HB&B@GRID: an heterogeneous grid-enabled Branch and Bound algorithm

In this paper, we propose an extended version of the hybrid multi-core and GPU-accelerated Branch-and-Bound (B&B) algorithm previously introduced for massively-parallel distributed and heterogeneous environments. The proposed algorithm consists in hierarchically combining two levels of parallelism by (1) dividing the B&B tree exploration among multiple distributed resources using the B&B@GRID approach, and (2) exploring in parallel each sub-tree using an heterogeneous meta-algorithm. Using this portable, heterogeneous and self-adaptive approach allows to achieve high performance.