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Fast Multiprocessor Memory Allocation

and Garbage CollectionHans-J . BoehmInternet and Mobile Systems LaboratoryHP L aboratories Palo AltoHPL -2000-165December 8th, 2000*

E-mail: Hans_Boehm@hp.com

garbagecollection,memoryallocation,multiprocessors,threads

We extended our garbage collecting memory allocator to provide goodperformance for multi-threaded applications on multiprocessors. The

basic design is similar to the approach previously pursued in [12].However, we concentrate on issues important to more common small-scale multiprocessors, and on specific issues not reported elsewhere.We argue that a reasonable level of garbage collector scalability canbe achieved with relatively minor additions to the underlyingcollector code. F urthermore the scalable collector does not need to beappreciably slower on a uniprocessor. Since our collector can serve aa plug-in replacement for malloc/free, we have the opportunity tocompare it to scalable malloc-free implementations, notably Hoard[3]. Somewhat surprisingly, our collector significantly outperformsHoard in some tests, a property that is mostly shared by the garbage

collecting allocator in [ETY97]. We argue that garbagecollectors currently require significantly less synchronization thanexplicit allocators, but that it may be possible to derive significantlyfaster explicit allocators from this observation.Speedy access to thread-local storage is a significant issue in thedesign of allocators that must conform to standard callingconventions. We present empirical evidence that at least in thepresence of a garbage collector, this can often be accomplished fasterin a thread-independent way than through the standard threadlibrary facilities, casting some doubt on the utility of the latter.

*Internal Accession Date Only Approved for External PublicationCopyright Hewlett-Packard Company 2000

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Fast Multiprocessor Memory Allocation and GarbageCollection

Hans-J. Boehm Hewlett-Packard Laboratories1501 Page Mill Rd.

Palo Alto, CA 94304

Hans Boehm@hp.com

ABSTRACT

1. INTRODUCTION

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2. RELATED WORK

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3. CONTEXT

4. PARALLEL ALLOCATION

5. PARALLEL MARKING

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Local Mark stacks(One per marker thread)

Clearedtraced

To be

Queue

Global Mark

6. ISSUES AFFECTING ABSOLUTE PER-

FORMANCE

6.1 Mark bit representation

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6.2 Thread-specific-data

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7. COLLECTOR MEASUREMENTS

7.1 Allocators

7.2 Benchmarks

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7.2.1 Ghostscript

7.2.2 MT GCBench2

7.2.3 Larson

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7.2.4 Larson-small

8. OBSERVATIONS ABOUT EXPLICIT DE-

ALLOCATION

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9. REFERENCES