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Traditional HPC (High Performance Computing) clusters are best suited for well-formed calculations. The orderly batch-oriented HPC cluster offers maximal potential for performance per application, but limits resource efficiency and user flexibility. An HPC cloud can host multiple virtual HPC clusters, giving the scientists unprecedented flexibility for research and development. With the proper incentive model, resource efficiency will be automatically maximized. In this context, there are three new challenges. The first is the virtualization overheads. The second is the administrative complexity for scientists to manage the virtual clusters. The third is the programming model. The existing HPC programming models were designed for dedicated homogeneous parallel processors. The HPC cloud is typically heterogeneous and shared.
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