898 results about "Graphical processing unit" patented technology

Architectures and methods for performing big data analytics by providing an integrated storage / processing system containing non-volatile memory devices that form a large, non-volatile memory array and a graphics processing unit (GPU) configured for general purpose (GPGPU) computing. The non-volatile memory array is directly functionally coupled (local) with the GPU and optionally mounted on the same board (on-board) as the GPU.

Exemplary embodiments of methods and apparatuses to dynamically redistribute computational processes in a system that includes a plurality of processing units are described. The power consumption, the performance, and the power / performance value are determined for various computational processes between a plurality of subsystems where each of the subsystems is capable of performing the computational processes. The computational processes are exemplarily graphics rendering process, image processing process, signal processing process, Bayer decoding process, or video decoding process, which can be performed by a central processing unit, a graphics processing units or a digital signal processing unit. In one embodiment, the distribution of computational processes between capable subsystems is based on a power setting, a performance setting, a dynamic setting or a value setting.

A method of registering two images using a graphics processing unit includes providing a pair of images with a first and second image, calculating a gradient of the second image, initializing a displacement field on the grid point domain of the pair of images, generating textures for the first image, the second image, the gradient, and the displacement field, and loading said textures into the graphics processing unit. A pixel buffer is created and initialized with the texture containing the displacement field. The displacement field is updated from the first image, the second image, and the gradient for one or more iterations in one or more rendering passes performed by the graphics processing unit.

A graphics processing unit implemented method for fiber tract mapping from diffusion tensor magnetic resonance imaging data includes providing a diffusion tensor magnetic resonance brain image volume, initializing a set of fiber positions in a 3D set of points, fiber displacements, and a posterior distribution for an updated fiber displacement in terms of the initial displacements and diffusion tensors, randomly sampling a set of updated fiber displacements from said posterior distribution, computing a new set of fiber positions from said initial fiber positions and said updated fiber displacements, wherein a fiber path comprises a set of fiber points connected by successive fiber displacements, accumulating connectivity values in each point of said 3D set of points by additive alpha-blending a scaled value if a fiber path has passed through a point and adding zero if not, and rendering said connectivity values.

A multi-display computer system comprises a host computer system that processes windowed desktop environments for multiple remote displays, multiple users or a combination of the two. For each display and for each frame, the multi-display processor responsively manages each necessary portion of a windowed desktop environment. The necessary portions of the windowed desktop environment are further processed, encoded, and where necessary, transmitted over the network to the remote display for each user. Embodiments integrate the multi-display processor with the graphics processing unit, network controller, main memory controller or a combination of the three. The encoding process is optimized for network traffic and special attention is made to assure that all users have low latency interactive capabilities.

The invention provides improvements in reconstructive imaging of the type in which a volume is reconstructed from a series of measured projection images (or other two-dimensional representations) by utilizing the capabilities of graphics processing units (GPUs). In one aspect, the invention configures a GPU to reconstruct a volume by initializing an estimated density distribution of that volume to arbitrary values in a three-dimensional voxel-based matrix and, then, determining the actual density distribution iteratively by, for each of the measured projections, (a) forward-projecting the estimated volume computationally and comparing the forward-projection with the measured projection, (b) generating a correction term for each pixel in the forward-projection based on that comparison, and (c) back-projecting the correction term for each pixel in the forward-projection onto all voxels of the volume that were mapped into that pixel in the forward-projection.

Methods and systems for leveraging temperature sensors in a portable computing device (“PCD”) are disclosed. The sensors may be placed within the PCD near known thermal energy producing components such as a central processing unit (“CPU”) core, graphical processing unit (“GPU”) core, power management integrated circuit (“PMIC”), power amplifier, etc. The signals generated by the sensors may be monitored and used to trigger drivers running on the processing units. The drivers are operable to cause the reallocation of processing loads associated with a given component's generation of thermal energy, as measured by the sensors. In some embodiments, the processing load reallocation is mapped according to parameters associated with pre-identified thermal load scenarios. In other embodiments, the reallocation occurs in real time, or near real time, according to thermal management solutions generated by a thermal management algorithm that may consider CPU and / or GPU performance specifications along with monitored sensor data.

One embodiment of the invention sets forth a technique for efficiently combining two graphics processing units (“GPUs”) to enable an improved price-performance tradeoff and better scalability relative to prior art multi-GPU designs. Each GPU's memory interface is split into a first part coupling the GPU to its respective frame buffer and a second part coupling the GPU directly to the other GPU, creating an inter-GPU private bus. The private bus enables higher bandwidth communications between the GPUs compared to conventional communications through a PCI Express™ bus. Performance and scalability are further improved through render target interleaving; render-to-texture data duplication; data compression; using variable-length packets in GPU-to-GPU transmissions; using the non-data pins of the frame buffer interfaces to transmit data signals; duplicating vertex data, geometry data and push buffer commands across both GPUs; and performing all geometry processing on each GPU.

The invention provides, in some aspects, a system for rendering images, the system having one or more client digital data processors and a server digital data processor in communications coupling with the one or more client digital data processors, the server digital data processor having one or more graphics processing units. The system additionally comprises a render server module executing on the server digital data processor and in communications coupling with the graphics processing units, where the render server module issues a command in response to a request from a first client digital data processor. The graphics processing units on the server digital data processor simultaneously process image data in response to interleaved commands from (i) the render server module on behalf of the first client digital data processor, and (ii) one or more requests from (a) the render server module on behalf of any of the other client digital data processors, and (b) other functionality on the server digital data processor.

Systems, methods, and computer programs are disclosed for minimizing power consumption in graphics frame processing. One such method comprises: initiating graphics frame processing to be cooperatively performed by a central processing unit (CPU) and a graphics processing unit (GPU); receiving CPU activity data and GPU activity data; determining a set of available dynamic clock and voltage / frequency scaling (DCVS) levels for the GPU and the CPU; and selecting from the set of available DCVS levels an optimal combination of a GPU DCVS level and a CPU DCVS level, based on the CPU and GPU activity data, which minimizes a combined power consumption of the CPU and the GPU during the graphics frame processing.

A method for calculating a lighting function for an object to be rendered using a basis function is provided. The method includes calculating a transfer function approximation of the lighting function through a stream processor. A method for presenting lighting characteristics associated with a display object in real-time and a method for determining secondary illumination features for an object to be displayed are also provided. A computer readable medium and a computing device having a graphics processing unit capable of determining lighting characteristics for an object in real time are also included.

Systems and methods for applying virtual machines to graphics hardware are provided. In various embodiments of the invention, while supervisory code runs on the CPU, the actual graphics work items are run directly on the graphics hardware and the supervisory code is structured as a graphics virtual machine monitor. Application compatibility is retained using virtual machine monitor (VMM) technology to run a first operating system (OS), such as an original OS version, simultaneously with a second OS, such as a new version OS, in separate virtual machines (VMs). VMM technology applied to host processors is extended to graphics processing units (GPUs) to allow hardware access to graphics accelerators, ensuring that legacy applications operate at full performance. The invention also provides methods to make the user experience cosmetically seamless while running multiple applications in different VMs. In other aspects of the invention, by employing VMM technology, the virtualized graphics architecture of the invention is extended to provide trusted services and content protection.