Abstract:
Disclosed herein are mobile computing devices that employ compatible updated drivers. In one embodiment, the mobile computing device includes: (1) a processor, (2) a driver library configured to store original drivers and updated drivers for applications on the mobile computing device, and (3) a driver selector configured to determine at least one driver from the original drivers or the updated drivers to use for running one of the applications.
Abstract:
A method for dynamically adjusting a frame buffer resolution, the method comprising calculating a target scaling factor based upon a calculated average frame rate and incrementally changing a current scaling factor to reach the target scaling factor. The method includes calculating the target scaling factor based upon the average frame rate and a current scaling factor. The method includes adjusting a resolution of a frame of data rendered to the frame buffer according to the current scaling factor.
Abstract:
Disclosed herein are methods and systems that provide compatible device drivers to mobile computing devices. In one embodiment, a method of determining compatibility between different versions of device drivers and operating systems of a mobile computing device is disclosed that includes: (1) establishing a test environment employing a current operating system of a mobile computing device, (2) applying an updated driver to the test environment and (3) determining system compatibility of the updated driver with the current operating system employing the test environment, wherein the determining is based on both direct and implied compatibility of the updated driver with the current operating system.
Abstract:
In various examples, a virtualized computing platform for advanced computing operations—including image reconstruction, segmentation, processing, analysis, visualization, and deep learning—may be provided. The platform may allow for inference pipeline customization by selecting, organizing, and adapting constructs of task containers for local, on-premises implementation. Within the task containers, machine learning models generated off-premises may be leveraged and updated for location specific implementation to perform image processing operations. As a result, and using the virtualized computing platform, facilities such as hospitals and clinics may more seamlessly train, deploy, and integrate machine learning models within a production environment for providing informative and actionable medical information to practitioners.
Abstract:
A mobile computing device, a method of operating thereof, a method of manufacturing and an external source for dynamic profile settings for mobile computing devices. In one embodiment, the mobile computing device includes: (1) a settings reservoir configured to store dynamic sets of profile settings and static set of profile settings for the computing device and (2) a profile generator configured to generate coalesced sets of profile settings for applications on the computing device based on the dynamic sets of profiles and the static set of profiles.
Abstract:
System and method of dynamically adjusting a frame buffer resolution. An average frame rate is dynamically computed based on the frame rates with respect to rendering a sequence of previous frames to a frame buffer. The frame rates may vary with the processing load of an associated graphics processor. A target scaling factor for frame buffer resolution is computed based upon the dynamic average frame rate and a desired frame rate. The current scaling factor of frame buffer resolution for rendering a respective frame data of a sequence of frame data to the frame buffer is adjusted incrementally to reach the target scaling factor. Accordingly, frame resolutions for rendering the sequence of frame data to the frame buffer are incrementally adjusted based on corresponding current scaling factors.
Abstract:
Disclosed herein are methods and systems that provide compatible device drivers to mobile computing devices. In one embodiment, a method of determining compatibility between different versions of device drivers and operating systems of a mobile computing device is disclosed that includes: (1) establishing a test environment employing a current operating system of a mobile computing device, (2) applying an updated driver to the test environment and (3) determining system compatibility of the updated driver with the current operating system employing the test environment, wherein the determining is based on both direct and implied compatibility of the updated driver with the current operating system.
Abstract:
Apparatuses, systems, and techniques are presented to analyze objects in images including digital representations of those objects. In at least one embodiment, one or more diagnostic processes are determined based, at least in part, on one or more neural networks used to identify one or more medical images.
Abstract:
Disclosed herein are mobile computing devices that employ compatible updated drivers. In one embodiment, the mobile computing device includes: (1) a processor, (2) a driver library configured to store original drivers and updated drivers for applications on the mobile computing device, and (3) a driver selector configured to determine at least one driver from the original drivers or the updated drivers to use for running one of the applications.
Abstract:
A method for compiling a shader for execution by a graphics processor. The method comprises selecting a shader for execution. A key is computed for the selected shader. A memory is searched for a copy of the computed key. A shader binary stored in the memory is passed to the graphics processor for execution if the copy of the computed key is located in the memory. Otherwise, the shader is compiled to produce the shader binary for execution by the graphics processor and storing the shader binary in the memory. The shader binary is associated with the computed key and the copy of the computed key.