Univa Brings Enterprise Workload Management to ARM-based Servers, Speeding Delivery

MARKHAM, Ontario--(BUSINESS WIRE)-- Univa, the Data Center Automation Company, today announced that its Univa Grid Engine software will support ARM(LON: ARM; Nasdaq: ARMH), the world's leading semiconductor intellectual property (IP) supplier. ARM designs the technology that is at the heart of advanced digital products, from wireless, networking and consumer entertainment solutions to imaging, automotive, security and storage devices. With Univa Grid Engine supporting ARM, dynamic workloads are automatically placed, enabling ARM to perform tasks far more quickly and efficiently. Univa Grid Engine for ARM Beta is available immediately at http://www.univa.com/resources/univa-grid-engine-arm-beta.php.

"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 datacenter services to support mobile and cloud computing, ARM will continue to gain in-roads into the datacenter 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. "As enterprises shift towards highly scalable solutions such as Calxeda, a key enabling technology is intelligent workload management – and we have partnered with Univa to provide our customers with a great solution."

Univa Grid Engine is the industry leading distributed resource management platform that enables 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.