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

摘要

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.