Nvidia Corporation

Prashant Sohani

Hassane S Azar

Niranjan Avadhanam

Vinayak Jayaram Pore

Ravi Kumar Boddeti

Ajit Lalwani

Rudragouda Pharale

In various examples, machine learning of encoding parameter values for a network is performed using a video encoder. Feedback associated with streaming video encoded by a video encoder over a network may be applied to an MLM(s). Using such feedback, the MLM(s) may predict a value(s) of an encoding parameter(s). The video encoder may then use the value to encode subsequent video data for the streaming. By using the video encoder in training, the MLM(s) may learn based on actual encoded parameter values of the video encoder. The MLM(s) may be trained via reinforcement learning based on video encoded by the video encoder. A rewards metric(s) may be used to train the MLM(s) using data generated or applied to the physical network in which the MLM(s) is to be deployed and/or a simulation thereof. Penalty metric(s) (e.g., the quantity of dropped frames) may also be used to train the MLM(s).

Machine learning of encoding parameters for a network using a video encoder

Apparatuses, systems, and techniques for isolating the performance of a quality-of-service (QoS) policy for improved data streaming systems and applications. In at least one embodiment, a metric is determined for a QoS policy used to provide an application session based on a value of at least one characteristic of the application session that reflects an impact of one or more external conditions beyond the control of the QoS policy.

Isolating QoS policy performance for improved data streaming systems and applications

A method includes implementing, through a processor communicatively coupled to a memory and/or a hardware block, a Bilateral Filter (BF) including a spatial filter component and a range filter component, and implementing the spatial filter component with a low-complexity function to allow for focus on the range filter component. The method also includes determining, through the processor, filter tap value(s) related to the range filter component as a function of radiometric distance between a pixel of a video frame and/or an image and other pixels thereof based on a pre-computed corpus of data related to execution of an application in accordance with a filtering requirement of the pixel by the application. Further, the method includes constraining, through the processor, the filter tap value(s) to a form i&#xd7;base based on the BF implementation. i is an integer and base is a floating point base.

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Marharashtra, India

Prashant Sohani