September 27, 2010
Dell recently announced that a handful of American universities would be implementing their cloud-ready PowerEdge C6100 high-density rack servers for research in the life and earth sciences and beyond.
According to Vince Kellen, CIO at the University of Kentucky, his institution chose Dell based “on their legacy in working with academia across the globe in HPC and [our] interest in exploring new uses of HPC computing analysis in language arts and sciences.” Kellen went on to note that the cloud-enabled nature of the servers complements his university’s vision to become a top 20 public research university by 2020 as the servers support their “aim to experiment with HPC in the cloud over the next several years.”
Dell has been in the HPC headlines over the past few weeks as it reveals where some implementations of its C-series systems have taken place. The company has been pushing its line of HPC-oriented products since March when the cloud-capable systems were first announced. News that the University of Colorado at Boulder, among others, have adopted their systems helps give Dell’s HPC and technical computing-driven message some added punch.
While the servers are technically “cloud ready” during an interview with Dell in mid-September, there were no HPC cloud use cases that they were able to reveal at NASA (where they are using Dell's new servers) or the string of universities that were tied to their series of announcements. For now, HPC cloud plans for these servers, at least on the public and technical computing level remain in the “ambitions” stage as Kellen noted, but it is now a possibility.
Full story at Campus Technology
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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