Retrospectively Reverse-Engineering Apple's Neural Engine

A detailed technical exploration has been published regarding the reverse-engineering of Apple's Neural Engine (ANE), the specialized hardware accelerator found in Apple Silicon chips. The article documents the author's journey in deciphering the proprietary architecture and instruction set of the ANE, which is responsible for accelerating machine learning tasks on macOS and iOS devices. By analyzing binary blobs and system drivers, the researcher provides insights into how the hardware manages memory, handles compute kernels, and executes neural network operations. This work sheds light on the opaque nature of Apple's silicon design, offering a rare look at the low-level operations of the ANE. The findings are particularly significant for developers and security researchers interested in understanding the performance characteristics and potential vulnerabilities of Apple's custom AI hardware, moving beyond the official documentation provided by the company.