Meta Platforms, Inc.

Prahlad Rao Venkatapuram

Harikrishna Madadi Reddy

Yunqing Chen

Junqiang Lan

Gaurang Chaudhari

Zhao Wang

Srikanth Alaparthi

Baheerathan Anandharengan

A disclosed system may include a hardware distortion data pipeline that may include (1) a quantization module that generates a quantized data set, (2) an inverse quantization module that generates, from the quantized data set, an inverse quantized data set by executing an inverse quantization of the quantized data set, and (3) an inverse transformation module that generates an inversely transformed data set by executing an inverse transformation of the inverse quantized data set. The system may also include a hardware determination pipeline that determines a distortion metric based on the inversely transformed data set and the residual frame data set, and a hardware token rate pipeline that determines, based on the quantized data set, a token rate for an encoding of the residual frame data set via a video encoding pipeline. Various other methods, systems, and computer-readable media are also disclosed.

Hardware pipelines for rate-distortion optimization (RDO) that support multiple codecs

A system for calculating token rates for video encoding includes a plurality of different probability lookup tables implemented in hardware, wherein each of the probability lookup tables specifically corresponds to a different prediction mode of a video codec. The system includes an application-specific integrated circuit compute unit. For each candidate prediction mode among the different prediction modes, the application-specific integrated circuit is configured to determine a rate distortion cost (RD Cost) for a video. The application-specific integrated circuit is configured to select one of the plurality of different probability lookup tables that corresponds to the candidate prediction mode and use the selected one of the plurality of different probability lookup tables to calculate a corresponding token rate for the candidate prediction mode. The application-specific integrated circuit is configured to encode the video using a selected one of the different prediction modes determined based on the determined rate distortion costs.

Hardware optimization of rate calculation in rate distortion optimization for video encoding

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Saratoga, CA, United States of America

Prahlad Rao Venkatapuram