February 24, 2011
Although Variety Magazine is not exactly the first place one might expect to find an article on challenges for high-performance computing in the cloud, this week Karen Idelson produced a rich piece exploring how film production companies are thinking about cloud computing—and what limitations some of them see as deal-killers.
Render farms for visual effects and animation studios are working with seriously large datasets--and their HPC infrastructure reflects it. As Idelson stated, “during the making of Avatar, Weta Digital’s render farm was considered the fastest supercomputer in the southern hemisphere.” While one couldn’t expect a deep discussion about LINPACK benchmarks to follow, Idelson’s point is well-taken—production companies invest an extraordinary amount of money in their infrastructure.
But with great computational power comes great cost. Many of the largest effects and animation render farms face power and security bills that are easily in the million dollar range annually.
As a result of the high overhead, some of these production companies are looking to cloud computing to solve their challenges—but there is not necessarily a mass migration. Latency and security issues are paramount to these studios and slowing down their workflow or risking data privacy or protection are not worth the possibility of lessened expense or hassle.
While companies like Warner Bros. have been using the cloud because of the scalability, others see tax, cost and other incentives, including Dreamworks, who outsources their rendering to a New Mexico-based company, Cerelink. Others, like Sony remain unconvinced of the power of the cloud for their core production business due to the latency and security issues.
Full story at Variety
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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04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.