Abstract: Disclosed herein is a graph streaming neural network processing system comprising a first processor array, a second processor, and a thread scheduler. The thread scheduler dispatches a thread of a first node to the first processor array or the second processor, wherein the thread is executed to generate output data comprising a data unit stored in a private data buffer of the second processor. The thread scheduler determines that the data unit is sufficient for executing a thread of a second node. The second node is dependent on the output data generated by execution of a plurality of threads of the first node. Upon determining that the data unit is sufficient, the thread scheduler dispatches the thread of the second node. The thread scheduler determines to dispatch a subsequent thread of the first node for execution when a predefined threshold buffer size is available on the private data buffer.

Abstract: Systems, apparatuses and methods are disclosed for efficient management of registers in a graph stream processing (GSP) system. The GSP system includes a thread scheduler module operative to initiate a Single Instruction Multiple Data (SIMD) thread, the SIMD thread including a dispatch mask with an initial value. A thread arbiter module operative to select an instruction from the instructions and provide the instruction to each of one or more compute resources, and an instruction iterator module, associated with the each of one or more compute resources operative to determine a data type of the instruction. The instruction iterator module iteratively executes the instruction based on the data type and the dispatch mask.

Abstract: Systems, apparatuses and methods are disclosed for efficient management of registers in a graph stream processing (GSP) system. The GSP system includes a thread scheduler module operative to initiate a Single Instruction Multiple Data (SIMD) thread, the SIMD thread including a dispatch mask with an initial value. A thread arbiter module operative to select an instruction from the instructions and provide the instruction to each of one or more compute resources, and an instruction iterator module, associated with the each of one or more compute resources operative to determine a data type of the instruction. The instruction iterator module iteratively executes the instruction based on the data type and the dispatch mask.