21 citations · 34 across the 7 of their papers we have counts for
8 papers
A Secure dToF LiDAR SoC with Dual-Domain Fingerprinting and Event-Driven AFE Circuit Achieving Sensor-Level Attack Resilience
Risa Nonaka, Ryoya Matsuno, Shota Nagai +10
Recent studies have shown that most commercial direct time-of-flight (dToF) LiDARs can be spoofed by injecting high-frequency laser pulses into the receiver, which can erase pedest…
BitROM: Weight Reload-Free CiROM Architecture Towards Billion-Parameter 1.58-bit LLM Inference
Wenlun Zhang, Xinyu Li, Shimpei Ando +1
Compute-in-Read-Only-Memory (CiROM) accelerators offer outstanding energy efficiency for CNNs by eliminating runtime weight updates. However, their scalability to Large Language Mo…
AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization
Wenlun Zhang, Yunshan Zhong, Weiqi Yan +3
The Segment Anything Model (SAM) has revolutionized image and video segmentation with its powerful zero-shot capabilities. However, its massive parameter scale and high computation…
A Review of SRAM-based Compute-in-Memory Circuits
Kentaro Yoshioka, Shimpei Ando, Satomi Miyagi +2
This paper presents a tutorial and review of SRAM-based Compute-in-Memory (CIM) circuits, with a focus on both Digital CIM (DCIM) and Analog CIM (ACIM) implementations. We explore…
ASiM: Modeling and Analyzing Inference Accuracy of SRAM-Based Analog CiM Circuits
Wenlun Zhang, Shimpei Ando, Yung-Chin Chen +1
SRAM-based Analog Compute-in-Memory (ACiM) demonstrates promising energy efficiency for deep neural network (DNN) processing. Nevertheless, efforts to optimize efficiency frequentl…
PACiM: A Sparsity-Centric Hybrid Compute-in-Memory Architecture via Probabilistic Approximation
Wenlun Zhang, Shimpei Ando, Yung-Chin Chen +3
Approximate computing emerges as a promising approach to enhance the efficiency of compute-in-memory (CiM) systems in deep neural network processing. However, traditional approxima…
HALO-CAT: A Hidden Network Processor with Activation-Localized CIM Architecture and Layer-Penetrative Tiling
Yung-Chin Chen, Shimpei Ando, Daichi Fujiki +2
To address the 'memory wall' problem in NN hardware acceleration, we introduce HALO-CAT, a software-hardware co-design optimized for Hidden Neural Network (HNN) processing. HALO-CA…
OSA-HCIM: On-The-Fly Saliency-Aware Hybrid SRAM CIM with Dynamic Precision Configuration
Yung-Chin Chen, Shimpei Ando, Daichi Fujiki +2
Computing-in-Memory (CIM) has shown great potential for enhancing efficiency and performance for deep neural networks (DNNs). However, the lack of flexibility in CIM leads to an un…