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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.

model for garbage collection.

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.

A memory manager that does not move objects may suffer from memory fragmentation. Compaction is an efficient, and sometimes inevitable, mechanism for reducing fragmentation. A Mark-Sweep garbage collector must occasionally execute a compaction, usually while the application is suspended. Compaction during pause time can have detrimental effects for interactive applications that require guarantees for maximal pause time. This work presents a method for reducing the pause time created by compaction at a negligible throughput hit. The solution is most suitable when added to a Mark-Sweep garbage collector. Compaction normally consists of two major activities: the moving of objects and the update of all the objects ’ references to the new locations. We present a method for executing the reference updates concurrently, thus eliminating a substantial portion of the pause time hit. To reduce the time for moving objects in each compaction, we use the existing technique of incremental compaction, but select the optimal area to compact. Selecting the area is done after executing the mark and sweep phases, and is based on their results. We implemented our compaction on top of the IBM J9 JVM V2.2, and present measurements of its effect on pause time, throughput, and mutator utilization. We show that our compaction is indeed an efficient fragmentation reduction tool, and that it improves the performance of a few of the benchmarks we used, with very little increase in the pause time (typically far below the cost of the mark phase).

The Erlang/OTP system has a process centric model of memory management. Each process is created with a local heap where it allocates objects. An alternate approach used in the Erlang to Scheme (ETOS) system is to have a single system-wide heap in which all processes allocate. We have performed an empirical performance evaluation of both systems and found that in most cases the unied heap approach is better because it improves the speed of inter-process communication, especially when large objects are transferred, it reduces the overhead of garbage collection for processes with high allocation rates, and it avoids fragmentation.

We present an implementation of Scheme for microcontroller that is very compact and includes a real-time garbage collector. The compiler, which runs on a normal workstation, produces byte-code from the source program and the bytecode is linked with a runtime module. With this system, we demonstrate that it's clearly possible to run Scheme programs on a microcontroller with 64 KB of memory such as the Motorola 68HC11. Executables that include the whole library can be as little as 22 KB. As a secondary result, the research on memory management for this system brought us to create a space-ecient real-time GC algorithm. 1 Introduction Embedded applications are often implemented by programming microcontrollers in assembly language. Indeed this provides a high degree of control on the microcontroller and fast and compact code for simple applications. However this approach becomes tedious and error prone for more complex applications. For this reason, compilers for higher-level languages su...

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We discuss alternative heap architectures for languages that rely on automatic memory management and implement concurrency through asynchronous message passing. We describe how interprocess communication and garbage collection happens in each architecture, and extensively discuss the tradeoffs that are involved. In an implementation setting (the Erlang/OTP system) where the rest of the runtime system is unchanged, we present a detailed experimental comparison between these architectures using both synthetic programs and large commercial products as benchmarks. Categories and Subject Descriptors D.3.3 [Programming Languages]: Language Constructs and Features—concurrent programming structures, dynamic storage management; D.3.4 [Programming Languages]: Processors—memory management (garbage collection), runtime environments; D.1.3 [Programming Techniques]:

Abstract. There are many algorithms for concurrent garbage collection, but they are complex to describe, verify, and implement. This has resulted in a poor understanding of the relationships between the algorithms, and has precluded systematic concurrent garbage collection algorithm, and show how existing snapshot and incremental update collectors, can be derived from the abstract algorithm by reducing precision. We also derive a new hybrid algorithm that reduces floating garbage while terminating quickly. We have implemented a concurrent collector framework and the resulting algorithms in IBM’s J9 Java virtual machine product and compared their performance in terms of space, time, and incrementality. The results show that incremental update algorithms sometimes reduce memory requirements (on 3 of 5 benchmarks) but they also sometimes take longer due to recomputation in the termination phase (on 4 of 5 benchmarks). Our new hybrid algorithm has memory requirements similar to the incremental update collectors while avoiding recomputation in the termination phase. 1