A 2.793µW Near-Threshold Neuronal Population Dynamics Simulator for Reliable Simultaneous Localization and Mapping
Zhengzhe Wei, Boyi Dong, Yuqi Su, Yi Wang, Chuanshi Yang, Yuncheng Lu, Chao Wang, Tony Tae-Hyoung Kim, Yuanjin Zheng · 2024
This work presents an algorithm hardware co-design implementing a digital neuronal population dynamics simulator intended for a component within the back-end of simultaneous localization and mapping. A custom discretized procedural algorithm including injection, finite difference update, activation, and inhibition to approximate neuronal population dynamics is developed for digital implementation. Fabricated using a 40nm technology, the test chip features a scalable neuron 22 × 22 array with 0.1358mm2core area and provides a 12-bit computing precision. A time-multiplexed processing element design prevents the use of excessive silicon area. Accomplished via extensive data reuse through massively parallel processing-in-memory architecture attached to a custom I/O interface, a single inference operation is completed within 3277 clock cycles, providing 200 inferences per second operating at a low frequency of 0.667Mhz with a 0.5V core supply and consuming 2.793µW of power.