A Parallel Analysis on Scale Invariant Feature Transform (SIFT) Algorithm. - Donglei Yang; Lili Liu; Feiwen Zhu; Weihua Zhang (APPT, 2011)

A GPU-based high-throughput image retrieval algorithm. - Feiwen Zhu; Peng Chen; Donglei Yang; Weihua Zhang; Haibo Chen 001; Binyu Zang (GPGPU@ASPLOS, 2012)

Sparse Persistent RNNs: Squeezing Large Recurrent Networks On-Chip. - Feiwen Zhu; Jeff Pool; Michael Andersch; Jeremy Appleyard; Fung Xie (ICLR (Poster), 2018)

FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads. - Zhen Zheng; Pengzhan Zhao; Guoping Long; Feiwen Zhu; Kai Zhu; Wenyi Zhao; Lansong Diao; Jun Yang 052; Wei Lin 016 (CoRR, 2020)

AStitch: enabling a new multi-dimensional optimization space for memory-intensive ML training and inference on modern SIMT architectures. - Zhen Zheng; Xuanda Yang; Pengzhan Zhao; Guoping Long; Kai Zhu; Feiwen Zhu; Wenyi Zhao; Xiaoyong Liu; Jun Yang 052; Jidong Zhai; Shuaiwen Leon Song; Wei Lin 016 (ASPLOS, 2022)

FastDimeNet++: Training DimeNet++ in 22 minutes. - Feiwen Zhu; Michal Futrega; Han Bao 018; Sukru Burc Eryilmaz; Fei Kong; Kefeng Duan; Xinnian Zheng; Nimrod Angel; Matthias Jouanneaux; Maxmilian Stadler; Michal Marcinkiewicz; Fung Xie; et al. (ICPP, 2023)

HyperGef: A Framework Enabling Efficient Fusion for Hypergraph Neural Network on GPUs. - Zhongming Yu; Guohao Dai; Shang Yang; Genghan Zhang; Hengrui Zhang; Feiwen Zhu; June Yang; Jishen Zhao; Yu Wang 002 (MLSys, 2023)

ScaleFold: Reducing AlphaFold Initial Training Time to 10 Hours. - Feiwen Zhu; Arkadiusz Nowaczynski; Rundong Li; Jie Xin; Yifei Song; Michal Marcinkiewicz; Sukru Burc Eryilmaz; Jun Yang; Michael Andersch (DAC, 2024)

Boosting the Convergence of Reinforcement Learning-Based Auto-Pruning Using Historical Data. - Jiandong Mu; Mengdi Wang; Feiwen Zhu; Jun Yang 052; Wei Lin 016; Wei Zhang 012 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)