Affiliation:
1. University Computing Center Graduate Research Center University of Massachusetts Amherst, Mass.
Abstract
This paper describes a study of the performance of APL. The study was carried out by placing code in an existing APL interpreter (APLUM running on a CDC CYBER 175 computer) to monitor the distribution of data types, element counts, and ranks of arrays. The effect of reference counts on data blocks was also monitored. Although the results of the study may not be surprising, they are very interesting. For example, it turns out that nearly half of all allocations of data are made for scalars or one-element vectors, and that although the over-all average number of elements in APL arrays is 30, most users achieve average element counts of around 10. From these figures, it can be shown that set-up time dominates the execution of APL expressions.
Publisher
Association for Computing Machinery (ACM)
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