Research Data and the Computing Cloud: NSF/Google and IBM
Research in the Cloud: Providing Cutting Edge Computational Resources to Scientists is an interesting recent post to the Google Research Blog. It provides Googles take on its participation in the National Science Foundation/Google/IBM collaboration within The Cluster Exploratory Program (CluE).
The NSF solicitation for proposals was released last week. To quote from the call:
‘In addition to the widespread societal impact of data-intensive computing, this computational paradigm also promises significant opportunities to stimulate advances in science and engineering research, where large digital data collections are increasingly prevalent. Well-known examples include the Sloan Digital Sky Survey, the Visible Human, the IRIS Seismology Data Base, the Protein Data Bank and the Linguistic Data Consortium, however other valuable data collections or federations of data collections are being assembled on an ongoing basis. In many fields, it is now possible to pose hypotheses and test them by looking in databases of already collected information. Further, the possibility of significant discovery by interconnecting different data sources is extraordinarily appealing. In data-intensive computing, the sheer volume of data is the dominant performance parameter. Storage and computation are co-located, enabling large-scale parallelism over terabytes of data. This scale of computing supports applications specified in high-level programming primitives, where the run-time system manages parallelism and data access. Supporting architectures must be extremely fault-tolerant and exhibit high degrees of reliability and availability.
The Cluster Exploratory (CluE) program has been designed to provide academic researchers with access to massively-scaled, highly-distributed computing resources supported by Google and IBM. While the main focus of the program is the stimulation of research advances in computing, the potential to stimulate simultaneous advances in other fields of science and engineering is also recognized and encouraged.’
It should be interesting to see how this collaboration evolves and the datasets it includes. For more information see the The Cluster Exploratory (CluE) program call text.
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