August 26, 2010
The NASA IT Summit Agenda, which included topics ranging from cloud security to space medicine, was fertile ground for discussions about the future direction of government and research technology.
Cloud computing was at the heart of more than a few of the talks presented and Alex Howard, who was live on the scene, was able to spend some time talking about the future of NASA IT with the agency’s CIO, Linda Cureton.
Howard asked Cureton whether NASA’s open source cloud computing initiative known as Nebula was going to be put to use as the platform for other agencies but Cureton had to remind us that NASA is “not in the business of providing IT services…[we] are in the business of being innovative. To create that capabilities for elsewhere in government is difficult, from that perspective, yet it’s something that the government needs.” Still, she emphasized that it was released as open source so that other agencies could build upon it and tailor it to their own needs, stating that this was part of the reason behind opening the code.
Cureton also noted that there is wide concern about the government taking the public cloud route, suggesting, “the things that slow people down with public cloud include IT security and things of that nature. Once an agency understands Nebula, the model can address a lot of risks and concerns the agency might have.”
She goes on to state, perhaps in reference to the “everyman” in the cloud, “if you’re not ready with the Amazon model, it might be a good choice to get your feet wet. The best choice is to start with lower security-class data. When you look at large, transcriptional databases, I ‘m not sure that’s ready for the cloud yet.”
Full story at O'Reilly
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
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