Abstract:
Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.
Abstract:
Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.
Abstract:
Graphics processing unit (GPU) performance and power efficiency is improved using machine learning to tune operating parameters based on performance monitor values and application information. Performance monitor values are processed using machine learning techniques to generate model parameters, which are used by a control unit within the GPU to provide real-time updates to the operating parameters. In one embodiment, a neural network processes the performance monitor values to generate operating parameters in real-time.
Abstract:
One or more copy commands are scheduled for locating one or more pages of data in a local memory of a graphics processing unit (GPU) for more efficient access to the pages of data during rendering. A first processing unit that is coupled to a first GPU receives a notification that an access request count has reached a specified threshold. The first processing unit schedules a copy command to copy the first page of data to a first memory circuit of the first GPU from a second memory circuit of the second GPU. The copy command is included within a GPU command stream.
Abstract:
A system, method, and computer program product are provided for a dynamic display refresh. In use, a state of a display device is identified in which an entirety of an image frame is currently displayed by the display device. In response to the identification of the state, it is determined whether an entirety of a next image frame to be displayed has been rendered to memory. The next image frame is transmitted to the display device for display thereof, when it is determined that the entirety of the next image frame to be displayed has been rendered to the memory. Further, a refresh of the display device is delayed, when it is determined that the entirety of the next image frame to be displayed has not been rendered to the memory.