135 citations · 224 across the 16 of their papers we have counts for
7 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.…
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…
ThundeRiNG: Generating Multiple Independent Random Number Sequences on FPGAs
Hongshi Tan, Xinyu Chen, Yao Chen +2
In this paper, we propose ThundeRiNG, a resource-efficient and high-throughput system for generating multiple independent sequences of random numbers (MISRN) on FPGAs. Generating M…
3U-EdgeAI: Ultra-Low Memory Training, Ultra-Low BitwidthQuantization, and Ultra-Low Latency Acceleration
Yao Chen, Cole Hawkins, Kaiqi Zhang +2
The deep neural network (DNN) based AI applications on the edge require both low-cost computing platforms and high-quality services. However, the limited memory, computing resource…
Skew-Oblivious Data Routing for Data-Intensive Applications on FPGAs with HLS
Xinyu Chen, Hongshi Tan, Yao Chen +3
FPGAs have become emerging computing infrastructures for accelerating applications in datacenters. Meanwhile, high-level synthesis (HLS) tools have been proposed to ease the progra…
MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank
Lixiang Li, Yao Chen, Zacharie Zirnheld +2
Personalized PageRank (PPR) is a graph algorithm that evaluates the importance of the surrounding nodes from a source node. Widely used in social network related applications such…