Parallelizing Nested Loops with Approximation of Distance Vectors: A Survey

Alain Darte 1, * Frédéric Vivien 1
* Auteur correspondant
1 REMAP - Regularity and massive parallel computing
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
Abstract : In this paper, we compare three nested loops parallelization algorithms (Allen and Kennedy's algorithm, Wolf and Lam's algorithm and Darte and Vivien's algorithm) that use different representations of distance vectors as input. We study the optimality of each with respect to the dependence analysis it uses. We propose well-chosen examples that illustrate the power and limitations of the three algorithms. This study identifies which algorithm is the most suitable for a given representation of distance vectors.
Type de document :
Article dans une revue
Parallel Processing Letters, World Scientific Publishing, 1997, 7 (2), pp.133--144. 〈10.1142/S0129626497000152〉
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Soumis le : lundi 2 septembre 2013 - 16:19:10
Dernière modification le : vendredi 20 avril 2018 - 15:44:24

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Alain Darte, Frédéric Vivien. Parallelizing Nested Loops with Approximation of Distance Vectors: A Survey. Parallel Processing Letters, World Scientific Publishing, 1997, 7 (2), pp.133--144. 〈10.1142/S0129626497000152〉. 〈hal-00856889〉

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