Abstract Generational garbage collection is one of the most commonly used dynamic memory management techniques. Copying generational garbage collection can achieve better collection efficiency by compaction via object movement. However, object movement requires more processing overhead during collection time. Non-copying generational garbage collection eliminates the overhead of object movement. In association of with the limited memory traversal technique, it can achieve faster collection runs. But, since no compaction technique is used, poorer collection efficiency us unavoided. In addition, some in-effective design choices can greatly reduce the efficiency of generational garbage collectors. They include poor prediction of object lifetimes, unnecessarily frequent collection runs, and in-effective internal fragmentation reduction within pages, etc. In this research, we designed a user-configurable garbage collection method to improve collection efficiency and performance of current non-copy generational garbage collection method. Dynamically generated objects are characterized into four collection categories according to the usage characteristic as well as this predicted lifetimes of the objects. Our memory allocator will allocate objects to different storage heaps according to their collection categories. The four categories are: (1) short life time objects: allocated in the multiple generations, storage and collect are in the multiple ways of generation . (2) long life time objects: allocated in the single generation, storage and collect are in the single way of generation. (3) permanent life time objects: allocated in the area never been collected, the objects will occupy the space until the program terminate. (4) user-level management objects: allocated in the area never been collected, but the object will be allocated and freed by the user. For different collection categories, we separately incorportes domain-specific knowledge of memory allocation and garbage collection. We plan to restrict each garbage collection activity on its own category heap. Hence, when certain category heap needs to be collected, only a small portion of dynamic data is involved. Category-specific collection timing decision reclamation, re-allocation, and memory allocation methods can be devised for each category heap. In addition, it allows users to apply their knowledge of the program characteristics to suitabley classify the generated object's collection category to improve the collection efficiency. It also allows users to integrate direct-managed collection and automatic collection technique in one program. For performance validation, we carried out a set of performance experiments. The experiments indicate that we can reduce collection overhead and improve the average number of effective memory pages in running cases with different characteristics with our non

The provision of system-wide heap storage has a number of advantages. However, when the technique is applied to distributed systems automatically recovering inaccessible variables becomes a serious problem. This thesis presents a survey of such garbage collection techniques but finds that no existing algorithm is entirely suitable. A new, general purpose algorithm is developed and presented which allows individual systems to garbage collect largely independently. The effects of these garbage collections are combined, using recursively structured control mechanisms, to achieve garbage collection of the entire heap with the minimum of overheads. Experimental results show that new algorithm recovers most inaccessible variables more quickly than a straightforward garbage collection, giving an improved memory utilisation.

published_or_final_version / Computer Science / Master / Master of Philosophy

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Due to advances in capacity, speed, and economics, NAND-based flash memory technology is increasingly integrated into all types of computing systems, ranging from enterprise servers to embedded devices. However, due to its unpredictable up-date behavior and time consuming garbage collection mechanism, NAND-based flash memory is difficult to integrate into hard-real-time embedded systems. In this thesis, I propose a performance model for flash memory garbage collection that can be used in conjunction with a number of different garbage collection strategies. I describe how to model the cost of reactive (lazy) garbage collection and compare it to that of more proactive schemes. I develop formulas to assess the schedulability of hard real- time periodic task sets under simplified memory consumption models. Results show that I prove the proactive schemes achieve the larger maximum schedulable utilization than the traditional garbage collection mechanism for hard real-time systems in flash memory.

Thesis (M.S.)--George Mason University, 2007. / Title from PDF t.p. (viewed Jan. 18, 2008). Thesis director: Elizabeth White. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science. Vita: p. 152. Includes bibliographical references (p. 150-151). Also available in print.

Thesis (Ph. D.)--Washington State University, August 2007. / Includes bibliographical references (p. 168-179).

Title Garbage Collection in Software Performance Engineering Author Peter Libič peter.libic@d3s.mff.cuni.cz Advisor doc. Ing. Petr Tůma, Dr. petr.tuma@d3s.mff.cuni.cz Department Department of Distributed and Dependable Systems Faculty of Mathematics and Physics Charles University Malostranské nám. 25, 118 00 Prague, Czech Republic Abstract The increasing popularity of languages with automatic memory management makes the garbage collector (GC) performance key to effective application execution. Unfortunately, performance behavior of contemporary GC is not well understood by the application developers and often ignored by the per- formance model designers. In this thesis, we (1) evaluate nature of GC overhead with respect to its effect on accuracy of performance models. We assess the possibility to model GC overhead as a black-box and identify workload characteristics that contribute to GC performance. Then we (2) design an analytical model of one-generation collector and a simulation model of both one-generation and two-generation collectors. These models rely on application characteristics. We evaluate the accuracy of such models and perform an analysis of their sensitivity to the inputs. Using the model we expose the gap between under- standing the GC overhead based on knowing the algorithm...

Garbage collector performance in LISP systems on custom hardware has been substantially improved by the adoption of lifetime-based garbage collection techniques. To date, however, successful lifetime-based garbage collectors have required special-purpose hardware, or at least privileged access to data structures maintained by the virtual memory system. I present here a lifetime-based garbage collector requiring no special-purpose hardware or virtual memory system support, and discuss its performance.