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publications
Adaptive Cache Management for Energy-efficient GPU Computing
Published in the 47th International Symposium on Micro Architecture, 2014
MICRO’14 (Acceptance rate: 53/273 ≈ 19.4%)
Recommended citation: 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.
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Optimizing STT-RAM Based Register File Energy Consumption on GPGPU with Delta Compression
Published in the 53rd Design Automation Conference, 2016
DAC’16 (Acceptance rate: 152/876 ≈ 17.4%)
Recommended citation: 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.
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Pangolin: An Efficient and Flexible Graph Mining System on CPU and GPU
Published in the 46th International Conference on Very Large Data Bases, 2020
VLDB’20 (Acceptance rate: 241/1172 ≈ 20.6%)
Recommended citation: 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.
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Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining
Published in the 35th International Conference on Supercomputing, 2021
ICS’21 (Acceptance rate: 39/157 ≈ 24.8%)
Recommended citation: 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
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FlexMiner: A Pattern-Aware Accelerator for Graph Pattern Mining
Published in the 48th International Symposium on Computer Architecture, 2021
ISCA’21 (Acceptance rate: 67/400 ≈ 16.8%)
Recommended citation: 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).
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Efficient and Scalable Graph Pattern Mining on GPUs
Published in the 16th USENIX Symposium on Operating Systems Design and Implementation, 2022
OSDI’22 (Acceptance rate: 49/253 ≈ 19.4%)
Recommended citation: Xuhao Chen, Arvind, Efficient and Scalable Graph Pattern Mining on GPUs, 16th USENIX Symposium on Operating Systems Design and Implementation, 2022.
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Speedcode: Software performance engineering education via Coding of didactic exercises
Published in the 14th NSF/TCPP Workshop on Parallel and Distributed Computing Education (EduPar-24), in conjunction with IPDPS 2024, 2024
EduPar’24
Recommended citation: 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 conjunction with IPDPS 2024.
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Accurate and Fast Approximate Graph Pattern Mining at Scale
Published in the 51st International Conference on Very Large Data Bases, 2025
VLDB’25
Recommended citation: Anna Arpaci-Dusseau, Zixiang Zhou and Xuhao Chen, Accurate and Fast Approximate Graph Pattern Mining at Scale, arXiv:2405.03488.
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resources
How to Write Fast Code?
A Quick-start Toolkit for Fast Coders
Getting Started with HPC
Tutorials for Hands-on HPC Experiences
software
GraphMiner
High performance Graph Pattern Mining
talks
Pangolin
Published:
Invited talk on Pangolin at the VLDB conference, September 3, 2020
Efficient and Scalable Graph Pattern Mining on GPUs
Published:
Invited talk on G2Miner at the OSDI conference, July 13, 2022
Speedcode Tutorial
Published:
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.
team
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Past Members
Faculty
Dr. Xuhao Chen
Students
Current Members