This paper presents two techniques for improving garbage collection performance: generational stack collection and profile-driven pretenuring. The first is applicable to stackbased implementations of functional languages while the second is useful for any generational collector. We have implemented both techniques in a generational collector used by the TIL compiler (Tarditi, Morrisett, Cheng, Stone, Harper, and Lee 1996), and have observed decreases in garbage collection times of as much as 70% and 30%, respectively. Functional languages encourage the use of recursion which can lead to a long chain of activation records. When a collection occurs, these activation records must be scanned for roots. We show that scanning many activation records can take so long as to become the dominant cost of garbage collection. However, most deep stacks unwind very infrequently, so most of the root information obtained from the stack remains unchanged across successive garbage collections. Generatio...

We present the design and implementation of a new garbage collection framework that significantly generalizes existing copying collectors. The Beltway framework exploits and separates object age and incrementality. It groups objects in one or more increments on queues called belts, collects belts independently, and collects increments on a belt in first-in-first-out order. We show that Beltway configurations, selected by command line options, act and perform the same as semi-space, generational, and older-first collectors, and encompass all previous copying collectors of which we are aware.

We present a programming language, model, and logic appropriate for implementing and reasoning about a memory management system. We then state what is meant by correctness of a copying garbage collector, and employ a variant of the novel separation logics [18, 23] to formally specify partial correctness of Cheney's copying garbage collector [8]. Finally, we prove that our implementation of Cheney's algorithm meets its specification, using the logic we have given, and auxiliary variables [19].

We describe a memory management toolkit for language implementors. It offers efficient and flexible generation scavenging garbage collection. In addition to providing a core of languageindependent algorithms and data structures, the toolkit includes auxiliary components that ease implementation of garbage collection for programming languages. We have detailed designs for Smalltalk and Modula-3 and are confident the toolkit can be used with a wide variety of languages. The toolkit approach is itself novel, and our design includes a number of additional innovations in flexibility, efficiency, accuracy, and cooperation between the compiler and the collector. This project is supported by National Science Foundation Grant CCR-8658074, and by Digital Equipment Corporation, GTE Laboratories, and Apple Computer. 1 Introduction As part of an ongoing effort to implement Persistent Smalltalk and Persistent Modula-3, we have designed a high performance garbage collector toolkit that can be us...

Abstract The trends in software development are towards larger programs, more complex programs, and more use of programs as "component software. " These trends mean that the features of modern programming languages are becoming more important than ever before. Programming languages need to have features such as strong typing, a module system, polymorphism, automatic storage management, and higher-order functions. In short, modern programming languages are becoming more important than ever before.

Garbage collection can be done in vector mode on supercomputers like the Cray-2 and the Cyber 205. Both copying collection and mark-and-sweep can be expressed as breadth-first searches in which the "queue" can be processed in parallel. We have designed a copying garbage collector whose inner loop works entirely in vector mode. We give performance measurements of the algorithm as implemented for Lisp CONS cells on the Cyber 205. Vector-mode garbage collection performs up to 9 times faster than scalar-mode collection --- a worthwhile improvement. - 1. Automatic garbage collection on vector supercomputers Languages like Lisp with dynamic storage allocation and automatic garbage collection are increasingly being used on vector supercomputers. Implementations of Lisp have been done for Cray supercomputers [1], and fully supported supercomputer Lisp environments will soon be available (e.g. Common Lisp provided by Cray Research and Franz, Inc.)[2]. This is a natural development. Languages ...

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.

Generational garbage collectors are able to achieve very small pause times by concentrating on the youngest (most recently allocated) objects when collecting, since objects have been observed to die young in many systems. Generational collectors must keep track of all pointers from older to younger generations, by "monitoring " all stores into the heap. This write barrier has been implemented in a number of ways, varying essentially in the granularity of the information observed and stored. Here we examine a range of write barrier implementations and evaluate their relative performance within a generation scavenging garbage collector for Smalltalk. 1 Introduction Generational collectors achieve short collection pause times partly because they separate heap-allocated objects into two or more generations and do not process all generations during each collection. Empirical studies have shown that in many programs most objects die young, so separating objects by age and focusing collecti...

This paper describes a memory discipline that combines region-based memory management and copying garbage collection by extending Cheney's copying garbage collection algorithm to work with regions. The paper presents empirical evidence that region inference very significantly reduces the number of garbage collections; and evidence that the fastest execution is obtained by using regions alone, without garbage collection.