2024

Xueyuan Liu, Zhuoran Song, Hao Chen, Xing Li, and Xiaoyao Liang. MoC: A Morton-Code-Based Fine-Grained Quantization for Accelerating Point Cloud Neural Networks. Accepted by Design Automation Conference (DAC 2024). [blog]

Xueyuan Liu, Zhuoran Song, Guohao Dai, Gang Li, Can Xiao, Yan Xiang, Dehui Kong, Ke Xu and Xiaoyao Liang. FusionArch: A Fusion-Based Accelerator for Point-Based Point Cloud Neural Networks. Accepted by Design, Automation, and Test in Europe (DATE 2024). Best Paper Award. [blog]

Xueyuan Liu, Zhuoran Song, Xiang Liao, Xing Li, Tao Yang, Fangxin Liu and Xiaoyao Liang. Sava: A Spatial- and Value-Aware Accelerator for Point Cloud Transformers. Accepted by Design, Automation, and Test in Europe (DATE 2024). [blog]

Xing Li, Zhuoran Song, Rachata Ausavarungnirun, Xiao Liu, Xueyuan Liu, Xuan Zhang, Xuhang Wang, Jiayao Ling, Gang Li, Naifeng Jing, Xiaoyao Liang. Janus: A Flexible Processing-in-Memory Graph Accelerator Towards Sparsity. Accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2024. [view]

2022

Xing Li, Rachata Ausavarungnirun, Xiao Liu, Xueyuan Liu, Xuan Zhang, Heng Lu, Zhuoran Song, Naifeng Jing and Xiaoyao Liang. Gzippo: Highly-compact Processing-In-Memory Graph Accelerator Alleviating Sparsity and Redundancy. Accepted by 2022 IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2022). [view]

Contributed to the writing of “General-Purpose Graphics Processing Units Design - GPGPU Programming Model and Architecture Principles” (通用图形处理器设计——GPGPU编程模型和架构原理). Published by Tsinghua University Press, 2022. [view]

2020

Zhuoran Song, Feiyang Wu, Xueyuan Liu, Naifeng Jing and Xiaoyao Liang. VR-DANN: Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration. Accepted by IEEE/ACM International Symposium on Microarchitecture (MICRO 2020). [view]