Self-Modifying Code for Neural Network Computation Reduction

The patent applies dynamics by making the instruction sequence dynamic through self-modifying code. Instead of executing a fixed instruction sequence, the processor dynamically modifies its own instruction stream at runtime based on break conditions. When a break condition is met, the processor overwrites subsequent instructions with NOP instructions, allowing the execution flow to adapt dynamically and eliminate redundant computations while maintaining implementation simplicity.

The patent applies preliminary action by pre-compiling all possible instruction sequences for neural network layers, including those that may eventually become redundant. The break condition checking mechanism is embedded within these pre-compiled instructions. At runtime, when a break condition is detected, the self-modifying code immediately overwrites subsequent instructions with NOPs, preventing wasted execution time while ensuring that all necessary computations are completed beforehand in the compilation phase.

The patent applies self-service by implementing self-modifying code that allows the processor to automatically modify its own instruction stream without external intervention. The processor includes dedicated circuitry (such as a code generation unit and instruction memory) that works autonomously to detect break conditions and overwrite subsequent instructions with NOP instructions. This self-service mechanism enables dynamic control flow and improved computation efficiency while minimizing the need for complex external control logic.

The patent introduces an intermediary mechanism in the form of a code generation unit and instruction memory structure that mediates between the compilation phase and execution phase. During compilation, all instructions are generated and stored in instruction memory with associated break condition logic. During execution, this intermediary structure automatically handles the self-modifying code operations by detecting break conditions and overwriting subsequent instructions with NOPs through dedicated circuitry, thereby reducing redundant computations while managing code complexity through structured intermediation rather than ad-hoc modifications.