Abstract: As one of the most distinctive representations for distributed computing, an end-edge-cloud collaborative computing system is capable of effectively bringing such applications as Internet of Things, large-scale language models, and digital twins into real life. By mimicking the neural activities that take place in the human brain, brain-inspired computing has various advantages, including energy efficiency, high speed, high error-tolerance, and desirable scalability. Through leveraging the event-driven mechanism and the sparsity in spike generation of spiking neural networks, the real-time processing capability and energy efficiency of an end-edge-cloud collaborative computing system can be significantly improved. In this paper, a distributed computing-oriented ISA design for brain-inspired intelligence CPU is studied. Bearing in mind the requirements of delay-sensitive, low-power, and high diversity for end devices, we focus on the software-hardware interface, i.e., ISA, and propose a hardware design that is rooted in the current systems, easy to implement and upgrade, safety-aware and self-controllable, and compatible with heterogeneous architectures. Along with a corresponding CPU micro-architecture design, a dozen of instructions specifically conceived for brain-inspired computing are proposed based on a well established ISA, which sets the stage for empowering distributed computing systems with brain-inspired computing. We firmly believe that this paper has discovered a fruitful research field, and sincerely hope that more interests can be stimulated in ISA designs for brain-inspired intelligence CPU in both academic and industrial communities.