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IBM Linux Servers Designed to Accelerate Artificial Intelligence, Deep Learning

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ibby Angela Guess

A new press release out of the company reports, “IBM today revealed a series of new servers designed to help propel cognitive workloads and to drive greater data center efficiency. Featuring a new chip, the Linux-based lineup incorporates innovations from the OpenPOWER community that deliver higher levels of performance and greater computing efficiency than available on any x86-based server. Collaboratively developed with some of the world’s leading technology companies, the new Power Systems are uniquely designed to propel artificial intelligence, deep learning, high performance data analytics and other compute-heavy workloads, which can help businesses and cloud service providers save money on data center costs.”

The release goes on, “IBM’s new chip and servers are designed to accelerate artificial intelligence, deep learning and advanced analytics. With built-in NVIDIA NVLink technology, the new servers deliver higher levels of performance and greater computing efficiency than available on any x86-based server. The three new systems are an expansion of IBM’s Linux server portfolio comprised of IBM’s specialized line of servers co-developed with fellow members of the OpenPOWER Foundation. The new servers join the Power Systems LC lineup that is designed to outperform x86-based servers on a variety of data-intensive workloads.”

It adds, “Early testing with Tencent, one of the world’s largest Internet service providers based in China, has shown that a large cluster of the new IBM OpenPOWER servers was able to run a data-intensive workload three times faster than its former x86-based infrastructure. Moreover, this result was achieved while reducing the total number of servers used by two-thirds. Given the significant cost benefits of using fewer servers to deliver faster performance, the company is now integrating the new servers into its hyperscale data center for big data workloads.”

Read more at PR Newswire.

Photo credit: IBM

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