5 citations · 7 across the 2 of their papers we have counts for
3 papers
cs.AR2021★ 2 cited
Being-ahead: Benchmarking and Exploring Accelerators for Hardware-Efficient AI Deployment
Xiaofan Zhang, Hanchen Ye, Deming Chen
Customized hardware accelerators have been developed to provide improved performance and efficiency for DNN inference and training. However, the existing hardware accelerators may…
cs.AR2020
DNNExplorer: A Framework for Modeling and Exploring a Novel Paradigm of FPGA-based DNN Accelerator
Xiaofan Zhang, Hanchen Ye, Junsong Wang +4
Existing FPGA-based DNN accelerators typically fall into two design paradigms. Either they adopt a generic reusable architecture to support different DNN networks but leave some pe…
cs.AR2020★ 5 cited
HybridDNN: A Framework for High-Performance Hybrid DNN Accelerator Design and Implementation
Hanchen Ye, Xiaofan Zhang, Zhize Huang +2
To speedup Deep Neural Networks (DNN) accelerator design and enable effective implementation, we propose HybridDNN, a framework for building high-performance hybrid DNN accelerator…