We survey basic garbage collection algorithms, and variations such as incremental and generational collection; we then discuss low-level implementation considerations and the relationships between storage management systems, languages, and compilers. Throughout, we attempt to present a uni ed view based on abstract traversal strategies, addressing issues of conservatism, opportunism, and immediacy of reclamation; we also point outavariety of implementation details that are likely to have a significant impact on performance.

this paper. associated with a relocating collector is saved; other costs remain, however, such as the costs of updating all pointers and foregoing some compiler optimizations.

The complexity of systems for automatic control and other safety-critical applications grows rapidly. Computer software represents an increasing part of the complexity. As larger systems are developed, we need to find scalable techniques to manage the complexity in order to guarantee high product quality. Memory management is a key quality factor for these systems. Automatic memory management, or garbage collection, is a technique that significantly reduces the complex problem of correct memory management. The risk of software errors decreases and development time is reduced. Garbage collection techniques suitable for interactive and soft real-time systems exist, but few approaches are suitable for systems with hard real-time requirements, such as control systems (embedded systems). One part of the problem is solved by incremental garbage collection algorithms, which have been presented before. We focus on the scheduling problem which forms the second part of the problem, i.e. how the work of a garbage collector should be scheduled in order

Garbage collection is the automatic reclamation of computer storage [Knu73, Coh81, Wil92, Wil95]. While in many systems, programmers must explicitly reclaim heap memory at some point in their program by using a "free" or "dispose" statement, garbage collected systems free the programmer from this burden. In spite of its obvious attractiveness for many applications, garbage collection for real-time programs is not popular. This is largely due to the perceived cost and disruptiveness of garbage collection in general, and of incremental garbage collection in particular. Most existing "real-time" garbage collectors are not in fact usefully real-time, largely due to the use of a read barrier to trigger incremental copying of data structures being traversed by the running application. This may slow down running applications unpredictably, even though individual increments of garbage collection work are small and bounded. We have developed a hard real-time garbage collector which us...

Reference counting is not naturally suitable for running on multiprocessors. The update of pointers and reference counts requires atomic and synchronized operations. We present a novel reference counting algorithm suitable for a multiprocessor that does not require any synchronized operation in its write barrier (not even a compare-and-swap type of synchronization). The algorithm is efficient and may compete with any tracing algorithm.

The emergence of standards for programming real-time systems in Java has encouraged many developers to consider its use for systems previously only built using C, Ada, or assembly language. However, the RTSJ standard in isolation leaves many important problems unaddressed, and suffers from some serious problems in usability and safety. As a result, the use of Java for real-time programming has continued to be viewed as risky and adoption has been slow. In this paper we provide a description of IBM’s new real-time Java virtual machine product, which combines Metronome realtime garbage collection, ahead-of-time compilation, and a complete implementation of the RTSJ standard, running on top of a custom real-time multiprocessor Linux kernel. We will describe the implementation of each of these components, including how they interacted both positively and negatively, and the extensions to previous work required to move it from research prototype to a system implementing the complete semantics of the Java language. The system has been adopted for hard real-time development of naval weapons systems and soft real-time telecommunications servers. We present measurements showing that the system is able to provide sub-millisecond worst-case garbage collection latencies, 50 microsecond Linux scheduling accuracy, and eliminate non-determinism due to JIT compilation.

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

Many programming languages provide automatic garbage collection to reduce the need for memory management related programming. However, traditional garbage collection techniques lead to long and unpredictable delays and are therefore not satisfactory in a number of settings, such as interactive systems, where non-disruptive behavior is of paramount importance. Advanced techniques, such as generation-based collection, alleviate the problem somewhat by concentrating collection efforts on small but hopefully gainful areas of memory, the so-called young generations. This approach reduces the need for collecting the remaining large memory area, the old generation, but in no way obviates it. Traditionally, conventional techniques have been employed for old generation collection, leading to pauses which, although less frequent, are still highly disruptive. Recently, however, Hudson & Moss have introduced a new algorithm, the Train Algorithm, for performing efficient incremental collection of o...

Constructing correct concurrent garbage collection algorithms is notoriously hard. Numerous such algorithms have been proposed, implemented, and deployed – and yet the relationship among them in terms of speed and precision is poorly understood, and the validation of one algorithm does not carry over to others. As programs with low latency requirements written in garbagecollected languages become part of society’s mission-critical infrastructure, it is imperative that we raise the level of confidence in the correctness of the underlying system, and that we understand the trade-offs inherent in our algorithmic choice. In this paper we present correctness-preserving transformations that can be applied to an initial abstract concurrent garbage collection algorithm which is simpler, more precise, and easier to prove correct than algorithms used in practice — but also more expensive and with less concurrency. We then show how both pre-existing and new algorithms can be synthesized from the abstract algorithm by a series of our transformations. We relate the algorithms formally using a new definition of precision, and informally with respect to overhead and concurrency. This provides many insights about the nature of concurrent collection, allows the direct synthesis of new and useful algorithms, reduces the burden of proof to a single simple algorithm, and lays the groundwork for the automated synthesis of correct concurrent collectors. 1.

Tracing and reference counting are uniformly viewed as being fundamentally different approaches to garbage collection that possess very distinct performance properties. We have implemented highperformance collectors of both types, and in the process observed that the more we optimized them, the more similarly they behaved — that they seem to share some deep structure. We present a formulation of the two algorithms that shows that they are in fact duals of each other. Intuitively, the difference is that tracing operates on live objects, or “matter”, while reference counting operates on dead objects, or “anti-matter”. For every operation performed by the tracing collector, there is a precisely corresponding anti-operation performed by the reference counting collector. Using this framework, we show that all high-performance collectors (for example, deferred reference counting and generational collection) are in fact hybrids of tracing and reference counting. We develop a uniform cost-model for the collectors to quantify the trade-offs that result from choosing different hybridizations of tracing and reference counting. This allows the correct scheme to be selected based on system performance requirements and the expected properties of the target application.