10 papers
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…
An Event-Driven E-Skin System with Dynamic Binary Scanning and real time SNN Classification
Gaishan Li, Zhengnan Fu, Anubhab Tripathi +2
This paper presents a novel hardware system for high-speed, event-sparse sampling-based electronic skin (e-skin)that integrates sensing and neuromorphic computing. The system is bu…
1024-Channel 0.8V 23.9-nW/Channel Event-based Compute In-memory Neural Spike Detector
Ye Ke, Zhengnan Fu, Junyi Yang +2
The increasing data rate has become a major issue confronting next-generation intracortical brain-machine interfaces (iBMIs). The scaling number of recording sites requires complex…
A 33.6-136.2 TOPS/W Nonlinear Analog Computing-In-Memory Macro for Multi-bit LSTM Accelerator in 65 nm CMOS
Junyi Yang, Xinyu Luo, Ye Ke +7
The energy efficiency of analog computing-in-memory (ACIM) accelerator for recurrent neural networks, particularly long short-term memory (LSTM) network, is limited by the high pro…
Near-Memory Architecture for Threshold-Ordinal Surface-Based Corner Detection of Event Cameras
Hongyang Shang, An Guo, Shuai Dong +3
Event-based Cameras (EBCs) are widely utilized in surveillance and autonomous driving applications due to their high speed and low power consumption. Corners are essential low-leve…