Chen Zhang is a Visiting Graduate Researcher at the Computer Science Department at the University of California, Los Angeles (UCLA) from 22nd Sept. 2015 through 22nd Sept. 2016. He is a PhD student at the Center for Energy-efficient Computing and Applications as Peking University (2012- ). Currently, he is working at the PKU-UCLA Joint Research Center as a graduate student researcher.
His work is to build a heterogeneous computing system for deep learning frameworks and applications.
Google Scholar: https://scholar.google.com/citations?user=s9LcP1AAAAAJ&hl=zh-CN
1. Chen Zhang, Zhenman Fang, Peipei Zhou, Jason Cong. Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks. To appear in the 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2016), 2016.
2. Chen Zhang, Di Wu, Jiayu Sun, Guangyu Sun, Guojie Luo, Jason Cong. Energy-Efficient CNN Implementaion on a Deeply Pipelined FPGA Cluster. To appear in the 2016 IEEE/ACM International Symposim on Low Power Electronics and Design (ISLPED 2016), 2016.
3. Chen Zhang, Peng Li, Guangyu Sun, Yijin Guan, Bingjun Xiao, Jason Cong. Optimizing fpga-based accelerator design for deep convolutional neural networks. In Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. 2016.
4. Peng Wang, Guangyu Sun, Song Jiang, Jiang Ouyang, Shidin Lin, Chen Zhang, Jason Cong. An efficient design and implementation of LSM-tree based key-value store on open-channel SSD. In Proceedings of the Ninth European Conference on Computer Systems, ACM. 2014
5. Yuxin Wang, Peng Li , Peng Zhang, Chen Zhang, Jason Cong. Memory partitioning for multidimensional arrays in high-level synthesis. In Proceedings of the 50th Annual Design Automation Conference. ACM, 2013