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US Data Centers Running On British Semiconductor Design


Data center automation player Univa has confirmed that its Grid Engine software will now support semiconductor intellectual property (IP) from ARM. With Univa Grid Engine supporting ARM, dynamic workloads are automatically placed, which enables ARM to perform tasks far more quickly and efficiently.

NOTE: United Kingdom-based ARM Holdings is responsible for producing the ARM microprocessor architecture built upon RISC-based computing technologies. ARM designs technology at the heart of advanced digital products from wireless, networking, and consumer entertainment solutions to imaging, automotive, security, and storage devices.

"Large enterprise users have become increasingly interested in using ARM-based chips in the data center as the focus shifts from performance to making their servers more energy efficient," said Fritz Ferstl, Univa CTO. "ARM-based servers support multiple use cases in the modern data center as part of a larger trend toward matching the server hardware to the workload. Univa Grid Engine, the leading intelligent workload management solution in the enterprise, excels at automating the placement of dynamic workloads across all architectures from Intel x86_64, Intel Xeon Phi, NVIDIA GPGPUs, and now ARM-based resources."

"Driven by the demand for new data center services to support mobile and cloud computing, ARM will continue to gain in-roads into the data center server market because of the low-power and energy efficient design of SOC's based on ARM's technology", said Karl Freund, VP Marketing at Calxeda, a start-up company that aims to provide ARM-based computers for the server market.

Freund suggest that as enterprises shift towards highly scalable solutions (such as his own firm), a key enabling technology is intelligent workload management.

Univa Grid Engine is the industry-leading distributed resource management platform to enable shared infrastructures under multiple workloads including Hadoop, a big data software framework that supports data-intensive distributed applications. Sharing the infrastructure allows enterprises to more efficiently and rapidly deploy and to operationalize a mission-critical Hadoop application.


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