International audienceThis paper presents a detailed analysis of the scalability and parallelization of local search algorithms for the Satisfiability problem. We propose a framework to estimate the parallel performance of a given algorithm by analyzing the runtime behavior of its sequential version. Indeed, by approximating the runtime distribution of the sequential process with statistical methods, the runtime behavior of the parallel process can be predicted by a model based on order statistics. We apply this approach to study the parallel performance of two SAT local search solvers, namely Sparrow and CCASAT, and compare the predicted performances to the results of an actual experimentation on parallel hardware up to 384 cores. We show ...
International audienceWe propose a probabilistic model for the parallel execution of Las Vegas algor...
International audienceWe address the issue of parallelizing constraint solvers based on local search...
International audienceWe present a parallel implementation of a constraint-based local search algori...
International audienceThis paper presents a detailed analysis of the scalability and par-allelizatio...
ICTAI 2016: 28th International Conference on Tools with Artificial Intelligence, San Jose, Californi...
In cloud systems, computation time can be rented by the hour and for a given number of processors. T...
We show how to exploit the 32/64 bit architecture of modern computers to accelerate some of the algo...
AbstractStochastic local search (SLS) algorithms have been successfully applied to hard combinatoria...
Stochastic local search (SLS) algorithms have been successfully applied to hard combinatorial proble...
We present a parallel implementation of a constraint-based local search algorithm and investigate it...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algori...
Local search metaheuristics are a recognized means of solving hard com- binatorial problems. Over th...
International audienceIn this work, our objective is to study the impact of knowledge sharing on the...
Combinatorial optimisation problems are an important and well-studied class of problems, with applic...
AbstractLocal search is widely used for solving the propositional satisfiability problem. Papadimitr...
International audienceWe propose a probabilistic model for the parallel execution of Las Vegas algor...
International audienceWe address the issue of parallelizing constraint solvers based on local search...
International audienceWe present a parallel implementation of a constraint-based local search algori...
International audienceThis paper presents a detailed analysis of the scalability and par-allelizatio...
ICTAI 2016: 28th International Conference on Tools with Artificial Intelligence, San Jose, Californi...
In cloud systems, computation time can be rented by the hour and for a given number of processors. T...
We show how to exploit the 32/64 bit architecture of modern computers to accelerate some of the algo...
AbstractStochastic local search (SLS) algorithms have been successfully applied to hard combinatoria...
Stochastic local search (SLS) algorithms have been successfully applied to hard combinatorial proble...
We present a parallel implementation of a constraint-based local search algorithm and investigate it...
Abstract. Machine learning can be utilized to build models that predict the runtime of search algori...
Local search metaheuristics are a recognized means of solving hard com- binatorial problems. Over th...
International audienceIn this work, our objective is to study the impact of knowledge sharing on the...
Combinatorial optimisation problems are an important and well-studied class of problems, with applic...
AbstractLocal search is widely used for solving the propositional satisfiability problem. Papadimitr...
International audienceWe propose a probabilistic model for the parallel execution of Las Vegas algor...
International audienceWe address the issue of parallelizing constraint solvers based on local search...
International audienceWe present a parallel implementation of a constraint-based local search algori...