Hansen's algorithm for verified continuous global optimization is based on interval arithmetic. It is of the Branch&Bound type. Our proposal for the parallelization of Hansen's algorithm consists in creating a lightweight process or thread to explore each subinterval and in beginning its execution immediately after its creation. This strategy provides a high level of speculation and enables to virtualize the architecture. The implementation of this parallel algorithm is based on the parallel execution support PM2 for the handling of threads at a low cost and on the PROFIL/BIAS interval library. Preliminary experimental results exhibit superlinear speed-ups.