With the increasing numbers of Cloud Service Providers and the migration of the Grids to the Cloud paradigm, it is necessary to be able to leverage these new resources. Moreover, a large class of High Performance Computing (HPC) applications can run these resources without (or with minor) modifications. But using these resources come with the cost of being able to interact with these new resource providers. In this paper we introduce the design of a HPC middleware that is able to use resources coming from an environment that compose of multiple Clouds as well as classical hpc resources. Using the diet middleware, we are able to deploy a large-scale, distributed HPC platform that spans across a large pool of resources aggregated from different providers. Furthermore, we hide to the end users the difficulty and complexity of selecting and using these new resources even when new Cloud Service Providers are added to the pool. Finally, we validate the architecture concept through cosmological simulation RAMSES. Thus we give a comparison of 2 well-known Cloud Computing Software: OpenStack and OpenNebula.