Abstract: Techniques are described for reordering commands to improve the speed at which at least one command stream may execute. Prior to distributing commands in the at least one command stream to multiple pipelines, a multimedia processor analyzes any inter-pipeline dependencies and determines the current execution state of the pipelines. The processor may, based on this information, reorder the at least one command stream by prioritizing commands that lack any current dependencies and therefore may be executed immediately by the appropriate pipeline. Such out of order execution of commands in the at least one command stream may increase the throughput of the multimedia processor by increasing the rate at which the command stream is executed.

Abstract: This disclosure describes techniques for extending the architecture of a general purpose graphics processing unit (GPGPU) with parallel processing units to allow efficient processing of pipeline-based applications. The techniques include configuring local memory buffers connected to parallel processing units operating as stages of a processing pipeline to hold data for transfer between the parallel processing units. The local memory buffers allow on-chip, low-power, direct data transfer between the parallel processing units. The local memory buffers may include hardware-based data flow control mechanisms to enable transfer of data between the parallel processing units. In this way, data may be passed directly from one parallel processing unit to the next parallel processing unit in the processing pipeline via the local memory buffers, in effect transforming the parallel processing units into a series of pipeline stages.

Abstract: This disclosure describes communication techniques that may be used within a multiple-processor computing platform. The techniques may, in some examples, provide software interfaces that may be used to support message passing within a multiple-processor computing platform that initiates tasks using command queues. The techniques may, in additional examples, provide software interfaces that may be used for shared memory inter-processor communication within a multiple-processor computing platform. In further examples, the techniques may provide a graphics processing unit (GPU) that includes hardware for supporting message passing and/or shared memory communication between the GPU and a host CPU.

Abstract: The techniques are generally related to implementing a pipeline topology of a data processing algorithm on a graphics processing unit (GPU). A developer may define the pipeline topology in a platform-independent manner. A processor may receive an indication of the pipeline topology and generate instructions that define the platform-dependent manner in which the pipeline topology is to be implemented on the GPU.

Abstract: The techniques are generally related to management of buffers with a management unit that resides within an integrated circuit that includes a graphics processing unit (GPU). The management unit may ensure proper access to the buffers by the programmable compute units of the GPU to allow the GPU to execute kernels on the programmable compute units in a pipeline fashion.

Abstract: A method includes storing, with a first programmable processor, shared variable data to cache lines of a first cache of the first processor. The method further includes executing, with the first programmable processor, a store-with-release operation, executing, with a second programmable processor, a load-with-acquire operation, and loading, with the second programmable processor, the value of the shared variable data from a cache of the second programmable processor.

Abstract: The techniques described in this disclosure are directed to validating an application that is to be executed on a graphics processing unit (GPU). For example, a validation server device may receive code of the application. The validation server device may provide some level of assurance that the application satisfies one or more performance criteria. In this manner, the probability of a problematic application executing on the device that includes the GPU may be reduced.

Abstract: The techniques described in this disclosure are directed to validating an application that is to be executed on a graphics processing unit (GPU). For example, a validation server device may receive code of the application. The validation server device may provide some level of assurance that the application satisfies one or more performance criteria. In this manner, the probability of a problematic application executing on the device that includes the GPU may be reduced.

Abstract: The techniques described in this disclosure are directed to efficient parallel execution of graphics and non-graphics application on a graphics processing unit (GPU). The GPU may include a plurality of shader cores within a shader processor. The techniques may reserve one or more shader cores to execute the graphics application and reserve one or more other shader cores to execute the non-graphics application. In this manner, the execution of the non-graphics application may not interfere with the execution of the graphics application, and vice-versa.

Abstract: This disclosure describes communication techniques that may be used within a multiple-processor computing platform. The techniques may, in some examples, provide software interfaces that may be used to support message passing within a multiple-processor computing platform that initiates tasks using command queues. The techniques may, in additional examples, provide software interfaces that may be used for shared memory inter-processor communication within a multiple-processor computing platform. In further examples, the techniques may provide a graphics processing unit (GPU) that includes hardware for supporting message passing and/or shared memory communication between the GPU and a host CPU.

Abstract: A graphics processor capable of efficiently performing arithmetic operations and computing elementary functions is described. The graphics processor has at least one arithmetic logic unit (ALU) that can perform arithmetic operations and at least one elementary function unit that can compute elementary functions. The ALU(s) and elementary function unit(s) may be arranged such that they can operate in parallel to improve throughput. The graphics processor may also include fewer elementary function units than ALUs, e.g., four ALUs and a single elementary function unit. The four ALUs may perform an arithmetic operation on (1) four components of an attribute for one pixel or (2) one component of an attribute for four pixels. The single elementary function unit may operate on one component of one pixel at a time. The use of a single elementary function unit may reduce cost while still providing good performance.

Abstract: Methods and apparatuses for accessing data within programmable graphics hardware are provided. According to one aspect, a user inserts special log commands into a software program, which is compiled into instructions for the programmable graphics hardware to execute. The hardware writes data to an external memory during runtime according to a flow control protocol, and the software driver reads the data from the memory to display to the user.

Abstract: A method includes storing, with a first programmable processor, shared variable data to cache lines of a first cache of the first processor. The method further includes executing, with the first programmable processor, a store-with-release operation, executing, with a second programmable processor, a load-with-acquire operation, and loading, with the second programmable processor, the value of the shared variable data from a cache of the second programmable processor.

Abstract: The techniques described in this disclosure are directed to efficient parallel execution of graphics and non-graphics application on a graphics processing unit (GPU). The GPU may include a plurality of shader cores within a shader processor. The techniques may reserve one or more shader cores to execute the graphics application and reserve one or more other shader cores to execute the non-graphics application. In this manner, the execution of the non-graphics application may not interfere with the execution of the graphics application, and vice-versa.

Abstract: The techniques described in this disclosure are directed to validating an application that is to be executed on a graphics processing unit (GPU). For example, a validation server device may receive code of the application. The validation server device may provide some level of assurance that the application satisfies one or more performance criteria. In this manner, the probability of a problematic application executing on the device that includes the GPU may be reduced.

Abstract: A wireless device which performs a first-level compiler packing process and a second-level hardware packing process on varyings. The compiler packing process packs two or more shader variables (varyings or attributes) whose sum of components equals M into a shared M-dimensional (MD) vector register. The hardware packing consecutively packs M components of the shader variables (varyings or attributes) and any remaining variables into a vertex cache or other storage medium.

Abstract: This disclosure describes techniques for removing vertex points during two-dimensional (2D) graphics rendering using three-dimensional (3D) graphics hardware. In accordance with the described techniques one or more vertex points may be removed during 2D graphics rendering using 3D graphics hardware. For example, the techniques may remove redundant vertex points in the display coordinate space by discarding vertex points that have the substantially same positional coordinates in the display coordinate space as a previous vertex point. Alternatively or additionally, the techniques may remove excess vertex points that lie in a straight line. Removing the redundant vertex points or vertex points that lie in a straight line allow for more efficient utilization of the hardware resources of the GPU and increase the speed at which the GPU renders the image for display.

Abstract: This disclosure describes techniques for extending the architecture of a general purpose graphics processing unit (GPGPU) with parallel processing units to allow efficient processing of pipeline-based applications. The techniques include configuring local memory buffers connected to parallel processing units operating as stages of a processing pipeline to hold data for transfer between the parallel processing units. The local memory buffers allow on-chip, low-power, direct data transfer between the parallel processing units. The local memory buffers may include hardware-based data flow control mechanisms to enable transfer of data between the parallel processing units. In this way, data may be passed directly from one parallel processing unit to the next parallel processing unit in the processing pipeline via the local memory buffers, in effect transforming the parallel processing units into a series of pipeline stages.

Abstract: This disclosure describes communication techniques that may be used within a multiple-processor computing platform. The techniques may, in some examples, provide software interfaces that may be used to support message passing within a multiple-processor computing platform that initiates tasks using command queues. The techniques may, in additional examples, provide software interfaces that may be used for shared memory inter-processor communication within a multiple-processor computing platform. In further examples, the techniques may provide a graphics processing unit (GPU) that includes hardware for supporting message passing and/or shared memory communication between the GPU and a host CPU.

Abstract: This disclosure describes communication techniques that may be used within a multiple-processor computing platform. The techniques may, in some examples, provide software interfaces that may be used to support message passing within a multiple-processor computing platform that initiates tasks using command queues. The techniques may, in additional examples, provide software interfaces that may be used for shared memory inter-processor communication within a multiple-processor computing platform. In further examples, the techniques may provide a graphics processing unit (GPU) that includes hardware for supporting message passing and/or shared memory communication between the GPU and a host CPU.