December 10, 2010
Microsoft is again doling out gifts of free time on its Azure cloud platform, this time to Australian researchers at a number of universities and institutions.
The 4 million-hour donation, which is estimated to be in the $3 million range, will allow researchers to use the platform and all support and tools inherent to Azure.
As ZDnet noted, “the Australian National University and National Computation Infrastructure will be using Azure for computational chemistry packages. Researchers at the University of Melbourne and Monash University will work on e-science applications and researchers at the University of Adelaid will be using Azure for a magnetotellurics platform, which provides electromagnetic imaging of the Earth’s subsurface.
As Microsoft’s group director of eXtreme computing, Dennis Gannon said, “science is about sharing information and data with other collaborators and the roll-out of NBN would also provide benefits for using cloud computing in research.”
Microsoft has been on something of a spree in the last year, issuing free time and resources on Azure to research and science groups, often at universities abroad. This is a strategic way to get younger researchers experienced with the platform (which means they might be more likely to use it after the free time is discontinued) but there is no guarantee that, as the cloud ecosystem and available options increase (especially hosted in Australia) researchers will be obligated to use the platform.
Full story at ZDNet
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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