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Microprocessors Want to Tackle Big Data

Intel Xeon E7 V4 targets data analytics opportunities in IoT-driven big data (image courtesy of Intel).

Intel Xeon E7 V4 seeks opportunities in IoT-driven big data (image courtesy of Intel).

The microprocessor industry likes large-scale computing problems. Petascale, exascale projects demand supercomputers, powered by hundreds of thousands of processors. That means sales opportunities for chip makers. In the past, the market for high performance computing (HPC) was confined to university researchers, government institutions, and large enterprises. In the IoT era, however, Big Data may become everybody’s headache.

In the report titled  “IoT in Logistics” (April 2015), coauthors from Cisco and DHL predict, “By 2020 … there will be more than 50 billion devices connected to the Internet. By that time, computers (including PCs, tablets, and smartphones) will represent just 17% of all Internet connections; the other 83% will result from IoT, including wearables and smart-home devices.”

Many believe the anticipated data deluge is simply too complex for the naked eye to process, too voluminous for the current crop of data-management software to handle; therefore, it must be addressed with robust data-mining, pattern-hunting algorithms running on HPC.

This week, when Intel introduced its Intel Xeon E7 V4 product line in Beijing, China, the company identifies the market in its crosshair: “Dramatic growth in the volume and variety of data is bringing unprecedented opportunities for businesses to make new discoveries and to deliver improved services and customer experiences. The key opportunity is turning the massive amount of core business data plus new sources of unstructured data into actionable and timely insights. The Intel Xeon processor E7 v4 family offers robust performance, the industry’s largest memory capacity per socket, advanced reliability, and hardware-enhanced security for real-time analytics so that businesses can rapidly gain actionable insights from massive and complex data sets.”

In her blog post, Jennifer Huffstetler, Intel’s senior director of marketing for data center products, notes, “The payoff for enterprises to embark on this analytics journey can be huge. Research indicates that companies that use data-driven insights are two times more likely to have top quartile financial performance and five times more likely to make decisions faster than their competition—so it is no surprise that many companies are investing in analytics and view it as a mission-critical function. All types of companies are already deploying advanced analytics solutions to be more competitive and create new business opportunities and choosing the Intel Xeon processor family as the foundation.”

In the data sheet on Xeon E7 V4, Intel claims the processors can tackle big data analytics “up to 1.26X faster than the previous generation” (“Unlock the Potential for Timely, Actionable Insights,” Intel). The company writes, “Deep insights produced from big data are reshaping business opportunities, with advanced research, improved products and services, and better customer experiences.”

Along with Intel, GPU maker NVIDIA is also pitching its multi-threaded graphics hardware to the same market. Introducing a new server-class hardware at this year’s GPU Technology Conference, NVIDIA CEO Jen-Hsun Huang said, “[The NVIDIA TESLA P100] is the most advanced hyperscale datacenter GPU ever built.” (Read “NVIDIA GTC 2016: The GPU Wants to Accelerate VR, AI and Big Data Analysis,” April 2016).

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About Kenneth

Kenneth Wong has been a regular contributor to the CAD industry press since 2000, first an an editor, later as a columnist and freelance writer for various publications. During his nine-year tenure, he has closely followed the migration from 2D to 3D, the growth of PLM (product lifecycle management), and the impact of globalization on manufacturing. His writings have appeared in Cadalyst, Computer Graphics World, and Manufacturing Business Technology, among others.

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