Grand Challenge on Software and Hardware Co-Optimization for E-Commerce Recommendation System

Jianing Li1; Jiabin Liu1; Xingyuan Hu1; Yuhang Zhang2; Guosheng Yu3; Shimeng Qian3; Wei Mao4; Li Du1; Yongfu Li2; Yuan Du1

10.1109/AICAS57966.2023.10168648

2023

2834-9830

979-8-3503-3268-1

2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)

1-5

11-13 June 2023

Hangzhou, China

E-commerce has become an indispensable part of the whole commodity economy with rapid expansion. A great deal of time is required for customers to search products by manual work. A good automatic recommendation system can not only bring the customers good shopping experience, but also help companies gain profit growth. In the IEEE AICAS 2023 conference, we have organized the grand challenge on software and hardware co-optimization for e-commerce recommendation system. The desensitized data from Alibaba Group which recorded online purchase behaviors of online shopping users in China are provided. We organize two rounds of the challenge with two different parts of data, separately encouraging participating teams to propose novel ideas for the recommendation algorithm design and deployment. In the preliminary round, participating teams are required to design a recommendation system with high accuracy performance. In the final round, the qualified teams from the preliminary round will be offered with an ARM-based multi-core Yitian 710 CPU cloud server, the teams are required to design an acceleration scheme for the hardware resolution. In the final, 6 best teams will be awarded by using standard evaluation criteria.

Grand challenge software and hardware co-optimization recommendation system open-source efficient deployment machine-learning algorithms

其他

EI

20233114469040

Computer hardware ; Electronic commerce ; Learning algorithms ; Machine learning ; Open source software ; Open systems ; Sales

Computer Systems and Equipment:722 ; Computer Software, Data Handling and Applications:723 ; Artificial Intelligence:723.4 ; Machine Learning:723.4.2 ; Computer Applications:723.5

IEEE

1.School of Electronic Science and Engineering, Nanjing University, China
2.Department of Micro-Nano Electronics and MoE Key Lab of Artificial Intelligence, Shanghai Jiao Tong University, China
3.T-Head Semiconductor Co., Ltd, China
4.School of Microelectronics, Southern University of Science and Technology, Shenzhen, China

Jianing Li,Jiabin Liu,Xingyuan Hu,et al. Grand Challenge on Software and Hardware Co-Optimization for E-Commerce Recommendation System[C],2023:1-5.