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Paul Feautrier
Researcher at École normale supérieure de Lyon
Publications - 75
Citations - 4120
Paul Feautrier is an academic researcher from École normale supérieure de Lyon. The author has contributed to research in topics: Automatic parallelization & Polytope model. The author has an hindex of 24, co-authored 75 publications receiving 3992 citations. Previous affiliations of Paul Feautrier include University of Paris & French Institute for Research in Computer Science and Automation.
Papers
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Journal ArticleDOI
Dataflow analysis of array and scalar references
TL;DR: This paper presents an algorithm for analyzing the patterns along which values flow as the execution proceeds, and discusses several applications of the method: conversion of a program to a set of recurrence equations, array and scalar expansion, program verification and parallel program construction.
Journal ArticleDOI
Some efficient solutions to the affine scheduling problem: I. One-dimensional time
TL;DR: This paper deals with the problem of finding closed form schedules as affine or piecewise affine functions of the iteration vector and presents an algorithm which reduces the scheduling problem to a parametric linear program of small size, which can be readily solved by an efficient algorithm.
Journal ArticleDOI
Parametric integer programming
TL;DR: In this paper, the analysis semantique des programs informatiques conduit a la resolution de problemes de programmation parametrique entiere, i.e., the problem of finding a parametrization of a program.
Journal ArticleDOI
Some efficient solutions to the affine scheduling problem. Part II. Multidimensional time
TL;DR: This paper extends the algorithms which were developed in Part I to cases in which there is no affine schedule, i.e. to problems whose parallel complexity is polynomial but not linear, and gives some experimental evidence for the applicability, performances and limitations of the algorithm.
Book ChapterDOI
Automatic Parallelization in the Polytope Model
TL;DR: The aim of this paper is to explain the importance of polytope and polyhedra in automatic parallelization, and shows that the semantics of parallel programs is best described geometrically, as properties of sets of integral points in n-dimensional spaces.