(EduPar 2024)
[PDF]
[SpeedCode Website]
Tim Kaler, Xuhao Chen, Brian Wheatman, Dorothy Curtis, Bruce Hoppe, Tao B. Schardl, and Charles E. Leiserson
SpeedCode: Software performance engineering education via Coding of didactic exercises,
14th NSF/TCPP Workshop on Parallel and Distributed Computing Education
(EduPar-24), In conjuction with IPDPS 2024
(OSDI 2022)
[PDF]
[Talk]
[BibTeX]
[Code]
Xuhao Chen, Arvind
Efficient and Scalable Graph Pattern Mining on GPUs,
16th USENIX Symposium on Operating Systems Design and Implementation, 2022
(GNNSys 2021)
[PDF]
[Poster]
[BibTeX]
[Zoom Talk]
[Code]
Loc Hoang, Xuhao Chen, Hochan Lee, Roshan Dathathri, Gurbinder Gill, Keshav Pingali,
Efficient Distribution for Deep Learning on Large Graphs,
Workshop on Graph Neural Networks and Systems, 2021
(ISCA 2021)
[PDF]
[Talk (PPTX)]
[BibTeX]
[Zoom Talk]
[Code]
Xuhao Chen*, Tianhao Huang*, Shuotao Xu, Thomas Bourgeat, Chanwoo Chung, Arvind
FlexMiner: A Pattern-Aware Accelerator for Graph Pattern Mining,
International Symposium on Computer Architecture, 2021 (*: equal contribution)
(ICS 2021)
[PDF]
[Talk (PPTX)]
[BibTeX]
[Code]
Xuhao Chen, Roshan Dathathri, Gurbinder Gill, Loc Hoang, Keshav Pingali,
Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining,
International Conference on Supercomputing, 2021
(VLDB 2020)
[PDF]
[Talk (PPTX)]
[YouTube]
[Bilibili]
[BibTeX]
[Code]
Xuhao Chen, Roshan Dathathri, Gurbinder Gill, Keshav Pingali,
Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU,
PVLDB 13(8): 1190-1205, 2020
(HPEC 2019)
[PDF]
[Talk (PPTX)]
[BibTeX]
[Code]
Loc Hoang, Vishwesh Jatala, Xuhao Chen, Udit Agarwal, Roshan Dathathri, Grubinder Gill, Keshav Pingali,
DistTC: High Performance Distributed Triangle Counting,
IEEE High Performance Extreme Computing Conference (HPEC), 2019
(arXiv)
[PDF]
[Code]
Xuhao Chen,
GraphCage: Cache Aware Graph Processing on GPUs,
CoRR, https://arxiv.org/abs/1904.02241
(JETC)
[PDF]
[Code]
Zhen Xu, Xuhao Chen, Jie Shen, Yang Zhang, Cheng Chen, Canqun Yang,
GARDENIA: A Graph Processing Benchmark Suite for Next-generation Accelerators,
ACM Journal on Emerging Technologies in Computing Systems, 15(1): 1-13, 2019
(arXiv)
[PDF]
[Code]
Xuhao Chen,
Escort: Efficient Sparse Convolutional Neural Networks on GPUs,
CoRR, https://arxiv.org/abs/1802.10280
(Parco)
[PDF]
[Code]
[BibTeX]
Xuhao Chen, Cheng Chen, Jie Shen, Jianbin Fang, Tao Tang, Canqun Yang, Zhiying Wang,
Orchestrating Parallel Detection of Strongly Connected Components on GPUs,
Parallel Computing, Vol 78, Pages 101–114, 2018
(CPE)
[PDF]
[Code]
[BibTeX]
Xuhao Chen, Pingfan Li, Jianbin Fang, Tao Tang, Zhiying Wang, Canqun Yang,
Efficient and High-quality Sparse Graph Coloring on the GPU,
Concurrency and Computation: Practice and Experience, Volume 29, Issue 10, 17 April 2017
(DAC 2016)
[PDF]
[Talk (PPTX)]
[BibTeX]
Hang Zhang, Xuhao Chen, Nong Xiao, Fang Liu,
Optimizing STT-RAM Based Register File Energy Consumption on GPGPU with Delta Compression,
In the Proceedings of the 53rd Design Automation Conference (DAC-53), Austin, TX, June 2016
(Acceptance rate: 152/876 ≈ 17.4%)
(MICRO 2014)
[PDF]
[Talk (PPTX)]
[Poster]
[Lightning]
[BibTeX]
Xuhao Chen, Li-Wen Chang, Christopher I. Rodrigues, Jie Lv, Zhiying Wang, Wen-Mei W. Hwu,
Adaptive Cache Management for Energy-efficient GPU Computing,
In the Proceedings of 47th International Symposium on Micro Architecture (MICRO), Cambridge, UK, December 2014
(Acceptance rate: 53/273 ≈ 19.4%)