Dimension-Based Search Space for Neural Network Mapping

The patent segments the CGRP system into distinct processing elements (PEs) and memory elements, each with specific functions. The compiler divides the neural network computation into operations that can be mapped to these segmented components, managing complexity by organizing the system into manageable functional units with defined roles in the computation pipeline.

The patent introduces intermediate representations and compiler abstractions that serve as mediators between the high-level neural network operations and the low-level CGRP hardware mapping. These intermediaries simplify the mapping process by providing structured interfaces that bridge the gap between algorithmic descriptions and hardware implementation details.

The patent segments memory elements into distinct storage units with specific functions (e.g., input buffers, weight buffers, output buffers). This segmentation provides clear mapping targets for different data types in neural network computations, reducing mapping difficulty by organizing memory resources into functionally distinct categories that correspond to operational requirements.

The patent assigns specific memory elements to specific data types and operational stages based on their local functional requirements. Different memory elements have optimized characteristics suited to their specific purposes (e.g., high-speed buffers for frequent access, larger capacity for weight storage), making the mapping process more straightforward by matching data access patterns to appropriately characterized memory resources.

The patent employs dynamic resource allocation and pipeline staging that adapts to the specific computational requirements of different neural network operations. The compiler generates dynamic control logic that manages data flow and synchronization between parallel processing elements based on runtime conditions, reducing fixed synchronization overhead while maintaining high computational performance through flexible resource utilization.

The patent implements pipelined execution that maintains continuous useful action across parallel processing elements. By organizing computations into overlapping pipeline stages where data flows continuously through the system, the patent reduces idle time and synchronization barriers, keeping processing elements actively engaged in productive work rather than waiting for synchronization events.