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GTC On-Demand

Presentation
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Abstract:
Learn how NVIDIA's GPUs are used to accelerate unified communications (UC) analytics processing by mathematically classifying UC call flows. We'll discuss how we're leveraging NVIDIA GPU parallelization technology to support classification and baselining of UC call flows, protect UC against fraudulent attacks, and establish predictive UC forecasting models. We'll explain how this allows us to more accurately identify and forecast deviations that may represent malicious use of UC against a baseline of normal traffic.
Learn how NVIDIA's GPUs are used to accelerate unified communications (UC) analytics processing by mathematically classifying UC call flows. We'll discuss how we're leveraging NVIDIA GPU parallelization technology to support classification and baselining of UC call flows, protect UC against fraudulent attacks, and establish predictive UC forecasting models. We'll explain how this allows us to more accurately identify and forecast deviations that may represent malicious use of UC against a baseline of normal traffic.  Back
 
Topics:
Telecommunications
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9385
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Abstract:
Learn how GPUs revolutionize the ability to scale Unified Communications in the cloud. Hear about Ribbon's innovation leveraging the power of the Nvidia GPU provide disruptive scale for simultaneous media processing. Ribbon was able to concurrently process multiple, different audio and video codecs, on a single GPU, with the high fidelity and resolution that its customers demand. See actual test results showing the performance, quality, and substantial cost savings that were achieved. Learn more on how Ribbon's learning curve was accelerated by Nvidia's robust set of tutorials, whitepapers and training, code execution benchmarking and analysis tools, and support from knowledge experts.
Learn how GPUs revolutionize the ability to scale Unified Communications in the cloud. Hear about Ribbon's innovation leveraging the power of the Nvidia GPU provide disruptive scale for simultaneous media processing. Ribbon was able to concurrently process multiple, different audio and video codecs, on a single GPU, with the high fidelity and resolution that its customers demand. See actual test results showing the performance, quality, and substantial cost savings that were achieved. Learn more on how Ribbon's learning curve was accelerated by Nvidia's robust set of tutorials, whitepapers and training, code execution benchmarking and analysis tools, and support from knowledge experts.  Back
 
Topics:
Performance Optimization, Telecommunications, Speech and Language Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8790
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