June 21, 2011
Q-Logic’s director of product and solutions marketing, Joe Yaworski, explained to InformationWeek that supercomputers are no longer reserved for the computationally elite. He said “The enterprise market is three times bigger, but HPC is where the growth is.”
Yaworski went on to say that if we take a look at what is going on within the enterprise, it’s all about consolidation, which in his view means moving applications into the cloud. In his view, cloud providers themselves maintain high standards and have to have configurations designed to deal with complex workloads—even more complicated than those in any enterprise datacenter. In other words, “This means a diminished role for the enterprise data center and an enhanced one for HPC.”
Yaworski claims that the idea case to prove his point comes from studios that are no longer investing in their own HPC for CGI and related animation functions. He says in this case, as is true in many other industries, “if there’s a single technology that cuts across all industries, it’s high performance computing.”
Q-Logic has good reason to tout the dual value of HPC and clouds. The company just released its new enhancements within IFS 7.0 which the company says will make it easier for IT to set priorities to important workloads, an issue that is important as HPC makes the move from clusters to systems that are designed to work along a number of virtual machines. As Yaworski said, “A single slow node can slow down an entire cluster because each node waits to get data from all the other nodes…it’s the weakest link.” He says that software to diagnose such bottlenecks by finding weak PCI connections or hardware failures is a key.
Full story at InformationWeek
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).
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