{"id":30,"date":"2016-02-10T09:12:48","date_gmt":"2016-02-10T17:12:48","guid":{"rendered":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/?page_id=30"},"modified":"2025-04-30T08:37:44","modified_gmt":"2025-04-30T15:37:44","slug":"publications","status":"publish","type":"page","link":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"
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Refereed Conference Publications:<\/h2>\n<\/header>\n
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  1. Rubayet Rongon and Xuechen Zhang. <\/strong>“iAUG: Accelerating Augmentation with Importance Sampling in Deep Neural Network Training”. In Proceedings of the 31st International European Conference on Parallel and Distributed Computing (EURO-PAR’25), Dresden, Germany, August 2025. (Acceptance Rate: 29%)<\/span><\/li>\n
  2. Weijian Chen, Shuibing He, Haoyang Ou, and Xuechen Zhang<\/strong>. “LeapGNN: Accelerating Distributed GNN Training Leveraging Feature-Centric Model Migration”.\u00a0 In the 23rd USENIX Conference on File and Storage Technologies (FAST ’25), Santa Clara, CA, February 2025. (Acceptance Rate: 21.5%)<\/li>\n
  3. Siling Yang, Shuibing He, Wenjiong Wang, Yanlong Yin, Tong Wu, Weijian Chen, Xuechen Zhang<\/strong>, Xina-He Sun, and Dan Feng, “GOPIM: GCN-Oriented Pipeline Optimization for PIM Accelerators”. In The 31st IEEE International Symposium on High-Performance Computer Architecture (HPCA-31), Las Vegas, NV, March 2025. (Acceptance Rate: 21%)<\/li>\n
  4. Rubayet Rongon, Chen Cao, and Xuechen Zhang<\/strong>, “A Study of Data-Path Bugs in PyTorch with a Focus on Memory Management”. In Proceedings of the 2024 IEEE International Conference on Big Data (BigData’24), Washington DC, December 2024. (Acceptance Rate: 18.8%)<\/li>\n
  5. \n

    Zhe Pan, Shuibing He, Xu Li, Xuechen Zhang<\/strong>, Yanlong Yin, Rui Wang, Lidan Shou, Mingli Song, Xian- He Sun, and Gang Chen. Enumeration of Billions of Maximal Bicliques in Bipartite Graphs without Using GPUs. In Proceedings of the ACM\/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC\u201924), Atlanta, GA, November 2024. <\/span>(<\/span>Acceptance Rate: 22.7%<\/span>)<\/span><\/p>\n<\/li>\n

  6. \n

    Tong Wu, Shuibing He, Jianxin Zhu, Weijiang Chen, Siling Yang, Ping Chen, Yanlong Yin, Xuechen Zhang<\/strong>, Xian-He Sun, Gang Chen. AUTOHET: An Automated Heterogeneous ReRAM-Based Accelerator for DNN Inference. In Proceedings of the 53rd International Conference on Parallel Processing (ICPP\u201924), Gotland, Sweden, August 2024. (Acceptance rate: 29%)<\/span><\/p>\n<\/li>\n

  7. \n

    Keegan Sanchez, Alex Gavin, Suren Byna, Kesheng Wu, and Xuechen Zhang<\/strong>. A High-Performance Collective I\/O Framework Leveraging Node-Local Persistent Memory. In Proceedings of the 30th International European Conference on Parallel and Distributed Computing (EURO-PAR’24), Madrid, Spain, August 2024. (Acceptance Rate: 29%)<\/span><\/p>\n<\/li>\n

  8. Zhenxin Li, Shuibing He, Zheng Dang, Peiyi Hong, Xuechen Zhang<\/strong>, Rui Wang, and Fei Wu, CCL- BTree: A Crash-Consistent Locality-Aware B+-Tree for Reducing XPBuffer-Induced Write Amplification in Persistent Memory. In Proceedings of The European Conference on Computer Systems (EuroSys \u201924), Athens, Greece, April 2024. (Acceptance Rate: 16%)<\/span><\/li>\n
  9. Zhe Pan, Shuibing He, Xu Li, Xuechen Zhang<\/strong>, Rui Wang, and Gang Chen, “Efficient Maximal Biclique Enumeration on GPUs”, In Proceedings of ACM\/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC\u201923), Denver, CO, November 2023. (Acceptance Rate: 24%)<\/span><\/li>\n
  10. Weijian Chen, Shuibing He, Yaowen Xu, Xuechen Zhang<\/strong>, Siling Yang, Shuang Hu, Xian-He Sun, and Gang Chen, “iCACHE: An Importance-Sampling-Informed Cache for Accelerating I\/O-Bound DNN Model Training”, In Proceedings of the 29th<\/sup> IEEE International Symposium on High-Performance Computer Architecture\u00a0(HPCA-29), Montreal, QC, Canada, February 2023. (Acceptance Rate: 25%)<\/span><\/li>\n
  11. Brian Koga, Theresa Vanderweide, Xinghui Zhao, and Xuechen Zhang<\/strong>. BlinkNet: Software-Defined Deep Learning Analytics with Bounded Resources. In Proceedings of 21st IEEE International Conference on Machine Learning and Applications (ICMLA’22), Nassau, The Bahamas, December 2022. (Full Paper Acceptance Rate: 32%)<\/span><\/li>\n
  12. \n

    Shuibing He, Matthew Myers, Xuehao Duan, Keegan Sanchez, and Xuechen Zhang<\/strong>. WAFLASH: Taming Unaligned Writes in Solid-State Disks. In Proceedings of 16th IEEE International Conference On Networking, Architecture, and Storage (NAS\u201922), Philadelphia, PA, October 2022.<\/p>\n<\/li>\n

  13. \n

    Brandon Lavinsky and Xuechen Zhang<\/strong>, “PM-Rtree: A Highly-Efficient Crash-Consistent R-tree for Persistent Memory”. In Proceedings of the 34th International Conference on Scientific and Statistical Database Management (SSDBM\u201922), Copenhagen, Denmark, July 2022. (Full Paper Acceptance Rate: 22%)<\/p>\n<\/li>\n

  14. Zheng Dang, Shuibing He, Peiyi Hong, Zhenxin Li, Xuechen Zhang<\/strong>, Xian-He Sun, Gang Chen, “NVAlloc: Rethinking Heap Metadata Management in Persistent Memory Allocators”, In Proceedings of the 27th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’22), Lausanne, Switzerland, February 2022. (Acceptance Rate: 20%)<\/span><\/li>\n
  15. Yekang Wu and Xuechen Zhang<\/strong>. “NVSwap: Latency-Aware Paging using Non-Volatile Main Memory”. In Proceedings of <\/span><\/span>15th IEEE International Conference On Networking, Architecture, and Storage (NAS’21), Riverside, CA, October 2021.<\/li>\n
  16. Ping Chen, Shuibing He, Xuechen Zhang<\/strong>, Shuaiben Chen, Peiyi Hong, Yanlong Yin, and Xian-He Sun. “CSWAP: A Self-Tuning Compression Framework for Accelerating Tensor Swapping in GPUs”. In Proceedings of the IEEE Cluster 2021 (Cluster’21), Online, September 2021. (Acceptance Rate: 29%)<\/span><\/li>\n
  17. Siling Yang, Weijian Chen, Xuechen Zhang<\/strong>, Shuibing He, Yanlong Yin, and Xian-He Sun. “Automated DNN Pruning and Mapping for ReRAM-based Accelerator”. In Proceedings of International Conference on Supercomputing 2021 (ICS’21), Worldwide online event, June 2021. (Acceptance Rate: 24%).<\/span><\/li>\n
  18. Tyler Coy, Shuibing He, Bin Ren, and Xuechen Zhang<\/strong>. “Compiler Aided Checkpointing using Crash-Consistent Data Structures in NVMM Systems”. In Proceedings of International Conference on Supercomputing 2020 (ICS’20), Barcelona, Spain, June 2020. (Acceptance Rate: 30%). <\/span><\/li>\n
  19. Soklong Lim, Zaixin Lu, Bin Ren, and Xuechen Zhang<\/strong>, “Enforcing Crash Consistency of Evolving Network Analytics in Non-Volatile Main Memory Systems”, In Proceedings of the 28th International Conference on Parallel Architectures and Compilation Techniques (PACT’19), Seattle, WA, September 2019. (Acceptance Rate: 25%)<\/li>\n
  20. Ian Kosen, Zhi Chen, and Xuechen Zhang<\/strong>. “Enabling QoS-Aware Processing of PMU Data on Unified Storage Infrastructure”, In Proceedings of the First IEEE International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA\u201919), College Station, Texas, USA, May 2019.<\/li>\n
  21. Soklong Lim, Jun Hao, Zaixin Lu, Xuechen Zhang<\/strong>, and Zhao Zhang, “Approximating the k-Minimum Distance Rumor Source Detection in Online Social Networks”, In Proceedings of the 27th International Conference on Computer Communications and Networks (ICCCN\u201918), Hangzhou, China, July 2018. (Acceptance Rate: 29.5%)<\/li>\n
  22. Suman Karki, Bao Bguyen, and Xuechen Zhang<\/strong>, \u201cQoS Support for Scientific Workflows using Software-Defined Storage Resource Enclaves\u201d, 32th IEEE International Parallel & Distributed Processing Symposium (IPDPS\u201918), Vancouver, BC, Canada, May 2018. (Acceptance Rate: 24.5%)<\/li>\n
  23. Fang Zheng, Bao Nguyen, and\u00a0Xuechen Zhang<\/strong>, “Feature Guided In-Situ Indices Generation and Data Placement on Distributed Deep Memory Hierarchies”. The 23rd IEEE International Conference on Parallel and Distributed Systems (ICPADS’17), Shenzhen, China, December 2017. (Acceptance Rate: 29%)<\/li>\n
  24. Bao Nguyen, Tan Hua, and Xuechen Zhang<\/strong>, \u00a0“Large-scale Adaptive Mesh Simulations Through Non-Volatile Byte-Addressable Memory”, ACM\/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC’17), Denver, CO, November 2017. (Acceptance Rate: 18.6%)<\/li>\n
  25. Jian Huang, Michael R. Allen-Bond, Xuechen Zhang<\/strong>, “Semantic-Aware Checking for Finding Deep Bugs in Fast Path”,\u00a0Proceedings of 22nd International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS’17), Xi’an, China, April 2017. (Acceptance Rate: 17.4%)<\/li>\n
  26. Xuechen Zhang<\/strong>, Ujjwal Khanal, Xinghui Zhao and Stephen Ficklin, “Understanding Software Platforms for In-memory Scientific Data Analysis: A Case Study of the Spark System”. The 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS’16),\u00a0Wuhan, China, December, 2016. (Acceptance Rate: 29%)<\/li>\n
  27. Xuechen Zhang<\/strong>, Fang Zheng, Karsten Schwan, and Matthew Wolf, \u201dFlashStager: Improving the Performance of SSD-based Data Staging Systems via Write Redirection\u201d. Short paper. IEEE International Conference on Cluster Computing (Cluster’16), Taipei, Taiwan, September 2016. (Acceptance Rate: 34%)<\/li>\n
  28. Jian Huang, Xuechen Zhang<\/strong>, and Karsten Schwan, “Understanding Issue Correlations: A Case Study of the Hadoop System”, The ACM Symposium on Cloud Computing 2015 (SOCC’15), Kohala Cost, HI, August 2015. (Acceptance Rate: 21%)<\/li>\n
  29. Xuechen Zhang<\/strong>, Jianqiang Ou, Kei Davis, and Song Jiang, “Orthrus: A Framework for Implementing High-performance Collective I\/O in the Multicore Clusters”,The International Supercomputing Conference (ISC’14), Leipzig, Germany, June 2014.<\/li>\n
  30. Jai Dayal, Drew Bratcher, Greg Eisenhauer, Karsten Schwan, Matthew Wolf, Xuechen Zhang<\/strong>, Hasan Abbasi, Scott Klasky and Norbert Podhorszki, \u201dFlexpath: Type-Based Publish\/Subscribe System for Large- scale Science Analytics\u201d,the 14th IEEE\/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID’14), Chicago, IL, May 2014. (Acceptance Rate: 19%)<\/li>\n
  31. Jian Huang, Xuechen Zhang<\/strong>, Greg Eisenhauer, Karsten Schwan, Matthew Wolf, Stephane Ethier, and Scott Klasky, \u201dScibox:Online Sharing of Scientific Data via the Cloud\u201d, IEEE IPDPS, Tucson, AZ, May 2014. (Acceptance Rate: 21%)<\/li>\n
  32. Dachuan Huang, Xuechen Zhang<\/strong>, Wei Shi, Mai Zheng, Song Jiang, and Feng Qin, \u201dLiU:Hiding Disk Access Latency for HPC Applications with a New SSD-Enabled Data Layout\u201d, IEEE MASCOTS, San Francisco, CA, August 2013. (Acceptance Rate: 27%)<\/li>\n
  33. Xuechen Zhang<\/strong>, Jianqiang Ou, Kei Davis, and Song Jiang, \u201cOrthrus: A Framework for Implementing High- performance Collective I\/O in the Multicore Clusters\u201d, Short paper, ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC\u201913), New York, June 2013. (Acceptance Rate: 26%)<\/li>\n
  34. Xuechen Zhang<\/strong>, Ke Liu, Kei Davis, and Song Jiang, \u201diBridge: Improving Unaligned Parallel File Access with Solid-State Drives\u201d, IEEE IPDPS, Boston, MA, May 2013. (Acceptance Rate: 21%)<\/li>\n
  35. Ke Liu, Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201dSynergistic Coupling of SSD and Hard Disk for QoS-aware Virtual Memory\u201d, IEEE ISPASS, Austin, TX, April 2013. (Best Paper Candidate)<\/li>\n
  36. Ajay Gulati, Ganesha Shanmuganathan, Xuechen Zhang<\/strong>, and Peter Varman, \u201dDemand Based Hierarchical QoS Using Storage Resource Pools\u201d, USENIX ATC, Boston, MA, June 2012. (Acceptance Rate: 17.8%)<\/li>\n
  37. Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201diTransformer: Using SSD to Improve Disk Scheduling for High-performance I\/O \u201d, IEEE IPDPS, Shanghai, China, May 2012. (Acceptance Rate: 21%)<\/li>\n
  38. Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201dOpportunistic Data-driven Execution of Parallel Programs for Efficient I\/O Services\u201d, IEEE IPDPS, Shanghai, China, May 2012. (Acceptance Rate: 21%)<\/li>\n
  39. Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201dQoS Support for End Users of I\/O-intensive Applications using Shared Storage Systems\u201d, ACM\/IEEE SC, Seattle, WA, November 2011. (Acceptance Rate: 21%)<\/li>\n
  40. Xuechen Zhang<\/strong>, Yuehai Xu, and Song Jiang, \u201dYouChoose: A Performance Interface Enabling Convenient and Efficient QoS Support for Consolidated Storage Systems \u201d, IEEE MSST, Denver, Colorado, May 2011. (Best Student Paper)<\/li>\n
  41. Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201dIOrchestrator: Improving the Performance of Multi-node I\/O Systems via Inter-Server Coordination\u201d, ACM\/IEEE SC, New Orleans, LA, November 2010. (Acceptance Rate: 20%)<\/li>\n
  42. Xuechen Zhang<\/strong> and Song Jiang, \u201dInterferenceRemoval: Removing Interference of Disk Access for MPI Programs through Data Replication\u201d, ACM ICS, Tsukuba, Japan, June 2010. (Acceptance Rate: 17.8%)<\/li>\n
  43. Lei Zhang, Guiquan Liu, Xuechen Zhang<\/strong>, and Song Jiang, \u201dStorage Device Performance Prediction with SBCART(Selective Bagging Classification and Regression Tree) Models\u201d, IFIP NPC, Zhengzhou, China, September 2010. (Acceptance Rate: 27%)<\/li>\n
  44. Xuechen Zhang<\/strong>, Guiquan Liu, and Song Jiang, \u201dImprove Throughput of Storage Cluster Interconnected with a TCP\/IP Network Using Intelligent Server Grouping\u201d, IFIP NPC, Zhengzhou, China, September 2010. (Best Paper Candidate)<\/li>\n
  45. Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201dMaking Resonance a Common Case: A High-performance Im- plementation of Collective I\/O on Parallel File Systems \u201d, IEEE IPDPS, Rome, Italy, May 2009. (Acceptance Rate: 21%)<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div><\/div>\n<\/section>\n
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    Refereed Journal Articles:<\/h2>\n<\/header>\n

     <\/p>\n

      \n
    1. Dang Zheng, Shuibing He, Xuechen Zhang<\/strong>, Peiyi Hong, Zhenxin Li, Xinyu Chen, Haozhe Song, Xian-He Sun, and Gang Chen, “PMAlloc: A Holistic Approach to Improving Persistent Memory Allocation”. ACM Transactions on Computer Systems (TOCS), 2024.<\/li>\n
    2. Siling Yang, Shuibing He, Hexiao Duan, Weijian Chen, Xuechen Zhang<\/strong>, Tong Wu, and Yanlong Yin, “APQ: Automated DNN Pruning and Quantization for ReRAM-based Accelerators”, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 34, no. 9, Sep. 2023.<\/li>\n
    3. Ping Chen, Shuibing He, Xuechen Zhang<\/strong>, Shuaiben Chen, Peiyi Hong, Yanlong Yin, and Xian-He Sun, “Accelerating Tensor Swapping in GPUs with Self-Tuning Compression”, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 33, issue 12, December 2022.<\/li>\n
    4. Soklong Lim, Tyler Coy, Zaixin Lu, Bin Ren, and Xuechen Zhang<\/strong>, “NVGRAPH: Enforcing Crash Consistency of Evolving Network Analytics in NVMM Systems”, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 31, no. 6, June 2020.<\/li>\n
    5. Shuibing He, Yanlong Yin, Xian-He Sun, Xuechen Zhang<\/strong>, Zongpeng Li, “Optimizing Parallel I\/O Accesses through Pattern-Directed and Layout-Aware Replication”. IEEE Transactions on Computers (TC),\u00a0 vol. 69, no. 2, February 2020.<\/span><\/li>\n
    6. Ian Kosen, Can Huang, Zhi Chen, Xuechen Zhang<\/strong>, Emma Stewart, Liang Min, Dao Zhou, Lin Zhu, and Yilu Liu. “UPS: Unified PMU-Data Storage System to Enhance T+D PMU Data Usability”. IEEE Transactions on Smart Grid (TSG), 2019. (Accepted)<\/li>\n
    7. Bao Nguyen, Hua Tan, Kei Davis, and\u00a0Xuechen Zhang.<\/strong>\u00a0\u201cPersistent Octrees for Parallel Mesh Refinement Through Non-Volatile Byte-Addressable Memory\u201d, IEEE Transactions on Parallel and Distributed Systems (TPDS),\u00a0Volume 30, Issue 3, March 2019.<\/li>\n
    8. Suman Karki, Bao Nguyen, Joshua Feener, Kei Davis, and Xuechen Zhang<\/strong>, “Enforcing End-to-end I\/O Policies for Scientific Workflows using Software-Defined Storage Resource Enclaves”,\u00a0IEEE Transactions on Multi-Scale Computing Systems (TMSCS), Volume 4, Issue 4, October-December 2018.<\/li>\n
    9. Xuechen Zhang<\/strong>, Fang Zheng, Bao Nguyen. “DeStager: Feature Guided In-Situ Data Management in Distributed Deep Memory Hierarchies”, Special Issue on Scientific and Statistical Database Management, Journal of Distributed and Parallel Databases (DAPD), Springer. (DOI: 10.1007\/s10619-018-7235-3)<\/li>\n
    10. Xuechen Zhang<\/strong>, Song Jiang, Alseny Diallo, and Lei Wang, “IR+: Removing Parallel I\/O Interference of MPI Programs through Data Replication on Heterogeneous Storage Devices”, Journal of Parallel Computing (ParCo), Elsevier, vol. 76, pages 91-105, 2018. (https:\/\/doi.org\/10.1016\/j.parco.2018.01.004)<\/li>\n
    11. Xuechen Zhang<\/strong>, Ujjwal Khanal, Xinghui Zhao, and Stephen Ficklin, “Making Sense of Performance in In-memory Computing Frameworks for Scientific Data Analysis: A Case Study of the Spark System”, Special issue on In-memory Computing, Journal of Parallel and Distributed Computing (JPDC), Elsevier (https:\/\/doi.org\/10.1016\/j.jpdc.2017.10.016).\u00a0<\/span><\/li>\n
    12. Kei Davis, Song Jiang, Xuechen Zhang<\/strong>, and Ke Liu, \u201dMaking Memory Swapping Practicable: Synergistic Coupling of SSD and Hard Disk for QoS-Aware Virtual Memory\u201d, ADTSC Science Highlights, Los Alamos, May 2012. LA-UR 13-20839.<\/li>\n
    13. Kei Davis, Xuechen Zhang<\/strong>, Ke Liu, and Song Jiang, \u201diBridge: Improving Unaligned Parallel File Access with Solid-State Drives\u201d, ADTSC Science Highlights, Los Alamos, May 2012. LA-UR 13-20839.<\/li>\n
    14. Kei Davis, Song Jiang, and Xuechen Zhang<\/strong>, \u201diTransformer:Using SSD to Improve Disk Scheduling for High-performance I\/O\u201d, ADTSC Science Highlights, Los Alamos, May 2012. LA-UR 12-20429.<\/li>\n
    15. Kei Davis, Song Jiang, and Xuechen Zhang<\/strong>, \u201dOpportunistic Data-driven Execution of Parallel Programs for Efficient I\/O Services\u201d, ADTSC Science Highlights, Los Alamos, May 2012. LA-UR 12-20429.<\/li>\n
    16. Xuechen Zhang<\/strong>, Yuehai Xu, and Song Jiang, \u201dYouChoose: Choosing your Storage Device as a Performance Interface to Consolidated I\/O Service\u201d, ACM Transactions on Storage, vol. 7, no. 3, article 8, October 2011.<\/li>\n
    17. Song Jiang, Xuechen Zhang<\/strong>, Shuang Liang, and Kei Davis, \u201dImproving Networked File System Performance Using a Locality-Aware Cooperative Cache Protocol\u201d, IEEE Transactions on Computers, vol. 59, no. 11, November 2010.<\/li>\n<\/ol><\/div>\n<\/section>\n
      \n
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      Refereed Workshop Publications:<\/h2>\n<\/header>\n
        \n
      1. Brian Koga, Theresa Vanderweide, Xinghui Zhao, and Xuechen Zhang<\/strong>. “BlinkNet: Software-Defined Deep Learning Analytics with Bounded Resources”. In Proceedings of 3rd Workshop on Accelerated Machine Learning (AccML) Co-located with European Network on High-performance Embedded Architecture and Compilation (HiPEAC’21), Online, January 2021.\u00a0<\/span><\/li>\n
      2. Tyler Coy and Xuechen Zhang<\/strong>, “Enforcing Crash Consistency of Scientific Applications in Non-Volatile Main Memory Systems, In Proceedings of the 9th Workshop on Fault Tolerance for HPC at eXtreme Scale” (FTXS’19) in conjunction with the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC’19).<\/li>\n
      3. Bao Nguyen, Hua Tan, Xuechen Zhang<\/strong>, and Kei Davis, “Large-Scale Adaptive Mesh Simulations Through Non-Volatile Byte-Addressable Memory”, 10th Annual Non-Volatile Memories Workshop, San Diego, CA, March 2019.<\/li>\n
      4. Xuechen Zhang<\/strong>, Hasan Abbasi, Kevin Huck, and Allen D. Malony, “WOWMON: A Machine Learning-based Profiler for Self-adaptive Instrumentation of Scientific Workflows”, International Conference on Computational Science Workshop – Tools for Program Development and Analysis in Computational Science, San Diego, CA, June 2016.<\/li>\n<\/ol><\/div>\n<\/section>\n
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        Refereed Poster Papers:<\/h2>\n<\/header>\n
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         <\/p>\n<\/div>\n<\/div>\n<\/div>\n

          \n
        1. Keegan Sanchez, Alex Gavin, Suren Byna, Kesheng Wu, and Xuechen Zhang<\/strong>, “PM-Aware Collective I\/Os”, SC’23, Denver, CO, November 2023.<\/li>\n
        2. Tyler Coy and Xuechen Zhang<\/strong>, \u00a0“Enforcing Crash Consistency of Scientific Applications in Non-Volatile Main Memory Systems”, SC’19, Denver, CO, November 2017.<\/span><\/li>\n
        3. Bao Nguyen, Tan Hua, and Xuechen Zhang<\/strong>, \u00a0“Large-scale Adaptive Mesh Simulations Through Non-Volatile Byte-Addressable Memory”, SC’17, Denver, CO, November 2017.<\/span><\/li>\n
        4. Swann Perarnau, Rinku Gupta, Pete Beckman\u00a0 with Xuechen Zhang<\/strong> and et al.,\u00a0“Argo: An Exascale Operating System and Runtime”, SC’15, Austin, TX, November 2015.<\/li>\n
        5. Jian Huang, Xuechen Zhang<\/strong>, Karsten Schwan, \u201dUnderstanding Issue Correlations: A Case Study of the Hadoop System\u201d, SOCC\u201915, Kohala Coast, HI, August 2015.<\/li>\n
        6. Jian Huang, Xuechen Zhang<\/strong>, Greg Eisenhauer, Karsten Schwan, Matthew Wolf, Stephane Ethier, and Scott Klasky, \u201dScibox: Online Sharing of Scientific Data via the Cloud\u201d, ACM\/IEEE SC\u201913, Denver, Colorado, November 2013.<\/li>\n
        7. Xuechen Zhang<\/strong>, Jianqiang Ou, Kei Davis, and Song Jiang, \u201dOrthrus: A Framework for Implementing High- performance Collective I\/O in the Multicore Clusters\u201d, ACM HPDC\u201913, New York, June 2013. (Acceptance Rate: 26%)<\/li>\n
        8. Xuechen Zhang<\/strong>, Kei Davis, and Song Jiang, \u201dQoS Support for End Users of I\/O-intensive Applications using Shared Storage Systems\u201d, ACM\/IEEE SC\u201911, Seattle, WA, November 2011.<\/li>\n
        9. Xuechen Zhang<\/strong>, Ajay Gulati, and Ganesha Shanmuganathan, \u201dStorage Resource Pools with IO Reservation\u201d, VMWorld, 2011.<\/li>\n<\/ol><\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"

          <\/p>\n

          Refereed Conference Publications:<\/h2>\n

          Rubayet Rongon and Xuechen Zhang. <\/strong>“iAUG: Accelerating Augmentation with Importance Sampling in Deep Neural Network Training”. In Proceedings of the 31st International European Conference on Parallel and Distributed Computing (EURO-PAR’25), Dresden, Germany, August 2025. (Acceptance Rate: 29%)
          Weijian Chen, Shuibing He, Haoyang Ou, and Xuechen Zhang<\/strong>. “LeapGNN: Accelerating Distributed GNN Training Leveraging Feature-Centric Model Migration”.\u00a0 In the 23rd USENIX Conference on File and Storage Technologies (FAST ’25), Santa Clara, CA, February 2025. (Acceptance Rate: 21.5%)
          Siling Yang, Shuibing He, Wenjiong Wang, Yanlong Yin, Tong Wu, Weijian Chen, Xuechen Zhang<\/strong>, Xina-He Sun, and Dan Feng, “GOPIM: GCN-Oriented Pipeline Optimization … » More …<\/span><\/a><\/p>\n","protected":false},"author":2132,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-builder.php","meta":{"_wsuwp_accessibility_report":[]},"wsuwp_university_location":[],"wsuwp_university_org":[],"_links":{"self":[{"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/pages\/30"}],"collection":[{"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/users\/2132"}],"replies":[{"embeddable":true,"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/comments?post=30"}],"version-history":[{"count":54,"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/pages\/30\/revisions"}],"predecessor-version":[{"id":425,"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/pages\/30\/revisions\/425"}],"wp:attachment":[{"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/media?parent=30"}],"wp:term":[{"taxonomy":"wsuwp_university_location","embeddable":true,"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/wsuwp_university_location?post=30"},{"taxonomy":"wsuwp_university_org","embeddable":true,"href":"https:\/\/vancouver.labs.wsu.edu\/xuechen-zhang\/wp-json\/wp\/v2\/wsuwp_university_org?post=30"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}