Bionic Brain Clockless Computer Architecture —The Only Path to Breakthrough in Future Artificial Intelligence

AbstractThe current artificial intelligence hardware system is entirely based on the traditional digital architecture of global synchronous clocks, which faces three core bottlenecks: explosive power consumption, limited parallel computing power, and the disconnect between sequential logic and biological intelligence. These issues have become fundamental obstacles to the advancement of general artificial intelligence, brain-like computing, and edge-side intelligence. Existing technologies such as asynchronous circuits and neuromorphic chips only achieve partial clockless optimization, suffering from architectural incompleteness, lack of universality, and incomplete timing systems, making them unable to break through the underlying constraints of AI development. This paper originally proposes a biomimetic brain-inspired unidirectional event chain clockless global computing architecture, completely abandoning global crystal oscillators, clock trees, and frequency-divided timing systems. It uses operation completion events for unidirectional relay to drive general program progression, and employs gate circuit inherent delay chains to uniformly implement system timing, baud rate generation, interrupt response, and other full-scenario timing functions. This architecture fully replicates the working mechanisms of human brain neural event conduction, on-demand activation, and silent low-power consumption, balancing universal computational completeness with brain-like intelligence nativity. Through multi-dimensional comparative verification with traditional synchronous architectures, traditional bidirectional handshake asynchronous architectures, and pulsed neuromorphic architectures, this architecture is proven to fundamentally address three industry pain points: clock idling power consumption, timing synchronization constraints, and fragmented intelligent logic. It represents the sole underlying paradigm innovation path to overcome the energy efficiency, computing power, and cognitive logic bottlenecks of next-generation artificial intelligence, providing a completely new technical system for the realization of general brain-like artificial intelligence hardware.