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

Modern generational garbage collectors look for garbage among the young objects, because they have high mortality; however, these objects include the very youngest objects, which clearly are still live. We introduce new garbage collection algorithms, called age-based, some of which postpone consideration of the youngest objects. Collecting less than the whole heap requires write barrier mechanisms to track pointers into the collected region. We describe here a new, efficient write barrier implementation that works for age-based and traditional generational collectors. To compare several collectors, their configurations, and program behavior, we use an accurate simulator that models all heap objects and the pointers among them, but does not model cache or other memory effects. For object-oriented languages, our results demonstrate that an older-first collector, which collects older objects before the youngest ones, copies on average much less data than generational collectors. Our resul...

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.

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A new garbage collection algorithm for distributed object systems, called DMOS (Distributed Mature Object Space), is presented. It is derived from two previous algorithms, MOS (Mature Object Space), sometimes called the train algorithm, and PMOS (Persistent Mature Object Space). The contribution of DMOS is that it provides the following unique combination of properties for a distributed collector: safety, completeness, non-disruptiveness, incrementality, and scalability. Furthermore, the DMOS collector is non-blocking and does not use global tracing. 1 Introduction Automatic storage management is an essential property of high level programming systems providing an error-free abstraction with which the programmer may manipulate space without regard to the inessential details of physical storage. The abstraction holds only until the store becomes full. Thus it is important for the storage management system to distinguish useful data from garbage, so that the space occupied by the garbag...

Traditional database management systems perform updates-in-place and use logs and periodic checkpointing to efficiently achieve atomicity and durability. In this Thesis we shall present a different method, Shades, for achieving atomicity and durability using a copy-on-write policy instead of updates-in-place. We shall also present index structures and the implementation of Shines, a persistent functional programming language, built on top of Shades. Shades includes real-time generational garbage collection. Real-timeness is achieved by collecting only a small part, a generation, of the database at a time. Contrary to previously presented persistent garbage collection algorithms, Shades has no need to maintain metadata (remembered sets) of intra-generation pointers on disk since the metadata can be reconstructed during recovery. This considerably reduces the amount of disk writing. In conjunction with aggressive commit grouping, efficient index structures, a design specialized to a main memory environment, and a carefully crafted implementation of Shines, we have achieved surprisingly high performance, handsomely beating commercial database management systems.

this paper is to help clear up some confusion about developing software with Modula-3. In particular, we will concentrate on using Modula-3 to write an operating system, which is where our primary experience lies. The key point with which we hope to leave the reader is that there is a fundamental difference between a programming language, and a particular implementation of that language. For example, there are many different versions of the C compiler and its runtime utilities. In the 80's though, BSD UNIX's pcc and libc.a

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.

PMOS is an incremental garbage collector designed specifically to reclaim space in a persistent object store. It is complete in that it will, after a finite number of invocations, reclaim all unreachable storage. PMOS imposes minimum constraints on the order of collection and offers techniques to reduce the I/O traffic induced by the collector. Here we present the first implementation of the PMOS collector called PMOS#1. The collector has been incorporated into the stable heap layer of the generic persistent object store used to support a number of languages including Napier88. Our main design goals are to maintain the independence of the language from the store and to retain the existing store interface. The implementation has been completed and tested using a Napier88 system. The main results of this work show that the PMOS collector is implementable in a persistent store and that it can be built without requiring changes to the language interpreter. Initial performance ...