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IBM unveils Openpower servers to manage big data faster

Capable of analysing data 50 times faster than the latest Intel x86 systems
Thu Apr 24 2014, 11:06
IBM logo in black with white text

BIG BLUE IBM has announced Power servers built on an open server standard that enable data centres to manage big data much faster.

Based upon the Openpower Foundation standard, the servers are powered by IBM's Power8 processors, each of which measures one square inch and has more than four billion transistors and more than 11 miles of copper circuit traces.

Designed for what the firm calls "an era of big data", the IBM Power8 servers are built from the ground up to deal with "the explosion of data generated each day", IBM said.

IBM SVP of the systems and technology group Tom Rosamilia said, "This is the first truly disruptive advancement in high-end server technology in decades, with radical technology changes and the full support of an open server ecosystem that will lead our clients into this world of massive data volumes and complexity.

"There no longer is a one size fits all approach to scale out a data centre. With our membership in the Openpower Foundation, IBM's Power8 processor will become a catalyst for emerging applications and an open innovation platform."

Alongside its new Power servers, IBM also announced what it called three new Power Systems solutions to "tackle the heavy requirements of today's big data".

Taking advantage of the Power8 servers together with the company's big data and analytics software, the IBM Solution for BLU Acceleration, IBM Solution for Analytics and IBM Solution for Hadoop are designed to deliver quick insights from both structured and unstructured data.

"For example, the new IBM Solution for Analytics provides speed of insight for today's data driven analytical, computational and cognitive workloads through integration with Cognos, SPSS and DB2 with BLU Acceleration," IBM explained, claiming that its Power Systems are capable of analysing data 50 times faster than the latest x86 systems, reducing run times. µ

 

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