Abstract:
This disclosure describes a method and apparatus for performing tessellation in a graphics process. A graphics processing unit may be configured to determine tessellation factors for a first patch of the graphics data, determine, based on the tessellation factors, that a first edge of an outermost ring of the first patch will produce only degenerated sub-primitives, and skip performing tessellation for the first edge. A graphics processing unit may determine that a second edge of the outermost ring of the first patch will produce at least some normal sub-primitives, and perform tessellation for the second edge to produce output primitives.
Abstract:
Techniques are described for stereoscopic view generation. A graphics processing unit (GPU) may combine attribute information for two or more corresponding vertices of corresponding primitives in different views. The GPU may process the combined attributed information to generate graphics data for the stereoscopic view.
Abstract:
This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for runtime optimization of the shader execution flow. A graphics processor may obtain instruction execution data associated with a graphics workload, the instruction execution data including graphics data for a set of shader operations. The graphics processor may configure, at a first iteration, at least one predication value based on the instruction execution data including the graphics data for the set of shader operations. The graphics processor may adjust, at a second iteration, an execution flow of the graphics workload based on the configured at least one predication value, the execution flow of the graphics workload including the set of shader operations. The graphics processor may execute or refrain from executing, at the second iteration, each of the set of shader operations based on the adjusted execution flow of the graphics workload.
Abstract:
Aspects presented herein relate to methods and devices for graphics processing including an apparatus, e.g., a GPU. The apparatus may receive a set of draw call instructions corresponding to a graphics workload, where the set of draw call instructions is associated with at least one run-time parameter. The apparatus may also obtain a first shader program associated with storing data in a system memory and at least one second shader program associated with storing data in a constant memory. Further, the apparatus may execute the first shader program or the at least one second shader program based on whether the at least one run-time parameter is less than or equal to a size of the constant memory. The apparatus may also update or maintain a configuration of a shader processor or a streaming processor based on executing the first shader program or the at least one second shader program.
Abstract:
This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for fast incremental shared constants. In aspects, a CPU may determine/update shared constant data for a first draw call of a plurality of draw calls. The shared constant data, which may correspond to at least one shader, may be updated based on a draw call update for the first draw call. The CPU may communicate the updated shared constant data for the first draw call to a GPU. The GPU may receive, in at least one register, the updated shared constant data from the CPU and configure the at least one register based on the updated shared constant data corresponding to the draw call update of the first draw call of the plurality of draw calls.
Abstract:
Techniques are described for stereoscopic view generation. A graphics processing unit (GPU) may combine attribute information for two or more corresponding vertices of corresponding primitives in different views. The GPU may process the combined attributed information to generate graphics data for the stereoscopic view.
Abstract:
This disclosure describes techniques for executing shader programs in a graphics processing unit (GPU). In some examples, the techniques for executing shader programs may include executing, with a shader unit of a graphics processor, a shader program that performs vertex shader processing and that generates multiple output vertices for each input vertex that is received by the shader program. In further examples, the techniques for executing shader programs may include executing a merged vertex/geometry shader program using a non-replicated mode of execution. The non-replicated mode of execution may involve assigning each of a plurality of primitives to one merged vertex/geometry shader program instance per primitive and causing each of the instances to output a plurality of vertices. In additional examples, the techniques for executing shader programs may include techniques for selecting one of a non-replicated mode and a replicated mode for executing a merged vertex/geometry shader program.
Abstract:
This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for dynamic wave pairing. A graphics processor may allocate one or more GPU workloads to one or more wave slots of a plurality of wave slots. The graphics processor may select a first execution slot of a plurality of execution slots for executing the one or more GPU workloads. The selection may be based on one of a plurality of granularities. The graphics processor may execute, at the selected first execution slot, the one or more GPU workloads at the one of the plurality of granularities.
Abstract:
The present disclosure relates to methods and apparatus for compute processing. For example, disclosed techniques facilitate improving performance of matrix multiplication in streaming processor. Aspects of the present disclosure can execute, with a load control unit, a first load instruction to load a set of input data of an input matrix from a first memory to a second memory. Aspects of the present disclosure can also execute, with the load control unit, a second load instruction to load a set of weight data of a weight matrix from the first memory to the second memory. Additionally, aspects of the present disclosure can perform, with an ALU component, a matrix multiplication operation using the set of input data and the set of weight data to generate an output matrix. Further, aspects of the present disclosure can store the output matrix at a general purpose register accessible to the ALU component.
Abstract:
A graphics processing unit (GPU) utilizes block general purpose registers (bGPRs) to load multiple waves of samples for an instruction group into a processing pipeline and receive processed samples from the pipeline. The GPU acquires a credit for the bGPR for execution of the instruction group for a first wave using a persistent GPR and the bGPR. The GPU refunds the credit upon loading the first wave into the pipeline. The GPU executes a subsequent wave for the instruction group to load samples to the pipeline when at least one credit is available and the pipeline is processing the first wave. The GPU stores an indication of each wave that has been loaded into the pipeline in a queue. The GPU returns samples for a next wave in the queue from the pipeline to the bGPR for further processing when the physical slot of the bGPR is available.