135 citations · 224 across the 16 of their papers we have counts for
16 papers
HiKonv: Maximizing the Throughput of Quantized Convolution With Novel Bit-wise Management and Computation
Yao Chen, Junhao Pan, Xinheng Liu +2
Quantization for CNN has shown significant progress with the intention of reducing the cost of computation and storage with low-bitwidth data representations. There are, however, n…
Compilation and Optimizations for Efficient Machine Learning on Embedded Systems
Xiaofan Zhang, Yao Chen, Cong Hao +3
Deep Neural Networks (DNNs) have achieved great success in a variety of machine learning (ML) applications, delivering high-quality inferencing solutions in computer vision, natura…
ReGraph: Scaling Graph Processing on HBM-enabled FPGAs with Heterogeneous Pipelines
Xinyu Chen, Yao Chen, Feng Cheng +3
The use of FPGAs for efficient graph processing has attracted significant interest. Recent memory subsystem upgrades including the introduction of HBM in FPGAs promise to further a…
HiKonv: High Throughput Quantized Convolution With Novel Bit-wise Management and Computation
Xinheng Liu, Yao Chen, Prakhar Ganesh +3
Quantization for Convolutional Neural Network (CNN) has shown significant progress with the intention of reducing the cost of computation and storage with low-bitwidth data inputs.…
YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs
Prakhar Ganesh, Yao Chen, Yin Yang +2
Performance of object detection models has been growing rapidly on two major fronts, model accuracy and efficiency. However, in order to map deep neural network (DNN) based object…
WinoCNN: Kernel Sharing Winograd Systolic Array for Efficient Convolutional Neural Network Acceleration on FPGAs
Xinheng Liu, Yao Chen, Cong Hao +2
The combination of Winograd's algorithm and systolic array architecture has demonstrated the capability of improving DSP efficiency in accelerating convolutional neural networks (C…