15 papers
NeuDW-CIM: a 65-nm 0.8-pJ/Sop Reconfigurable Neuromorphic Compute-in-Memory Macro with Nonlinear Dendrites and K-Winners
Junyi Yang, Yahan Yang, Shuai Dong +7
This work presents NeuDW-CIM, a highly efficient neuromorphic Compute-in-Memory (CIM) macro for Spiking Neural Networks (SNNs) implemented in 65 nm CMOS. The design introduces a cu…
A 32-Channel 3.53-μW Per Channel Brain-Machine Interface SoC Featuring Dual-Threshold Delta-modulation, In-Memory Spike Detection and Bi-SNN Based Motor Decoding
Ye Ke, Zhengnan Fu, Pao-Sheng Vincent Sun +8
With the scaling of sensor channel counts, systems confront challenges in frontend data sensing and on-implant data processing. This work presents a 32-channel fully event-based iB…
A Reconfigurable Computing In-Memory Macro with Charge-sharing-based Weighted Accumulator
Junyi Yang, Shuai Dong, Zhengnan Fu +2
SRAM-based analog computing-in-memory demonstrates outstanding efficiency. However, it faces three critical challenges: significant ADC overhead, high latency for multi-bit inputs,…
SNNF: An SNN-based Near-Sensor Noise Filter for Dynamic Vision Sensors
Yahan Yang, Pradeep Kumar Gopalakrishnan, Chang Chip Hong +1
Dynamic Vision Sensors (DVS) exhibit exceptional dynamic range and low power consumption, making them ideal for edge applications in the Internet of Video Things (IoVT). However, t…
SRAM-Based Compute-in-Memory Accelerator for Linear-decay Spiking Neural Networks
Hongyang Shang, Shuai Dong, Yahan Yang +3
Spiking Neural Networks (SNNs) have emerged as a biologically inspired alternative to conventional deep networks, offering event-driven and energy-efficient computation. However, t…
In-Memory ADC-Based Nonlinear Activation Quantization for Efficient In-Memory Computing
Shuai Dong, Junyi Yang, Biyan Zhou +3
In deep networks, operations such as ReLU and hardware-driven clamping often cause activations to accumulate near the edges of the distribution, leading to biased clustering and su…