Microsoft and Cray to build affordable supercomputer

The new system, the CX1, will be Cray’s lowest cost system ever and will be configured with Windows High Performance Computing (HPC) Server 2008, although it is also certified for Red Hat. The move is part of Microsoft’s plan to beat back the progress of Linux in high end computing.

"Cray sees Microsoft Windows becoming an increasingly important force in the HPC market," said Ian Miller, senior vice president of sales and marketing at Cray.

"We're bringing the power of Cray supercomputing to a much wider range of new users with an affordable and adaptable system that provides incredible value and is easy to install, program and use with a broad array of applications from independent software vendors."

The CX1 has up to 8 nodes and 16 Intel Xeon dual or quad core processors, come with up to 64 GB of memory per node; and provides up to 4 TB of internal storage. Prices range from US$25,000 to over US$60,000.

"IDC research shows that HPC has been one of the highest-growth IT markets during the past five years and the segment for HPC systems priced below US$100,000 is headed for continued growth," said Earl Joseph, IDC's HPC program vice president.

"The Cray HPC brand name and experience, combined with Microsoft's strategy of extending the familiar Windows environment upward to the server level, gives the Cray CX1 solution strong potential for exploiting the anticipated growth of this market segment."

One of the first systems sold has gone to the Laboratory of Neuro Imaging at UCLA. There it is being used to model brain structure and function.

Rico Magsipoc, chief technology officer for the Laboratory of Neuro Imaging said: "The work that we do in brain research is computationally intensive but will ultimately have a huge impact on our understanding of the relationship between brain structure and function, in both health and disease.”

“Having the power of a Cray supercomputer that is simple and compact is very attractive and necessary, considering the physical constraints we face in our data centers today."

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