Brief Industry Paper: optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms

MLA

Yunli Chen, et al. “Brief Industry Paper: Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms.” 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS), May 2021. EBSCOhost, https://doi.org/10.1109/rtas52030.2021.00048.

APA

Yunli Chen, Weisheng Zhao, Pengcheng Dai, Yingjie Qi, Jianlei Yang, Xiaoyi Wang, Ao Zhou, Yeqi Gao, Tong Qiao, & Chunming Hu. (2021). Brief Industry Paper: optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms. 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS). https://doi.org/10.1109/rtas52030.2021.00048

Chicago

Yunli Chen, Weisheng Zhao, Pengcheng Dai, Yingjie Qi, Jianlei Yang, Xiaoyi Wang, Ao Zhou, Yeqi Gao, Tong Qiao, and Chunming Hu. 2021. “Brief Industry Paper: Optimizing Memory Efficiency of Graph Neural Networks on Edge Computing Platforms.” 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium (RTAS), May. doi:10.1109/rtas52030.2021.00048.