Harnessing the necessary high performance compute power to drive modern biomedical research is a formidable and familiar challenge throughout the life sciences. Modern research-enabling technologies – Next Generation Sequencing (NGS), for example – generate huge datasets that must be processed. Key applications such as genome assembly, genome annotation and molecular modeling can be data-intensive, compute intensive, or both. Underlying high performance computing (HPC) infrastructures must evolve rapidly to keep pace with innovation. And not least, cost pressures constrain both large and small organizations alike. In such a demanding and dynamic HPC environment, Cloud Computing(i) technologies, whether deployed as a private cloud or in conjunction with a public cloud, represent a powerful approach to managing technical computing resources. By breaking down internal compute silos, by masking underlying HPC complexity to the scientist-clinician researcher user community, and by providing transparency and control to IT managers, cloud computing strategies and tools help organizations of all sizes effectively manage their HPC assets and growing compute workloads that consume them.
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