Computer-time garbage collection by sharing analysis

Jones, Simon B.; Métayer, Daniel Le

doi:10.1145/99370.99375

Cited by 62 publications

(15 citation statements)

References 9 publications

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“…In the space of functional languages, there are: rewriting methods such as deforestation [9,12,34], sharing analysis based reallocation [17], region based analysis [33], and insertion of compiletime nullifying statements [16,21]. All compile-time marking approaches rely on an efficient and precise alias analysis and cannot provide significant improvement in its absence.…”

Section: Related Workmentioning

confidence: 99%

Liveness-based garbage collection for lazy languages

Kumar

Sanyal

2016

Proceedings of the 2016 ACM SIGPLAN International Symposium on Memory Management

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We consider the problem of reducing the memory required to run lazy first-order functional programs. Our approach is to analyze programs for liveness of heap-allocated data. The result of the analysis is used to preserve only live data-a subset of reachable data-during garbage collection. The result is an increase in the garbage reclaimed and a reduction in the peak memory requirement of programs. While this technique has already been shown to yield benefits for eager first-order languages, the lack of a statically determinable execution order and the presence of closures pose new challenges for lazy languages. These require changes both in the liveness analysis itself and in the design of the garbage collector.To show the effectiveness of our method, we implemented a copying collector that uses the results of the liveness analysis to preserve live objects, both evaluated and closures. Our experiments confirm that for programs running with a liveness-based garbage collector, there is a significant decrease in peak memory requirements. In addition, a sizable reduction in the number of collections ensures that in spite of using a more complex garbage collector, the execution times of programs running with liveness and reachability-based collectors remain comparable.

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Section: Related Workmentioning

confidence: 99%

Liveness-based garbage collection for lazy languages

Kumar

Sanyal

2016

Proceedings of the 2016 ACM SIGPLAN International Symposium on Memory Management

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“…In the first, the program itself is instrumented to manage reclamation and reallocation without the aid of the garbage collector. Such attempts include: sharing analysis based reallocation [12], deforestation techniques [13,14,15], methods based on linear logic [16] and region analysis [17]. Closer to our approach, there are methods that enable the garbage collector to collect more garbage [18,6] by explicitly nullifying pointers that are not live.…”

Section: Related Workmentioning

confidence: 99%

Liveness-Based Garbage Collection

Asati

Sanyal

Mycroft

2014

Lecture Notes in Computer Science

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Abstract. Current garbage collectors leave much heap-allocated data uncollected because they preserve data reachable from a root set. However, only live data-a subset of reachable data-need be preserved.Using a first-order functional language we formulate a context-sensitive liveness analysis for structured data and prove it correct. We then use a 0-CFA-like conservative approximation to annotate each allocation and function-call program point with a finite-state automaton-which the garbage collector inspects to curtail reachability during marking. As a result, fewer objects are marked (albeit with a more expensive marker) and then preserved (e.g. by a copy phase).Experiments confirm the expected performance benefits-increase in garbage reclaimed and a consequent decrease in the number of collections, a decrease in the memory size required to run programs, and reduced overall garbage collection time for a majority of programs.

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“…Strictness analysis [8,24,25,36], update analysis [4,19], and sharing analysis [20] may all be able to provide useful information.…”

Section: Related Workmentioning

confidence: 99%

Smarter garbage collection with simplifiers

O'Neill

Burton

2006

Proceedings of the 2006 Workshop on Memory System Performance and Correctness

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We introduce a method for providing lightweight daemons, called simplifiers, that attach themselves to program data. If a data item has a simplifier, the simplifier may be run automatically from time to time, seeking an opportunity to "simplify" the object in some way that improves the program's time or space performance.It is not uncommon for programs to improve their data structures as they traverse them, but these improvements must wait until such a traversal occurs. Simplifiers provide an alternative mechanism for making improvements that is not tied to the vagaries of normal control flow.Tracing garbage collectors can both support the simplifier abstraction and benefit from it. Because tracing collectors traverse program data structures, they can trigger simplifiers as part of the tracing process. (In fact, it is possible to view simplifiers as analogous to finalizers; whereas an object can have a finalizer that is run automatically when the object found to be dead, a simplifier can be run when the object is found to be live.)Simplifiers can aid efficient collection by simplifying objects before they are traced, thereby eliminating some data that would otherwise have been traced and saved by the collector. We present performance data to show that appropriately chosen simplifiers can lead to tangible space and speed benefits in practice. Different variations of simplifiers are possible, depending on the triggering mechanism and the synchronization policy. Some kinds of simplifier are already in use in mainstream systems in the form of ad-hoc garbage-collector extensions. For one kind of simplifier we include a complete and portable Java implementation that is less than thirty lines long.

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Computer-time garbage collection by sharing analysis

Cited by 62 publications

References 9 publications

Liveness-based garbage collection for lazy languages

Liveness-based garbage collection for lazy languages

Liveness-Based Garbage Collection

Smarter garbage collection with simplifiers

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