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March 20, 2013

Shazam, and Cortexica Benefit from NVIDIA GPUs

By Meenakshi Shankar, TMCnet Contributor

NVIDIA, a company specializing in visual computing technologies, announced recently that Shazam, (News - Alert) and Cortexica are the latest to join the list of companies who rely on NVIDIA Tesla GPU accelerators for areas as diverse as audio search, big data analytics and image recognition.

Top enterprise and mobile application companies are using GPUs to tackle big data analytics and advanced search for both consumer and commercial applications. Shazam (News - Alert), and Cortexica are at the forefront of companies expanding the use of GPUs beyond their traditional role of processing massive data sets and complex algorithms for high performance computing science and engineering applications.

Shazam, one of the top five music applications in the Apple App Store and Google (News - Alert) Play store -- uses GPU accelerators to rapidly search and identify songs from its 27 million track database. By accelerating the search and matching process, Tesla GPUs enable Shazam to maintain a low-cost server infrastructure that scales with the company's dramatic growth. uses GPU accelerators to help major international brands monitor and analyze more than 500 million daily tweets for brand, product, and service and support issues. NVIDIA (News - Alert) CUDA GPUs enable to deliver insights almost10 minutes faster than a comparable CPU-based system.

Cortexica's mobile application makes it effortless for consumers to find and purchase goods they like. With GPU accelerators, Cortexica can run complex visual object recognition algorithms on a modest amount of server hardware to enable real-time searches against a database of millions of images.

"GPU accelerators provide great value to applications with lots of data or computations," Sumit Gupta, general manager of the Tesla accelerated computing business at NVIDIA said in a statement.

"A growing number of applications that provide mobile service and social media analysis have both. And that's prompting their providers to turn to GPU accelerators as they scale up their infrastructure to meet growing demand," Gupta added.

GPU computing has quickly become an industry standard, enjoyed by millions of users worldwide and adopted by virtually all computing vendors. All NVIDIA GPUs—GeForce, Quadro, and Tesla support GPU computing and the CUDA parallel programming model. Tesla GPUs are designed from the ground-up to accelerate scientific and technical computing workloads. The latest generation of Tesla GPUs based on NVIDIA Kepler, the world's fastest and most efficient high performance computing architecture.

Edited by Brooke Neuman

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