Solving Sat in a Distributed Cloud: A Portfolio Approach
Author:
Ngoko Yanik12, Cérin Christophe2, Trystram Denis3
Affiliation:
1. Department of Research and Development , Qarnot Computing, 40/42 Rue Barbés, Montrouge , France 2. Department of Computer Science , University of Paris 13 , 99, avenue Jean-Baptiste Clément, 93430 Villetaneuse , France 3. Department of Computer Science , University of Grenoble Alpes , 700 avenue Centrale, 38401 Saint Martin, d’Héres cedex , France
Abstract
Abstract
We introduce a new parallel and distributed algorithm for the solution of the satisfiability problem. It is based on an algorithm portfolio and is intended to be used for servicing requests in a distributed cloud. The core of our contribution is the modeling of the optimal resource sharing schedule in parallel executions and the proposition of heuristics for its approximation. For this purpose, we reformulate a computational problem introduced in a prior work. The main assumption is that it is possible to learn optimal resource sharing from traces collected on past executions on a representative set of instances. We show that the learning can be formalized as a set coverage problem. Then we propose to solve it by approximation and dynamic programming algorithms based on classical greedy algorithms for the maximum coverage problem. Finally, we conduct an experimental evaluation for comparing the performance of the various algorithms proposed. The results show that some algorithms become more competitive if we intend to determine the trade-off between their quality and the runtime required for their computation.
Publisher
Walter de Gruyter GmbH
Subject
Applied Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference17 articles.
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