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

... 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...

Dynamic storage allocation is an important part of a large class of computer programs written in C and C++. High-performance algorithms for dynamic storage allocation have been, and will continue to be, of considerable interest. This paper presents detailed measurements of the cost of dynamic storage allocation in 11 diverse C and C++ programs using five very different dynamic storage allocation implementations, including a conservative garbage collection algorithm. Four of the allocator implementations measured are publicly-available on the Internet. A number of the programs used in these measurements are also available on the Internet to facilitate further research in dynamic storage allocation. Finally, the data presented in this paper is an abbreviated version of more extensive statistics that are also publically-available on the Internet.

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...