Qualcomm Incorporated

Dam Backer

Wesley James Holland

Joseph Cheung

Serag Gadelrab

Meghal Varia

Tom Longo

Alexei Vladimirovich Bourd

Hee-Jun Park

Reza Pourreza Shahri

Brian Ellis

Shuaib Uddin Arshad

Roman Larionov

Li He

Vaibhav Rajesh Gandhi

Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel. The apparatus may also decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. Further, the apparatus may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels.

Non-linear filtering for color space conversions

The present disclosure relates to methods and apparatus for graphics processing. The apparatus can obtain at least one input image including a plurality of pixels. Additionally, the apparatus can determine shading information for each of the plurality of pixels in the at least one input image. The apparatus can also determine a shading map based on the determined shading information for each of the plurality of pixels in the at least one input image. In some aspects, the apparatus can generate at least one output image based on the at least one input image and the determined shading map. The apparatus can also enhance a quality of the at least one output image. In some aspects, the quality of the at least one output image can be enhanced based on machine learning. Further, the apparatus can generate the at least one input image including the plurality of pixels.

Methods and apparatus for machine learning rendering

An exemplary method for intelligent compression uses a foveated-compression approach. First, the location of a fixation point within an image frame is determined. Next, the image frame is sectored into two or more sectors such that one of the two or more sectors is designated as a fixation sector and the remaining sectors are designated as foveation sectors. A sector may be defined by one or more tiles within the image frame. The fixation sector includes the particular tile that contains the fixation point and is compressed according to a lossless compression algorithm. The foveation sectors are compressed according to lossy compression algorithms. As the locations of foveation sectors increase in angular distance from the location of the fixation sector, a compression factor may be increased.

System and method for foveated compression of image frames in a system on a chip

Methods and devices for managing data flows for concurrent multimedia applications executing on a device including a SoC, in response to determining that a temperature or power consumption exceeds a threshold are disclosed. A lowest priority data flow may be identified. A data flow path associated with the identified lowest priority data flow may be traced. A multimedia parameter of any hardware module along the data flow path may be reduced. When the temperature or power consumption no longer exceeds the threshold, a highest priority data flow among the multimedia applications that has had the multimedia parameter reduced may be identified. A data flow path for a data flow associated with the identified highest priority data flow may be traced. The multimedia parameter may be restored to an original value along the traced data flow path for the data flow associated with the identified highest priority data flow.

Method, devices and systems for dynamic multimedia data flow control for thermal power budgeting

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Dam Backer