Connectivity-BasedGarbage Collection

Presenter Feng XianAuthor Martin Hirzel, et.alPublished in OOPSLA’2003

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Garbage Collection Benefits

Garbage collection leads to simpler• Design no complex deallocation protocols

• Implementation automatic deallocation

• Maintenance fewer bugs

Benefits are widely accepted

• Java, C#, Python, …

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Garbage Collection:Haven’t we solved this problem yet?• For a state-of-the-art garbage collector:

– time ~14% of execution time– space 3x high watermark– pauses 0.8 seconds

• Can reduce any one cost

• Challenge: reduce all three costs

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Example Heap

Boxes: heap objects

Arrows: pointers

Long box: stack + global variables

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Thesis

1. Objects form distinct data structures

2. Connected objects die together

3. Garbage collectors can exploit 1. and 2. to reclaim objects efficiently

stack +globals

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Experimental Infrastructure

JikesRVM Research Virtual Machine– From IBM Research– Written in Java– Application and runtime system share heap

Good garbage collection even more important

Benchmarks– SPECjvm98 suite and SPECjbb2000– Java Olden suite– xalan, ipsixql, nfc, jigsaw

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Outline

• Garbage Collector Design Principles

• Family of Garbage Collectors

• Design Space Exploration

• Conclusion

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Garbage Collector Design Principles

“Do partial collections.”

Don’t collect the full heap every time

Shorter pause times

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Garbage Collector Design Principles

“Predict lifetime based on age.”

Generational hypothesis:Most objects die young

Generational garbage collection:– Partition by age– Collect young objects

most often

Low time overhead

That’s the state of the art.

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young generation old generation

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Garbage Collector Design Principles

Generational GC Problems

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young generation old generation

Regular full collections Long peak pause

Old-to-young pointers Need bookkeeping

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Garbage Collector Design Principles

“Collect connected objects together.”Likelihood that two objects die at the same time:

Connectivity Example Likelihood

Any pair 33.1%

Weakly connected 46.3%

Strongly connected 72.4%

Direct pointer 76.4%

o2o1 ?

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Garbage Collector Design Principles

“Focus on objects with few ancestors.”

Shortlived objects are easy to collect

LifetimeMedian number of ancestor objects

Short 2 objects

Long 83,324 objects

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Garbage Collector Design Principles

“Predict lifetime based on roots.”

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Lifetime

Objects reachable … Short Long

indirectly from stack 25.6% 16.2%

only directly from stack 32.9% 0.8%

from globals 4.0% 20.5%

Total 62.5% 37.5%

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For details, see [ISMM’02] paper.

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Outline

• Garbage Collector Design Principles

• Family of Garbage Collectors

• Design Space Exploration

• Conclusion

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CBGC Family of Garbage Collectors:

Connectivity-Based Garbage Collection

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• Do partial collections.• Collect connected

objects together.• Predict lifetime based

on age.• Focus on objects with

few ancestors.• Predict lifetime based

on roots.

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Family of Garbage Collectors

Components of CBGC

Before allocation:1. Partitioning

Decide into which partition to put each object

Collection algorithm:2. Estimator

Estimate dead + live objects for each partition

3. ChooserChoose “good” set of partitions

4. Partial collectionCollect chosen partitions

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Find fine-grained partitions, where

• Partition edgesrespect pointers

• Objects don’t move between partitions

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Family of Garbage Collectors

Partitioning Problem

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Pointer analysis• Type-based [Harris]

– o1 may point to o2 if o1 has a field of atype compatible to o2

-conservative: they determine the absence of a pointer btw two heaps only if they can prove that such pointer cannot exist.

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Family of Garbage Collectors

Partitioning Solutions

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Family of Garbage Collectors

Estimator Problem

For each partition guess

dead – Objects that can be

reclaimed– Pay-off

live– Objects that must be

traversed– Cost

3 dead + 3 live

1 dead + 2 live

2 dead + 0 live

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Family of Garbage Collectors

Estimator Solutions

Heuristics• Connected objects die

together• Most objects die

young• Objects reachable

from globals live long• The past predicts the

future

3 dead + 3 live

1 dead + 2 live

2 dead + 0 live

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Family of Garbage Collectors

Chooser Problem

Pick subset of partitions• Maximize total dead

• Minimize total live

• Closed under predecessor relation

No bookkeeping for external

pointers

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7 dead + 5 live

3 dead + 3 live

1 dead + 2 live

2 dead + 0 live

2 dead + 2 live

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Family of Garbage Collectors

Chooser Solutions

Optimal algorithm based on network flow [TR]

Simpler, greedy algorithm

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3 dead + 3 live

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Family of Garbage Collectors

Partial Collection Problem

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Look only at chosen partitions

Traverse reachable objects

Reclaim unreachable objects

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Family of Garbage Collectors

Partial Collection Solutions

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rest of heap

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Generalize canonical full-heap algorithms

• Mark and sweep[McCarthy’60]

• Semi-space copying[Cheney’70]

• Treadmill[Baker’92]

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Outline

• Garbage Collector Design Principles

• Family of Garbage Collectors

• Design Space Exploration

• Conclusion

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Design Space Exploration

Questions

How good is a naïve CBGC?

How good could CBGC be in 20 years?

How well does CBGC do in a JVM?

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Design Space Exploration

Simulator Methodology

Garbage collection simulator (under GPL)– Uses traces of allocations and pointer writes

from our benchmark runs

Simulator advantages– Easier to implement variety of collector algorithms– Know entire trace beforehand:

can use that for “in 20 years” experiments

Currently adding CBGC to JikesRVM

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Design Space Exploration

How good is a naïve CBGC?

Cost in time

Cost in space

Pause times

Full-heapSemi-space

copying

CBGC-naïve• Type-based

partitioning [Harris]• Heuristics

estimator

AppelCopying

generational

jack xalan jbb javac jack xalan jbb javac jack xalan jbb javac1.72

0

0

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0.87

0.22

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Cost in time

Cost in space

Pause times

Full-heapSemi-space

copying

CBGC-oraclesPartitioning

and estimatorbased on trace

AppelCopying

generational

jack xalan jbb javac jack xalan jbb javac jack xalan jbb javac

Design Space Exploration

How good could CBGC be in 20 years?1.72

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CBGC with oracles beats Appel– We did not find a “performance wall”– CBGC has potential

The performance gap between CBGC with oracles and naïve CBGC is large

– Research challenges

Design Space Exploration

How good could CBGC be in 20 years?

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How well does CBGC doin a Java virtual machine?

Implementation in progress

Need a pointer analysis for the partitioning

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Contributions presented in this talk

Connectivity-based GC design principles[ISMM’02]

CBGC, a new family of garbage collectors;

Design space exploration with simulator[OOPSLA’03]