6 papers · 1 filter
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…
3D Stack In-Sensor-Computing (3DS-ISC): Accelerating Time-Surface Construction for Neuromorphic Event Cameras
Hongyang Shang, Shuai Dong, Ye Ke +1
This work proposes a 3D Stack In-Sensor-Computing (3DS-ISC) architecture for efficient event-based vision processing. A real-time normalization method using an exponential decay fu…
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…
CADC: Crossbar-Aware Dendritic Convolution for Efficient In-memory Computing
Shuai Dong, Junyi Yang, Ye Ke +2
Convolutional neural networks (CNNs) are computationally intensive and often accelerated using crossbar-based in-memory computing (IMC) architectures. However, large convolutional…
Topkima-Former: Low-energy, Low-Latency Inference for Transformers using top-k In-memory ADC
Shuai Dong, Junyi Yang, Xiaoqi Peng +5
Transformer model has gained prominence as a popular deep neural network architecture for neural language processing (NLP) and computer vision (CV) applications. However, the exten…