Basin Hopping with synched multi L-BFGS local searches. Parallel implementation in multi-CPU and GPUs

In this work, a technique for improving the convergence properties (speed and reliability) of a non monotonic Basin Hopping algorithm is presented. This modification of Basin Hopping happens to be highly parallelizable and therefore the parallel implementation is shown both for multi-CPU and GPU arc...

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Bibliographic Details
Published inApplied mathematics and computation Vol. 356; pp. 282 - 298
Main Authors Ferreiro-Ferreiro, Ana M., García-Rodríguez, José A., Souto, Luis, Vázquez, Carlos
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.09.2019
Subjects
Basin Hopping
Global optimization
GPU
L-BFGS
Multi-CPU
Parallel
L-BFGS
Global optimization
Parallel
Multi-CPU
Basin Hopping
GPU
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Summary:In this work, a technique for improving the convergence properties (speed and reliability) of a non monotonic Basin Hopping algorithm is presented. This modification of Basin Hopping happens to be highly parallelizable and therefore the parallel implementation is shown both for multi-CPU and GPU architectures. A benchmark of classical global optimization tests is run, focussing in a number of tests in the literature that result to be particularly hard for Basin Hopping.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2019.02.040