A transformational approach to parametric accumulated-cost static profiling

Haemmerlé, Remy; López García, Pedro; Liqat, Umer; Klemen, Maximiliano; Gallagher, John y Hermenegildo, Manuel V. (2016). A transformational approach to parametric accumulated-cost static profiling. En: "13th International Symposium on Functional and Logic Programming, FLOPS 2016", 04-06 Mar 2016, Kochi, Japón. ISBN 978-3-319-29604-3. pp. 163-180. https://doi.org/doi.org/10.1007/978-3-319-29604-3_11.

Descripción

Título: A transformational approach to parametric accumulated-cost static profiling
Autor/es:
  • Haemmerlé, Remy
  • López García, Pedro
  • Liqat, Umer
  • Klemen, Maximiliano
  • Gallagher, John
  • Hermenegildo, Manuel V.
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 13th International Symposium on Functional and Logic Programming, FLOPS 2016
Fechas del Evento: 04-06 Mar 2016
Lugar del Evento: Kochi, Japón
Título del Libro: Functional and Logic Programming
Fecha: 2016
ISBN: 978-3-319-29604-3
Volumen: 9613
Materias:
Escuela: E.T.S. de Ingenieros Informáticos (UPM)
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Traditional static resource analyses estimate the total resource usage of a program, without executing it. In this paper we present a novel resource analysis whose aim is instead the static profiling of accumulated cost, i.e., to discover, for selected parts of the program, an estimate or bound of the resource usage accumulated in each of those parts. Traditional resource analyses are parametric in the sense that the results can be functions on input data sizes. Our static profiling is also parametric, i.e., our accumulated cost estimates are also parameterized by input data sizes. Our proposal is based on the concept of cost centers and a program transformation that allows the static inference of functions that return bounds on these accumulated costs depending on input data sizes, for each cost center of interest. Such information is much more useful to the software developer than the traditional resource usage functions, as it allows identifying the parts of a program that should be optimized, because of their greater impact on the total cost of program executions. We also report on our implementation of the proposed technique using the CiaoPP program analysis framework, and provide some experimental results.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
FP7318337ENTRAROSKILDE UNIVERSITETWhole-Systems Energy Transparency
Gobierno de EspañaTIN'12-39391Sin especificarSin especificarStrongSoft project
Comunidad de MadridM141047003N-GREENSSin especificarSin especificar

Más información

ID de Registro: 47609
Identificador DC: http://oa.upm.es/47609/
Identificador OAI: oai:oa.upm.es:47609
Identificador DOI: doi.org/10.1007/978-3-319-29604-3_11
URL Oficial: https://link.springer.com/chapter/10.1007/978-3-319-29604-3_11
Depositado por: Memoria Investigacion
Depositado el: 21 Mar 2018 11:35
Ultima Modificación: 21 Mar 2018 11:35
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