Effective “static-graph” reorganization to improve locality in garbage-collected systems

Wilson, Paul R.; Lam, Michael S.; Moher, Tom

doi:10.1145/113446.113461

Cited by 44 publications

(40 citation statements)

References 24 publications

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“…Finally, we compared our approach against the WilsonLam-Moher algorithm [30], which uses a hierarchical decomposition algorithm for copying data between semispaces (instead of Cheney's breadth-first traversal) to improve a program's virtual memory (page) locality. This experiment (Table 6) investigated whether techniques designed to improve locality at the memory (page) level are effective at the cache level, and to ensure that the cachemiss rate reductions in Table 5 are not exaggerated by the poor locality of the base case (which uses Cheney's breadthfirst traversal algorithm).…”

Section: Resultsmentioning

confidence: 99%

“…Moon describes a modification to this algorithm that results in approximate depth-first copying [18]. Wilson et al further refine the traversal to obtain hierarchical grouping of objects in TO space [30]. The copying algorithm ( Figure 9) described in this section uses the object affinity graph to produce a cache-conscious layout of objects in TO space.…”

Section: Combining Cache-conscious Data Placement With Garbage Collecmentioning

confidence: 99%

“…Other researchers have attempted to improve a program's virtual memory (page) locality by changing the traversal algorithm used by a copying garbage collector [18,30,15,10]. We compare our cache-conscious copying scheme against one such algorithm (the Wilson-Lam-Moher algorithm [30]).…”

Section: Introductionmentioning

confidence: 99%

“…We compare our cache-conscious copying scheme against one such algorithm (the Wilson-Lam-Moher algorithm [30]). The results show that our cache-conscious object layout reduces cache miss rates by 20-41% and improves program performance by 18-31% over their technique, indicating that page-level improvements are not necessarily effective at the cache level.…”

Section: Introductionmentioning

confidence: 99%

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Using generational garbage collection to implement cache-conscious data placement

Chilimbi

Larus

1998

SIGPLAN Not.

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The cost of accessing main memory is increasing. Machine designers have tried to mitigate the consequences of the processor and memory technology trends underlying this increasing gap with a variety of techniques to reduce or tolerate memory latency. These techniques, unfortunately, are only occasionally successful for pointer-manipulating programs. Recent research has demonstrated the value of a complementary approach, in which pointer-based data structures are reorganized to improve cache locality. This paper studies a technique for using a generational garbage collector to reorganize data structures to produce a cache-conscious data layout, in which objects with high temporal affinity are placed next to each other, so that they are likely to reside in the same cache block. The paper explains how to collect, with low overhead, real-time profiling information about data access patterns in object-oriented languages, and describes a new copying algorithm that utilizes this information to produce a cache-conscious object layout. Preliminary results show that this technique reduces cache miss rates by 21-42%, and improves program performance by 14-37% over Cheney's algorithm. We also compare our layouts against those produced by the WilsonLam-Moher algorithm, which attempts to improve program locality at the page level. Our cache-conscious object layouts reduces cache miss rates by 20-41% and improves program performance by 18-31% over their algorithm, indicating that improving locality at the page level is not necessarily beneficial at the cache level.

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Section: Resultsmentioning

confidence: 99%

Section: Combining Cache-conscious Data Placement With Garbage Collecmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Using generational garbage collection to implement cache-conscious data placement

Chilimbi

Larus

1998

SIGPLAN Not.

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“…Although there are works on how to reap the merits of virtual memory system [26][25] [27], these proposed mechanisms are mostly ignored by current garbage collectors, as pointed out in [24] where the authors propose to build barriers between secondary storage and the main memory in order to avoid collection paging. We should also mention [5] which describes a concurrent, incremental and parallel algorithm designed for compactors.…”

Section: Vm-aware Designmentioning

confidence: 99%

Index-Compact Garbage Collection

Tong

Lau

2010

Programming Languages and Systems

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Abstract. Automatic garbage collection is currently adopted by many object-oriented programming systems. Among the many variants, a markcompact garbage collector offers high space efficiency and cheap object allocation, but suffers from poor virtual memory interactions. It needs to linearly scan through the entire available heap, triggering many page faults which may lead to excessively long collection time. We propose building an object reference index while tracing the heap, which in the following stages can be used to directly locate the live objects. As the dead objects are not touched, the collection time becomes dependent only on the size of the live data set. We have implemented a prototype in Jikes RVM, which shows promising results with the SPECjvm98 benchmarks.

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Swap compression: resurrecting old ideas

Cortes

Becerra

Cervera

2000

Softw: Pract. Exper.

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The performance of memory-intensive applications tends to be poor due to the high overhead added by the swapping mechanism. The same problem may be found in highly-loaded multi-programming systems where all running applications have to use the swap space in order to be able to execute at the same time.In this paper, we present a solution to these problems. The idea consists of compressing the swapped pages and keeping them in a swap cache whenever possible.The idea of a compressed swap cache was proposed a few years ago, but it did not achieve the expected results due to hardware limitations. As processors are much faster and the performance gap between processors and disk is also much bigger, we believe that now it is the right time to revisit this idea. In this paper, we present a new implementation of the compressed cache, plus some enhancements that significantly improve the performance of the swapping mechanism. A FIRST APPROACH TerminologyBefore starting to describe the compressed swap cache, we believe it is necessary to define some terms that might otherwise get mixed up.

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Effective “static-graph” reorganization to improve locality in garbage-collected systems

Cited by 44 publications

References 24 publications

Using generational garbage collection to implement cache-conscious data placement

Using generational garbage collection to implement cache-conscious data placement

Index-Compact Garbage Collection

Swap compression: resurrecting old ideas

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