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: 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: Example techniques are described for generating graphics content by obtaining texture operation instructions corresponding to a texture operation, in response to determining at least one of insufficient general purpose register space is available for the texture operation or insufficient wave slots are available for the texture operation, generating an indication that the texture operation corresponds to a deferred wave, executing the texture operation, sending, to a texture processor, initial texture sample instructions corresponding to the texture operation that was executed, and receiving texture mapped data corresponding to the initial texture sample instructions.

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: Example techniques are described for generating graphics content by obtaining texture operation instructions corresponding to a texture operation, in response to determining at least one of insufficient general purpose register space is available for the texture operation or insufficient wave slots are available for the texture operation, generating an indication that the texture operation corresponds to a deferred wave, executing the texture operation, sending, to a texture processor, initial texture sample instructions corresponding to the texture operation that was executed, and receiving texture mapped data corresponding to the initial texture sample instructions.

Abstract: The present disclosure relates to methods and apparatus for graphics processing. In some aspects, multiple processing units can be in a graphics processing pipeline of a GPU. The apparatus can also group the multiple processing units into one or more processing unit clusters. In some aspects, each of the one or more processing unit clusters can correspond to one or more context registers. Additionally, the apparatus can determine one or more context states of the one or more context registers in each of the one or more processing unit clusters. Also, the apparatus can implement one or more execution counters corresponding to at least one of the one or more processing unit clusters in the graphics processing pipeline, where each of the one or more execution counters includes an execution value.

Abstract: Systems and techniques are disclosed for general purpose register dynamic allocation based on latency associated with of instructions in processor threads. A streaming processor can include a general purpose registers configured to stored data associated with threads, and a thread scheduler configured to receive allocation information for the general purpose registers, the information describing general purpose registers that are to be assigned as persistent general purpose registers (pGPRs) and volatile general purpose registers (vGPRs). The plurality of general purpose registers can be allocated according to the received information. The streaming processor can include the general purpose registers allocated according to the received information, the allocated based on execution latencies of instructions included in the threads.

Abstract: Systems and techniques are disclosed for general purpose register dynamic allocation based on latency associated with of instructions in processor threads. A streaming processor can include a general purpose registers configured to stored data associated with threads, and a thread scheduler configured to receive allocation information for the general purpose registers, the information describing general purpose registers that are to be assigned as persistent general purpose registers (pGPRs) and volatile general purpose registers (vGPRs). The plurality of general purpose registers can be allocated according to the received information. The streaming processor can include the general purpose registers allocated according to the received information, the allocated based on execution latencies of instructions included in the threads.

Abstract: Techniques are described for determining whether execution of an instruction would require reading more values from a memory cell of a general purpose register (GPR) than a read port of the memory cell would allow. In such a case, the techniques may store, prior to execution of the instruction, one or more values from the memory cell in a separate conflict queue. During execution of the instruction to implement an operation defined by the instruction, one value that is an operand of the operation would be read from the memory cell and another value that is an operand of the operation other would be read from the conflict queue.

Abstract: Techniques are described for determining whether execution of an instruction would require reading more values from a memory cell of a general purpose register (GPR) than a read port of the memory cell would allow. In such a case, the techniques may store, prior to execution of the instruction, one or more values from the memory cell in a separate conflict queue. During execution of the instruction to implement an operation defined by the instruction, one value that is an operand of the operation would be read from the memory cell and another value that is an operand of the operation other would be read from the conflict queue.