August 07, 2012
Datacastle RED available to Microsoft's Windows Azure customers and ecosystem; Datacastle selects Windows Azure as preferred public cloud provider
SEATTLE, Aug. 7 — Datacastle, a market leader for protecting enterprises from mobile data loss and data breaches, today announced a cloud services relationship with Microsoft Corp. Datacastle has selected Windows Azure as its preferred public cloud environment. In addition, Datacastle RED will be available to its Windows Azure customers and ecosystem.
"We have worked with Microsoft since Windows Azure's inception. We have found Windows Azure to be the best public cloud platform for Datacastle RED in terms of operations, scalability, capability richness, and cost-effectiveness," said Ron Faith, president and CEO of Datacastle. "With Datacastle RED on Windows Azure, our partners and customers can securely and cost-effectively provide continuous endpoint backup, mobile data security, and anytime, anywhere remote data access from a secure, scalable operating environment."
"Enterprises are demanding secure, scalable, and cost-effective cloud-based solutions that complement their existing IT investments," said Bill Hamilton, Director, Windows Azure, Microsoft. "Windows Azure and Datacastle RED help meet these enterprise-class requirements."
Many of Datacastle's global network of OEM partners already run and operate Datacastle RED on Windows Azure today.
Datacastle RED on Windows Azure is available worldwide today. Special Datacastle RED licenses are being made available for existing Windows Azure enterprise customers and ecosystem. For more information call 425.996.9684 or email firstname.lastname@example.org.
Datacastle protects enterprises from mobile data loss and data breach with simplified and scalable endpoint backup and data protection. The company's Datacastle RED product provides secure and auditable access to enterprise data on critical devices, anytime, anywhere. Profiled in Gartner's Hype Cycle for Storage Technologies, 2012, Datacastle RED is available through a global network of partners. To learn more about Datacastle RED, visit http://www.datacastlered.com, follow us on Twitter @Datacastle, or call 425-996-9684.
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.
May 23, 2013 |
The study of climate change is one of those scientific problems where it is almost essential to model the entire Earth to attain accurate results and make worthwhile predictions. In an attempt to make climate science more accessible to smaller research facilities, NASA introduced what they call ‘Climate in a Box,’ a system they note acts as a desktop supercomputer.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
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