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A general framework for static profiling of parametric resource usage*

Published online by Cambridge University Press:  14 October 2016

P. LOPEZ-GARCIA Open the ORCID record for P. LOPEZ-GARCIA [Opens in a new window] ,
M. KLEMEN ,
U. LIQAT Open the ORCID record for U. LIQAT [Opens in a new window]  and
M. V. HERMENEGILDO
P. LOPEZ-GARCIA
Affiliation:
IMDEA Software Institute (e-mail: [email protected], [email protected], [email protected], [email protected]) Spanish Council for Scientific Research (CSIC)
M. KLEMEN
Affiliation:
IMDEA Software Institute (e-mail: [email protected], [email protected], [email protected], [email protected])
U. LIQAT
Affiliation:
IMDEA Software Institute (e-mail: [email protected], [email protected], [email protected], [email protected])
M. V. HERMENEGILDO
Affiliation:
IMDEA Software Institute (e-mail: [email protected], [email protected], [email protected], [email protected]) Technical University of Madrid (UPM)
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Abstract

For some applications, standard resource analyses do not provide the information required. Such analyses estimate the total resource usage of a program (without executing it) as functions on input data sizes. However, some applications require knowing how such total resource usage is distributed over selected parts of a program. We propose a novel, general, and flexible framework for setting up cost equations/relations which can be instantiated for performing a wide range of resource usage analyses, including both static profiling and the inference of the standard notion of cost. We extend and generalize standard resource analysis techniques, so that the relations generated include additional Boolean control variables for switching on or off different terms in the relations, as required by the desired resource usage profile. We also instantiate our framework to perform static profiling of accumulated cost (also parameterized by input data sizes). Such information is much more useful to the software developer than the standard notion of cost: it identifies the parts of the program that have the greatest impact on the total program cost, and which therefore should be optimized first. We also report on an implementation of our framework within the CiaoPP system, and its instantiation for accumulated cost, and provide some experimental results. In addition to generality, our new method brings important advantages over our previous approach based on a program transformation, including support for non-deterministic programs, better and easier integration in the compiler, and higher efficiency.

Keywords

Static ProfilingStatic AnalysisResource Usage AnalysisComplexity Analysis
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 16 , Special Issue 5-6: 32nd International Conference on Logic Programming , September 2016 , pp. 849 - 865
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

*

This research has received funding from EU FP7 agreement no 318337 ENTRA, Spanish MINECO TIN2012-39391 StrongSoft and TIN2015-67522-C3-1-R TRACES projects, and the Madrid M141047003 N-GREENS program. Special thanks are due to John Gallagher for many fruitful and inspiring discussions and to the anonymous reviewers for their detailed and useful comments.

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