November 23, 2010
One of the movements in the vendor space that we’ll likely be seeing more of in coming months includes arrangements to help large-scale customers build with the cloud in mind from the outset, versus helping them find ways to migrate legacy systems to the cloud.
A number of vendors are looking for ways to improve their current, steadfast data center offerings to make them more attractive to enterprises looking to invest in hardware but with the possibility of bursting into the cloud or making use of the private cloud model.
For instance, this week Dell announced strategic partnerships with Joynet, a cloud service and software provider, and Aster Data, a data management and analytics company, to bring their offerings to Dell Data Center Solutions—and to allow an easier on-ramp for companies interesting in deploying the range of cloud computing models.
As Robert J. Mullins at Network Computing noted, “Typical DCS customers are large enterprises running hyperscale data centers that deploy Dell hardware such as its PowerEdge-C servers. DCS delivers Dell Cloud Solutions, introduced in March, that are pre-packaged and tested bundles that are said to be easier to configure, deploy and manage.”
Following an interview with Dell’s general manager of DCS, Roy Guillen, Mullins suggested, “the DCS approach began after Dell heard from customers that it wanted more from the tech giant than just a truckload of servers and desktop computers installed with software. They wanted Dell to help them build a data center that was efficient, resilient and scalable so they could focus on their business rather than worry about managing their IT.”
Full story at NetworkComputing
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.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
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.