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Empirical measurements of six allocation-intensive C programs

Empirical measurements of six allocation-intensive C programs 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 high-performance 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 statistics that are publically available on the internet. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGPLAN Notices Association for Computing Machinery

Empirical measurements of six allocation-intensive C programs

ACM SIGPLAN Notices , Volume 27 (12) – Dec 1, 1992

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Publisher
Association for Computing Machinery
Copyright
Copyright © 1992 by ACM Inc.
ISSN
0362-1340
DOI
10.1145/142181.142200
Publisher site
See Article on Publisher Site

Abstract

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 high-performance 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 statistics that are publically available on the internet.

Journal

ACM SIGPLAN NoticesAssociation for Computing Machinery

Published: Dec 1, 1992

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