Dynamic memory allocation has been a fundamental part of most computer systems since roughly 1960, and memory allocation is widely considered to be either a solved problem or an insoluble one. In this survey, we describe a variety of memory allocator designs and point out issues relevant to their design and evaluation. We then chronologically survey most of the literature on allocators between 1961 and 1995. (Scores of papers are discussed, in varying detail, and over 150 references are given.) We argue that allocator designs have been unduly restricted by an emphasis on mechanism, rather than policy, while the latter is more important; higher-level strategic issues are still more important, but have not been given much attention. Most theoretical analyses and empirical allocator evaluations to date have relied on very strong assumptions of randomness and independence, but real program behavior exhibits important regularities that must be exploited if allocators are to perform well in practice.

Abstract. We present an analysis of the memory usage for six of the Java programs in the SPECjvm98 benchmark suite. Most of the programs are realworld applications with high demands on the memory system. For each program, we measured as much low level data as possible, including age and size distribution, type distribution, and the overhead of object alignment. Among other things, we found that non-pointer data usually represents more than 50 % of the allocated space for instance objects, that Java objects tend to live longer than objects in Smalltalk or ML, and that they are fairly small. 1

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...

Abstract not found

If a fixed exponentially decreasing probability distribution function is used to model every object’s lifetime, then the age of an object gives no information about its future life expectancy. This radioactive decay model implies there can be no rational basis for deciding which live objects should be promoted to another generation. Yet there remains a rational basis for deciding how many objects to promote, when to collect garbage, and which generations to collect. Analysis of the model leads to a new kind of generational garbage collector whose effectiveness does not depend upon heuristics that predict which objects will live longer than others. This result provides insight into the computational advantages of generational garbage collection, with implications for the management of objects whose life expectancies are difficult to predict. 1

In this paper, we introduce the notion of prolific and non-prolific types, based on the number of instantiated objects of those types. We demonstrate that distinguishing between these types enables a new class of techniques for memory management and data locality, and facilitates the deployment of known techniques. Specifically, we first present a new type-based approach to garbage collection that has similar attributes but lower cost than generational collection. Then we describe the short type pointer technique for reducing memory requirements of objects (data) used by the program. We also discuss techniques to facilitate the recycling of prolific objects and to simplify object co-allocation decisions.

This paper describes a new garbage collection scheme for large persistent object stores that makes efficient use of the disk and main memory. The heap is divided into partitions that are collected independently using information about inter-partition references. We present efficient techniques to maintain this information stably using auxiliary data structures in memory and the log. The result is a scheme that truly preserves the localized and scalable nature of partitioned collection. Remembering

We describe a method of measuring lifetime characteristics of heap objects, and discuss ways in which such quantitative object behaviour measurements can help improve language implementations, especially garbage collection performance. For Standard ML of New Jersey, we find that certain primary aspects of object behaviour are qualitatively the same across benchmark programs, in particular the rapid object decay. We show that the heap-only allocation implementation model is the cause of this similarity. We confirm the weak generational hypothesis for SML/NJ and discuss garbage collector configuration tuning. Our approach is to obtain object statistics directly from program execution, rather than simulation, for reasons of simplicity and speed. Towards this end, we exploit the flexibility of the garbage collector toolkit as a measurement tool. Careful numerical analysis of the acquired data is necessary to arrive at relevant object lifetime measures. This study fills a gap in quantitativ...

Generational collection has improved the efficiency of garbage collection in fast-allocating programs by focusing on collecting young garbage, but has done little to reduce the cost of collecting a heap containing large amounts of older data. A new generational technique, older-first collection, shows promise in its ability to manage older data.

implementations incorporate techniques that restore robustness by effectively disabling older-first collection in cases where degradation occurs, and this dissertation discusses further measures the collectors may take to avoid performance degradation. i I thank my committee members, Mitchell Wand, Rajmohan Rajaraman and Eliot Moss, and particularly my advisor, Will Clinger, for their participation, comments and help. Will Clinger also contributed in many ways over many years to Larceny, my experimental system, most obviously by writing the Twobit compiler for Scheme. The benchmarks used in this dissertation were written or modified by or in other ways contributed to by Henry Baker, Hans Boehm, Bob Boyer, Will Clinger, David Detlefs, John Ellis, Marc Feeley, Richard Gabriel, Pete Kovac, Eugene Luks, and Richard O'Keefe. The work was supported in part by NSF Grant CCR-9629801 and by the College of Computer Science at Northeastern University. The most profound thanks still go to m