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, I evaluate the costs of different dynamic storage management algorithms, including domain-specific allocators, widelyused general-purpose allocators, and a publicly available conservative garbage collection algorithm. Surprisingly, I find that programmer enhancements often have little effect on program performance. I also find that the true cost of conservative garbage collection is not the CPU overhead, but the memory system overhead of the algorithm. I conclude that conservative garbage collection is a promising alternative to explicit storage management and that the performance of conservative collection is likely to improve in the future. C programmers should now seriously consider using conservative garbage collection instead of explicitly calling free in programs they write

This paper presents a comprehensive design overview of the SunOS 5.4 kernel memory allocator. This allocator is based on a set of object-caching primitives that reduce the cost of allocating complex objects by retaining their state between uses. These same primitives prove equally effective for managing stateless memory (e.g. data pages and temporary buffers) because they are space-efficient and fast. The allocator’s object caches respond dynamically to global memory pressure, and employ an objectcoloring scheme that improves the system’s overall cache utilization and bus balance. The allocator also has several statistical and debugging features that can detect a wide range of problems throughout the system. 1.

... In this paper, we describe a program (CustoMalloc) that synthesizes a memory allocator customized for a specific application. Our experiments show that the synthesized allocators are uniformly faster and more space efficient than the Berkeley UNIX allocator. Constructing a custom allocator requires little programmer effort, usually taking only a few minutes. Experience has shown that the synthesized allocators are not overly sensitive to properties of input sets and the resulting allocators are superior even to domain-specific allocators designed by programmers. Measurements show that synthesized allocators are from two to ten times faster than widelyused allocators

Dynamic memory management is an important part of a large class of computer programs and high-performance algorithms for dynamic memory management have been, and will continue to be, of considerable interest. This paper presents empirical data from a collection of six allocation-intensive C programs. Extensive statistics about the allocation behavior of the programs measured, including the distributions of object sizes, lifetimes, and interarrival times, are presented. This data is valuable for the following reasons: first, the data from these programs can be used to design highperformance algorithms for dynamic memory management. Second, these programs can be used as a benchmark test suite for evaluating and comparing the performance of different dynamic memory management algorithms. Finally, the data presented gives readers greater insight into the storage allocation patterns of a broad range of programs. The data presented in this paper is an abbreviated version of more extensive sta...

Because dynamic memory management is an important part of a large class of computer programs, high-performance algorithms for dynamic memory management have been, and will continue to be, of considerable interest. We evaluate and compare models of the memory allocation behavior in actual programs and investigate how these models can be used to explore the performance of memory management algorithms. These models, if accurate enough, provide an attractive alternative to algorithm evaluation based on trace-driven simulation using actual traces. We explore a range of models of increasing complexity including models that have been used by other researchers. Based on our analysis, we draw three important conclusions. First, a very simple model, which generates a uniform distribution around the mean of observed values, is often quite accurate. Second, two new models we propose show greater accuracy than those previously described in the literature. Finally, none of the models investigated ap...

This report is concerned with the efficient execution of array computation on Distributed Memory Architectures by applying compiler-directed program and data transformations. By translating a sub-set of a single-assignment language, Sisal, into a linear algebraic framework it is possible to transform a program so as to reduce load imbalance and non-local memory access. A new test is presented which allows the construction of transformations to reduce load imbalance. By a new expression of data alignment, transformations to reduce non-local access are derived. A new pre-fetching procedure, which prevents redundant non-local accesses, is presented and forms the basis of a new data partitioning methodology. By applying these transformations in a straightforward manner to some well known scientific programs, it is shown that this approach is competitive with hand-crafted methods. Preface The author graduated from Aston University in 1987 with an upper second B.Sc.(Hons.) in Computationa...