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.

No description available.

No description available.

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.

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...

No description available.

Conventional parallel computer architectures do not provide support for non-uniformly distributed objects. In this thesis, I introduce sparsely faceted arrays (SFAs), a new low-level mechanism for naming regions of memory, or facets, on different processors in a distributed, shared memory parallel processing system. Sparsely faceted arrays address the disconnect between the global distributed arrays provided by conventional architectures (e.g. the Cray T3 series), and the requirements of high-level parallel programming methods that wish to use objects that are distributed over only a subset of processing elements. A sparsely faceted array names a virtual globally-distributed array, but actual facets are lazily allocated. By providing simple semantics and making efficient use of memory, SFAs enable efficient implementation of a variety of non-uniformly distributed data structures and related algorithms. I present example applications which use SFAs, and describe and evaluate simple hardware mechanisms for implementing SFAs. Keeping track of which nodes have allocated facets for a particular SFA is an important task that suggests the need for automatic memory management, including garbage collection. To address this need, I first argue that conventional tracing techniques such as mark/sweep and copying GC are inherently unscalable in parallel systems. I then present a parallel memory-management strategy, based on reference-counting, that is capable of garbage collecting sparsely faceted arrays. I also discuss opportunities for hardware support of this garbage collection strategy. I have implemented a high-level hardware/OS simulator featuring hardware support for sparsely faceted arrays and automatic garbage collection. I describe the simulator and outline a few of the numerous details associated with a "real" implementation of SFAs and SFA-aware garbage collection. Simulation results are used throughout this thesis in the evaluation of hardware support mechanisms.

A memory leak is a common software vulnerability that will lead to performance degradation of the software or crash or both. A Memory leak is one typical cause of software aging. The phenomenon of memory leaks usually occurs in C/C++ because programmers need to manage memory by themselves when programs run. However, many think that Java does not suffer from memory leaks since Java provides automatic garbage collection. Actually, Java programs will run out of memory unexpectedly after executing for a long time. The reason for Java memory leaks is that reachable objects are no longer needed. These objects should be reclaimed but they can¡¦t because they are still referenced. This thesis introduces a method for filtering the leaked objects in Java memory leak programs. First, we monitor the heap growth after each full garbage collection and the numbers of full garbage collection to identify programs that might have potential memory management problems. Second, we periodically keep track of growth trend of each object of problematic programs and filter out the suspected one by time series analysis. Finally, we execute the program blocks that include objects that we find out to see if the program will run out of memory eventually. The method has been implemented and has been verified successful by four Java memory leak programs.

This thesis concentrates on the derivation of a modularised version of the DMOS distributed garbage collection algorithm and the implementation of this algorithm in a distributed computational environment. DMOS appears to exhibit a unique combination of attractive characteristics for a distributed garbage collector but the original algorithm is known to contain a bug and, previous to this work, lacks a satisfactory, understandable implementation. The relationship between distributed termination detection algorithms and distributed garbage collectors is central to this thesis. A modularised DMOS algorithm is developed using a previously published distributed garbage collector derivation methodology that centres on mapping centralised collection schemes to distributed termination detection algorithms. In examining the utility and suitability of the derivation methodology, a family of six distributed collectors is developed and an extension to the methodology is presented. The research work described in this thesis incorporates the definition and implementation of a distributed computational environment based on the ProcessBase language and a generic definition of a previously unimplemented distributed termination detection algorithm called Task Balancing. The role of distributed termination detection in the DMOS collection mechanisms is defined through a process of step-wise refinement. The implementation of the collector is achieved in two stages; the first stage defines the implementation of two distributed termination mappings with the Task Balancing algorithm; the second stage defines the DMOS collection mechanisms.

No description available.