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Huawei, MapD Partner to Accelerate Data Analytics with GPUs

Clock 9 months ago
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Huawei, MapD Partner to Accelerate Data Analytics with GPUs Image Credit: MapD

Huawei has signed an agreement with big data firm MapD to accelerate the application of GPU-powered data analytics at scale.

The partnership will enhance compatibility and interconnection between Huawei’s FusionServer hardware and the MapD analytics platform, enabling organizations to search and visualize multiple billions of rows of data sets in milliseconds.

Under the terms of the agreement, both parties will commit engineering resources to a joint R&D initiative that will not only improve software and hardware integration, but also increase support for and connection to third-party applications. The teams will create demo environments at Huawei’s headquarters and OpenLab for enterprise solutions, where customers can road-test the solution with their own data.

With the collaboration, Huawei can sell MapD products across the globe and MapD will join Huawei’s solution partnership plan. Huawei will also implement the MapD Core database and MapD Immerse visual analytics client internally on the FusionServer G5500. 

Earlier this month, MapD partnered with Canadian mobile data vendor Tutela Technologies on an analytics platform that provides real-time metrics on mobile network performance and device usage. The GPU-powered platform dubbed Tutela Explorer will combine visualizations with large data sets to help gauge the performance of mobile networks and the devices they support.

Todd Mostak, CEO of MapD Technologies
The sheer scale of many organizations means they create enormous volumes of data in their daily operations, which they then need to analyze. As MapD’s partner, Huawei can now provide a linearly scalable analytics platform which runs natively on their hardware.

Qiu Long, President, IT Server Product Line, Huawei 
We are seeing stronger and stronger demand for real-time data queries, analysis and visualization of hundreds of billions or trillions of rows of machine-generated logs. Achieving ad-hoc data analytics at this scale in real-time is extremely challenging. 

Ray is a news editor at The Fast Mode, bringing with him more than 10 years of experience in the wireless industry.

For tips and feedback, email Ray at ray.sharma(at)thefastmode.com, or reach him on LinkedIn, Facebook 


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