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Cloud computing has evolved in the commercial space to support highly asynchronous web 2.0 applications. Scientific computing has traditionally been supported by centralized federally funded supercomputing centers and grid resources with a focus on bulk-synchronous compute and data-intensive applications. The scientific computing community has shown increasing interest in exploring cloud computing to serve e-Science applications, with the idea of taking advantage of some of its features such as customizable environments and on-demand resources. Magellan, a recently funded cloud computing project is investigating how cloud computing can serve the needs of mid-range computing and future data-intensive scientific workloads. This paper summarizes the application requirements and business model needed to support the requirements of both existing and emerging science applications, as learned from the early experiences on Magellan and commercial cloud environments. We provide an overview of the capabilities of leading cloud offerings and identify the existent gaps and challenges. Finally, we discuss how the existing cloud software stack may be evolved to better meet e-Science needs, along with the implications for resource providers and middleware developers.
Ramakrishnan et al. (Thu,) studied this question.
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