve

• Introduce allocation elasticity

• Make use of introduced elasticity

Microeconomics demand curve

Garbage collection analogy

Empirical Allocation Curves

• Empirical data from real-world Java application

• Different algorithms from MMTk toolkit run on JikesRVM

• Java benchmarks from DaCapo suite

• Fixed size heap 35-500 MB

Full-Heap Collection

• Mark-Sweep GC• Allocation curves obey the law of allocation

Generational Collection

• Generational Mark-Sweep GC• Nursery space – frequently collected• Mature space – long-lived objects• Added weight of 0.1 to Nursery GC

Shifting the Allocation Curve

• Added “tax” – additional words to object header• Allocation curve shifted upwards

Elasticity

Controlling Heap Growth using Elasticity

• Elasticity to improve GC performance

• Controlling the expansion rate heap

• Default heuristics for controlling heap size

• Sensitivity in default heuristics

• Alternative heuristics

Alternative Heuristic for Heap Growth Management

• Based on allocation elasticity

• target elasticity, Eo small E, slow heap growth rateo large E, rapid heap growth rate

Execution Time Benchmarks

Final Heap Sizes

Related Work• Stefanovic et al. used statistical techniques

• Baker offered radioactive decay model

• Garbage collection and transactional memory

Conclusion• Microeconomics and memory management

• Allocation curve

• Allocation elasticity