November 21, 2012
Last week CyrusOne, Dell, and R Systems launched an HPC cloud solution designed to meet the needs of oil and gas companies. The new service is being housed in CyrusOne's "Sky for the Cloud" platform at its West Houston-based colocation facility.
The oil and gas space has long relied on HPC to analyze geological data in order to enhance operational decisions aimed at increasing time to market and improving profitability.
In a November 16 press release, CyrusOne Chief technology Officer Kevin Timmons noted that "Sky for the Cloud creates an ecosystem to efficiently facilitate the generation, analysis, and sharing of all the geophysical data locally and statewide."
As with other cloud systems, the promised benefits are reduced capital and operational expenditures and the ability to easily scale to meet times of peak demand. The cloud model also frees up resources to be spent on the company's main business drivers.
"We see the combination of HPC and cloud technologies as an incredibly powerful solution with tremendous customer benefit," reported Nnamdi Orakwue, vice president of Dell Cloud. "Customers who need immediate, high-performing computing solutions for shorter time frames can quickly realize revenue opportunities. Dell continues to invest in cloud enabling solutions to help our customers achieve faster business results."
Dell and R Systems are operating under a "project partner" alliance to offer their cloud service for both short and longer-term contracts that span anywhere from one day to one year. They say that the CyrusOne datacenter will help them achieve a high degree of performance, reliability and availability. Sky for the Cloud was designed for optimum power usage effectiveness (PUE) and the facility's 2N architecture is said to enable the highest degree of power redundancy.
Although the HPC cloud will initially focus on the needs of the oil and gas industry, the partners plan to support complex workloads from other industries as well, such as finance, healthcare, life sciences, manufacturing and media.
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.