168 citations · 743 across the 44 of their papers we have counts for
14 papers · 1 filter
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.…
EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture Search
Qian Jiang, Xiaofan Zhang, Deming Chen +2
In hardware-aware Differentiable Neural Architecture Search (DNAS), it is challenging to compute gradients of hardware metrics to perform architecture search. Existing works rely o…
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…
Scaling Up Hardware Accelerator Verification using A-QED with Functional Decomposition
Saranyu Chattopadhyay, Florian Lonsing, Luca Piccolboni +12
Hardware accelerators (HAs) are essential building blocks for fast and energy-efficient computing systems. Accelerator Quick Error Detection (A-QED) is a recent formal technique wh…
Generic Neural Architecture Search via Regression
Yuhong Li, Cong Hao, Pan Li +2
Most existing neural architecture search (NAS) algorithms are dedicated to and evaluated by the downstream tasks, e.g., image classification in computer vision. However, extensive…
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…