April 14, 2011
For those who are going to be attending the 4th annual International Conference on Cloud Computing (IEEE Cloud) this year, there’s an item on the session menu that’s worth highlighting. Members of the FutureGrid team aim to shed some much-needed light on how virtualization matters complicate (and in some cases extend) high-performance computing.
This group of researchers will be presenting an in-depth overview of the underlying virtualization technologies that lie at the heart of cloud computing. The authors of the report note in their abstract that even though there are any number of hypervisors with their own distinct features, the advantages and disadvantages of these can be difficult to put into context, especially for users with very specific demands.
The authors also suggest that according to their research, “virtualization sometimes introduces slight performance impacts, depending on the hypervisor type, however the benefits of such technologies are profound and not all virtualization technologies are equal.”
This is a timely topic for what is likely to be a very interested audience. Since one of the most frequently-cited debates about cloud for HPC is the performance overhead caused by the virtualization layer, having the topic fleshed out in the context of the multiple technologies will likely be quite enlightening.
The team behind the effort are from the Pervasive Technology Institute at Indiana University. Among the authors of the paper are Andrew Younge, Robert Henschel, James Brown, Gregor von Laszewski, Judy Qiu and Geoffrey Fox.
The IEEE Cloud 2011 event is taking place this year in Washington D.C. July 4-9. Each year the organizers choose a theme, which for 2011 is “Change We Are Leading” referring to the emphasis on the technical foundations of cloud computing. The event will explore issues related SOA and the hardware and software underpinnings of cloud computing.
Full story at IEEE Cloud 2011
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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