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.

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.

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...

Pretenuring is a technique for reducing copying costs in garbage collectors. When pretenuring, the allocator places long-lived objects into regions that the garbage collector will rarely, if ever, collect. We extend previous work on profiling-driven pretenuring as follows. (1) We develop a collector-neutral approach to obtaining object lifetime profile information. We show that our collection of Java programs exhibits a very high degree of homogeneity of object lifetimes at each allocation site. This result is robust with respect to different inputs, and is similar to previous work on ML, but is in contrast to C programs, which require dynamic call chain context information to extract homogeneous lifetimes. Call-site homogeneity considerably simplifies the implementation of pretenuring and makes it more efficient. (2) Our pretenuring advice is neutral with respect to the collector algorithm, and we use it to improve two quite different garbage collectors: a traditional generational collector and an older-first collector. The system is also novel because it classifies and allocates objects into 3 categories: we allocate immortal objects into a permanent region that the collector will never consider, long-lived objects into a region in which the collector placed survivors of the most recent collection, and shortlived objects into the nursery, i.e., the default region. (3) We evaluate pretenuring on Java programs. Our simulation results show that pretenuring significantly reduces collector copying for generational and older-first collectors. 1.

We introduce a new family of connectivity-based garbage collectors (Cbgc) that are based on potential objectconnectivity properties. The key feature of these collectors is that the placement of objects into partitions is determined by performing one of several forms of connectivity analyses on the program. This enables partial garbage collections, as in generational collectors, but without the need for any write barrier.

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Many garbage-cE6zcc systems use a single garbagecrb lecbag algorithmacrit allapplicRz"FRN It has long been known that thisci pro duc poor performanc onapplic# tions forwhic h thatcatz#E6N is not well suited. In some systems,suc h as those thatexec#6 stand-alonectand-a execd-alone an appropriatecppropri foreac happlic"FER ca be selecz" from a pool of availablecblezqS96 and tuned by using profile information. In a study of 20 benc hmarks and several cz99EOz"FS cz99EO with the Marmot optimizing Java-to-native c#qRO#z" for everycyzq#SFO there was at least one benc hmark that would have been at least 15% faster with a more appropriatecpropriat The czqE69Oz" are acO ying cgz9qFqz" a generationalce yingcgzqq6Oqz whic h is cz bined witheac h of 4 di#erent write barriers, and the null c6NN9z"EF whic h allo cloz but neverczq#qRSz A detailed analysis of storage managementc#Nq shows how they vary by applicEq#9 and cz#q9SFz" 1. INTRODUCTION Automatic storage management eliminates a significz t so...

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

hing. The behavior of the IRB on a suite of programs drawn from the Spec92, Spec95, and public domain codes, is measured under a variety of abstract models. Next, a detailed hardware design for the IRB that can be easily integrated into modern CPUs is presented. In this design, the IRB is decomposed into a recurrence recognition unit (RRU) and a prefetch unit (PU). The RRU is tightly coupled to the CPU pipelines, and monitors individual load instructions in executing programs. The PU operates asynchronously with respect to the processor pipelines, and is coupled only to the processor's iii bus interface. This division has two important ramifications. First, it allows the PU to pull ahead of the processor as a program executes. Second, it makes it possible to tune the IRB for processors with varying memory subsystems, simply by redesigning the PU. An early embodiment of the design is evaluated via detailed timing simulation on our benchmark suite. The dissertation concludes by outlini