Brain-like computer supporting hundred million neurons

Abstract

The invention discloses a brain-like computer supporting hundred million neurons. The brain-like computer comprises a hierarchical expansion system architecture and system architecture internal calculation process control. The system architecture comprises a plurality of brain-like computing chips which are managed in a hierarchical organization mode and used for achieving computing tasks, each brain-like computing chip comprises computing neurons and synaptic resources and forms a neural network, and pulse events among the computing neurons in the system architecture are transmitted in a hierarchical transmission mode; the calculation process control comprises parallel processing of calculation tasks in the control system architecture, management of synchronization time in the control system architecture and reconstruction of the neural network in the control system architecture to realize fault tolerance and robustness management of calculation neurons and synaptic resources. The brain-like computer can support hundreds of millions of spiking neural network reasoning calculation of the neuron scale.

Description

technical field [0001] The invention belongs to the technical field of artificial neural networks, and in particular relates to a brain-like computer supporting hundreds of millions of neurons. Background technique [0002] Since the von Neumann architecture was proposed in 1945, computers based on this architecture have been used to this day, and its basic feature is the separation of memory and computing units. The advantage of storage-computing separation is that the software is programmable, that is, the same hardware platform can store different software to perform different functions. The disadvantage is that the communication between the storage unit and the computing unit will become a performance bottleneck. Thanks to the rapid development of the semiconductor industry in accordance with Moore's Law, the computing performance index of the von Neumann architecture has increased for decades. In recent years, the effects of "memory wall" and "power consumption wall" ha...

AI Technical Summary

Problems solved by technology

In 2005, the University of Manchester in the United Kingdom began to develop the ARM-based multi-core supercomputer SpiNNaker, which mainly used ARM to simulate neurons. It reached a scale of 1 million cores in 2018, but the power consumption was relatively high.

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