On a Hybrid MPI-Pthread Approach for Simplicial Branch-and-Bound

We investigate models that efficiently map branch-and-bound algorithms on a distributed computer architecture using a case of multidimensional Lipschitz Global Optimization. A combination of MPI and Pthreads is studied: MPI for distributed computation (inter-node) and Pthreads for multicore computation (intra-node). That model adapts the algorithm to the characteristics of the architecture at hand with an increasing number of nodes. Dynamic load balancing is performed in intra-node space through dynamic generation of threads. Results show performance improvements compared to OpenMP and MPI versions used in previous work.