This paper reports our experiences with a mostly-concurrent incremental garbage collector, implemented in the context of a high performance virtual machine for the Java^TM programming language. The garbage collector is based on the "mostly parallel" collection algorithm of Boehm et al., and can be used as the old generation of a generational memory system. It overloads efficient write-barrier code already generated to support generational garbage collection to also identify objects that were modified during concurrent marking. These objects must be rescanned to ensure that the concurrent marking phase marks all live objects. This algorithm minimises maximum garbage collection pause times, while having only a small impact on the average garbage collection pause time and overall execution time. We support our claims with experimental results, for both a synthetic benchmark and real programs.

We present a new analysis for removing unnecessary write barriers in programs that use generational garbage collection. To our knowledge, this is the first static program analysis for this purpose. Our algorithm uses a pointer analysis to locate assignments that always create a reference from a younger object to an older object, then transforms the program to remove the write barriers normally associated with such assignments. We have implemented two transformations that reorder object allocations; these transformations can significantly increase the effectiveness of our write barrier removal algorithm. Our base technique assumes that the collector promotes objects in age order. We have developed an extension that enables the optimistic removal of write barriers, with the collector lazily adding each newly promoted object into a remembered set of objects whenever the compiler may have removed write barriers involving the object at statements that have yet to execute. This mechanism enables the application of our technique to virtually any memory management system that uses write barriers to enable generational garbage collection. Results from our implemented system show that our technique can remove substantial numbers of write barriers from the majority of the programs in our benchmark set, producing modest performance improvements of up to 6 % of the overall execution time. Moreover, by dynamically instrumenting the executable, we are able to show that for six of our nine benchmark programs, our analysis is close to optimal in the sense that it removes the write barriers for almost all assignments that do not, in the observed execution, create a reference from an older object to a younger object. Finally, our results show that the overhead of our optimistic extension is negligible.

With concurrent and garbage collected languages like Java and C# becoming popular, the need for a suitable non-intrusive, efficient, and concurrent multiprocessor garbage collector has become acute. We propose a novel mark and sweep on-the-fly algorithm based on the sliding views mechanism of Levanoni and Petrank. We have implemented our collector on the Jikes Java Virtual Machine running on a Netfinity multiprocessor and compared it to the concurrent algorithm and to the stop-the-world collector supplied with Jikes JVM. The maximum pause time that we measured with our benchmarks over all runs was 2ms. In all runs, the pause times were smaller than those of the stop-the-world collector by two orders of magnitude and they were also always shorter than the pauses of the Jikes concurrent collector. Throughput measurements of the new garbage collector show that it outperforms the Jikes concurrent collector by up to 60%. As expected, the stop-the-world does better than the on-the-fly collectors with results showing about 10% difference. On top of being

The mostly concurrent garbage collection was presented in the seminal paper of Boehm et al. With the deployment of Java as a portable, secure and concurrent programming language, the mostly concurrent garbage collector turned out to be an excellent solution for Java's garbage collection task. The use of this collector is reported for several modern production Java Virtual Machines and it has been investigated further in academia.

We present STOPLESS: a concurrent real-time garbage collector suitable for modern multiprocessors running parallel multithreaded applications. Creating a garbage-collected environment that supports real-time on modern platforms is notoriously hard, especially if real-time implies lock-freedom. Known real-time collectors either restrict the real-time guarantees to uniprocessors only, rely on special hardware, or just give up supporting atomic operations (which are crucial for lock-free software). STOPLESS is the first collector that provides real-time responsiveness while preserving lock-freedom, supporting atomic operations, controlling fragmentation by compaction, and supporting modern parallel platforms. STOPLESS is adequate for modern languages such as C # or Java. It was implemented on top of the Bartok compiler and runtime for C # and measurements demonstrate high responsiveness (a factor of a 100 better than previously published systems), virtually no pause times, good mutator utilization, and acceptable overheads. 1.

A reference counting garbage collector cannot reclaim unreachable cyclic structures of objects. Therefore, reference counting collectors either use a backup tracing collector seldom, or employ a cycle collector to reclaim cyclic structures. Recently, the first on-the-fly cycle collector, that may run concurrently with program threads, was presented by Bacon and Rajan [3]. This demonstrated the ability to run on-the-fly reference counting without resorting to an auxiliary tracing collector. In this paper

Abstract not found

A reference counting garbage collector cannot reclaim unreachable cyclic structures of objects. Therefore, reference counting collectors either use a backup tracing collector seldom, or employ a cycle collectors to reclaim cyclic structures. Recently, the first on-the-fly cycle collector, that may run concurrently with program threads, was presented by Bacon and Rajan [3]. This demonstrated the ability to run on-the-fly reference counting without resorting to an auxiliary tracing collector.

Generational garbage collection divides a heap up into two or more generations, and usually collects a youngest generation most frequently. Collection of the youngest generation requires identification of pointers into that generation from older generations; a data structure that supports such identification is called a remembered set. Various remembered set mechanisms have been proposed; these generally require mutator code to execute a write barrier when modifying pointer fields. Remembered set data structures can vary in their precision: an imprecise structure requires the garbage collector to do more work to find old-to-young pointers. Generally there is a tradeo# between remembered set precision and barrier cost: a more precise remembered set requires a more elaborate barrier. Many current systems tend to favor more e#cient barriers in this tradeo#, as shown by the widespread popularity of relatively imprecise card marking techniques. This imprecision becomes increasingly costly as the ratio between old- and young-generation sizes grows. We propose a technique that maintains more precise remembered sets that scale with old-generation size, using a barrier whose cost is not significantly greater than card marking.

The current state-of-the-art generational garbage collector pauses all the program threads when it performs young and old generation garbage collection. As the number of program threads increases, the delay due to garbage collection also increases, thus restricting the scalability of the collector. In order to improve the scalability and reduce the pause time, an on-the-fly generational garbage collector called Yama is proposed for multiprocessor systems. This uses the on-the-fly deferred reference counting in the young generation and the DLG (Doligez Leroy Gonthier) on-the-fly mark and sweep garbage collector in the old generation. We have proposed and experimented with two novel variations of the on-the-fly deferred reference counting called Chitragupt1 and Chitragupt2 in the young generation. Yama does not pause all the application threads simultaneously. An adaptive tenuring policy based on object reference count and survival rate is also proposed. Yama has been implemented in the IBM Jikes RVM (Research Virtual Machine). The above claims are supported with experimental results for standard benchmark programs. The results show that Yama has an extremely low pause time in both the young and the old generation. The pause time reduction results in better response times for the user programs.