Abstract: Systems, methods, and techniques utilize reinforcement learning to efficiently schedule a sequence of jobs for execution by one or more processing threads. A first sequence of execution jobs associated with rendering a target frame of a sequence of frames is received. One or more reward metrics related to rendering the target frame are selected. A modified sequence of execution jobs for rendering the target frame is generated, such as by reordering the first sequence of execution jobs. The modified sequence is evaluated with respect to the selected reward metric(s); and rendering the target frame is initiated based at least in part on the evaluating of the modified sequence with respect to the one or more selected reward metric(s).

Abstract: A first frame of a video stream is obtained. The first frame is defined by a plurality of pixels associated with a set of color data. A determination is made that a pixel of the plurality of pixels comprises high-frequency information. Responsive to the determination that the pixel comprises high-frequency information, a pixel lock is generated for the pixel such that color data associated with the pixel is maintained during a color accumulation process for at least one of the first frame or a second frame of the video stream that is subsequent to the first frame.

Abstract: A first frame of a video stream rendered at a first resolution is obtained. A second frame of the video stream upscaled to a second higher resolution is also obtained. The first plurality of pixels is upscaled to the second resolution. The upsampling generates upsampled color data for the upsampled first plurality of pixels. The upsampled color data is accumulated with a second set of color data associated with a second plurality of pixels defining the second frame to generate final color data for the upsampled first plurality of pixels. Color data of the second set of color data associated with a pixel lock contributes more to the final color data than corresponding color data of the upsampled color data. The upsampled first plurality of pixels is stored with the final color data as an upscaled frame representing the first frame at the second resolution.

Abstract: Systems, methods, and techniques utilize reinforcement learning to efficiently schedule a sequence of jobs for execution by one or more processing threads. A first sequence of execution jobs associated with rendering a target frame of a sequence of frames is received. One or more reward metrics related to rendering the target frame are selected. A modified sequence of execution jobs for rendering the target frame is generated, such as by reordering the first sequence of execution jobs. The modified sequence is evaluated with respect to the selected reward metric(s); and rendering the target frame is initiated based at least in part on the evaluating of the modified sequence with respect to the one or more selected reward metric(s).