Feng Zhang     张 峰

Address: 427, Information Building, No. 59 Zhongguancun Street, Haidian District Beijing, 100872, P.R. China.
Email: fengzhang@ruc.edu.cn

Feng Zhang is a professor in Key Laboratory of Data Engineering and Knowledge Engineering and School of Information, Renmin University of China. Feng Zhang's research lies in the broad field of Heterogeneous Database Systems, Parallel and Distributed Computing, and Machine Learning. He leads the fengzi research group (subgroup of DBIIR).

Our group is looking for undergraduate interns and graduate students. If you are interested in database, parallel and distributed systems, please contact me.

Professional Activities:

PC for WWW'25, ICDE'25, IPDPS'25, VLDB'24, ICDE'24, KDD'24, WISE'24 (Publicity Co-Chair), KDD'23, USENIX ATC'23, BigData'23, SC'23 (Poster), CIKM'23, ECML-PKDD'23, CODS-COMAD'23, EDBT'23, HiPC'23, WISE'23 (PC Co-Chair), NDBC'23, HPC China'22, ICPADS'22, HiPC'22, CIKM'22, SIGKDD'22, CCGrid'22, WSDM'22, AAAI'22, BigData'22, CODS-COMAD'22, HiPC'21, BigData'21, Cluster'21, CCGrid'21, IPDPS'21, NPC'20, SBAC-PAD'20, ICPP'20, HiPC'20, PC for NPC'19, CIKM'19, HPC China'19, Publication Chair for NPC'18. PC for ICPADS'18, HPC China'18. External Reviewer for SC'18, ICS'18, ICPP'18.

AE for TPDS, FCS, and BDMA. Reviewer for TPDS, TKDE, TC, JPDC, FCS, TSC, The Journal of Supercomputing, JCST, ACM Computing Surveys, TNSE, TSUSC, SPE, J. Imaging, Parallel Computing, CCF THPC, TMC, and TCC.

Research Experience:

1.       April. 2016 ~ Nov. 2016: Visiting Scholar in Compiler Group, Computer Science, North Carolina State University. Advisor: Prof. Xipeng Shen.

2.       Aug. 2018 ~ Aug. 2018: Visiting Scholar in Database Group, School of Computing, National University of Singapore. Advisor: Prof. Bingsheng He.

3.       Mar. 2013 ~ Oct. 2013: Research Intern, Architecture Group, AMD.

Education Background:

1.       Sep. 2012 ~ Jul. 2017: PhD in Computer Science, Department of Computer Science and Technology, Tsinghua University. Advisor: Prof. Wenguang Chen and Prof. Jidong Zhai.

2.       Sep. 2008 ~ Jul. 2012: B.S. in School of Computer Science and Technology, Xidian University.

Publication:

[SIGMOD’25] “Tribase: A Vector Data Query Engine for Reliable and Lossless Pruning Compression using Triangle Inequalities”, Qian Xu, Juan Yang, Feng Zhang, Junda Pan, Kang Chen, Youren Shen, Amelie Chi Zhou, Xiaoyong Du. SIGMOD 2025.

[SIGMOD’25] “Enabling Adaptive Sampling for Intra-Window Join: Simultaneously Optimizing Quantity and Quality”, Xilin Tang, Feng Zhang, Shuhao Zhang, Yani Liu, Bingsheng He, Xiaoyong Du. SIGMOD 2025.

[ASPLOS’24] “RECom: A Compiler Approach to Accelerating Recommendation Model Inference with Massive Embedding Columns”, Zaifeng Pan, Zhen ZHENG, Feng Zhang, Ruofan Wu, Hao Liang, Dalin Wang, Xiafei Qiu, Junjie Bai, Wei Lin, Xiaoyong Du. ASPLOS 2024.

[SIGMOD’24] “Homomorphic Compression: Making Text Processing on Compression Unlimited”, JiaWei Guan, Feng Zhang, Siqi Ma, Kuangyu Chen, Yihua Hu, Yuxing Chen, Anqun Pan, Xiaoyong Du. SIGMOD 2024.

[SIGMOD’24] “BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach”, Zhen Zheng, Zaifeng Pan, Dalin Wang, Kai Zhu, Wenyi Zhao, Tianyou Guo, Xiafei Qiu, Minmin Sun, Junjie Bai, Feng Zhang, Xiaoyong Du, Jidong Zhai, Wei Lin. SIGMOD 2024.

[VLDB’24] “Improving Graph Compression for Efficient Resource-Constrained Graph Analytics”, Qian Xu, Juan Yang, Feng Zhang, et al. VLDB 2024.

[VLDB’24] “Enabling Window-Based Monotonic Graph Analytics with Reusable Transitional Results for Pattern-Consistent Queries”, Zheng Chen, Feng Zhang, Yang Chen, Xiaokun Fang, Guanyu Feng, Xiaowei Zhu, Wenguang Chen, Xiaoyong Du. VLDB 2024.

[VLDB’24] “TDSQL: Tencent Distributed Database System”, Yuxing Chen, Anqun Pan, Hailin Lei, Anda Ye, Shuo Han, Yan Tang, Wei Lu, Yunpeng Chai, Feng Zhang, Xiaoyong Du. VLDB 2024.

[VLDB’24 (demo)] “HocoPG: A Database System with Homomorphic Compression for Text Processing”, Jiawei Guan, Feng Zhang, Yuxin Tang, Weitang Ye, Xiaoyong Du. VLDB (demo) 2024.

[ICDE’24] “Enabling Efficient NVM-Based Text Analytics without Decompression”, Xiaokun Fang, Feng Zhang, Junxiang Nong, Mingxing Zhang, Puyun Hu, Yunpeng Chai, Xiaoyong Du. ICDE 2024.

[ICDE’24] “F-TADOC: FPGA-Based Text Analytics Directly on Compression with HLS”, Yanliang Zhou, Feng Zhang, Tuo Lin, Yuanjie Huang, Saiqin Long, Jidong Zhai, Xiaoyong Du. ICDE 2024.

[ICDE’24] “Xorbits: Automating Operator Tiling for Distributed Data Science”, Weizheng Lu, Kaisheng He, Xuye Qin, Chengjie Li, Zhong Wang, Tao Yuan, Xia Liao, Feng Zhang, Yueguo Chen, Xiaoyong Du. ICDE 2024.

[SC’24] “RecFlex: Enabling Feature Heterogeneity-Aware Optimization for Deep Recommendation Models with Flexible Schedules”, Zaifeng Pan, Zhen Zheng, Feng Zhang, Bing Xie, Ruofan Wu, Shaden Smith, Chuanjie Liu, Olatunji Ruwase, Xiaoyong Du, Yufei Ding. SC 2024.

[NeurIPS’24] “UQ-Guided Hyperparameter Optimization for Iterative Learners”, Jiawei Guan, Feng Zhang, Jiesong Liu, Xipeng Shen. NeurIPS, 2024.

[TC’24] “Enabling Efficient Deep Learning on MCU with Transient Redundancy Elimination”, Jiesong Liu, Feng Zhang, Jiawei Guan, Hsin-Hsuan Sung, Xiaoguang Guo, Saiqin Long, Xiaoyong Du, Xipeng Shen. TC 2024.

[TPDS’24] “G-Learned Index: Enabling Efficient Learned Index on GPU”, Jiesong Liu, Feng Zhang, Lv Lu, Chang Qi, Xiaoguang Guo, Dong Deng, Guoliang Li, Huanchen Zhang, Jidong Zhai, Hechen Zhang, Yuxing Chen, Anqun Pan, Xiaoyong Du. TPDS 2024.

[TPDS’24] “Graph-Centric Performance Analysis for Large-Scale Parallel Applications”, Yuyang Jin, Haojie Wang, Runxin Zhong, Chen Zhang, Xia Liao, Feng Zhang, Jidong Zhai. TPDS 2024.

[TKDE’24] “Data-Aware Adaptive Compression for Stream Processing”, Yu Zhang, Feng Zhang, Hourun Li, Shuhao Zhang, Xiaoguang Guo, Yuxing Chen, Anqun Pan, Xiaoyong Du. TKDE 2024.

[VLDBJ’24] “GPU-Based Butterfly Counting”, Yifei Xia, Feng Zhang, Qingyu Xu, Mingde Zhang, Zhiming Yao, Lv Lu, Xiaoyong Du, Dong Deng, Bingsheng He, Siqi Ma. VLDBJ 2024.

[Computer Science’24] “ Cross-domain Data Management”, DU Xiaoyong, LI Tong, LU Wei, FAN Ju, ZHANG Feng, CHAI Yunpeng. Computer Science, 2024, 51(1): 4-12. (杜小勇, 李彤, 卢卫, 范举, 张峰, 柴云鹏. 跨域数据管理[J]. 计算机科学)

[EMNLP’24 (Demo)] “ Xinference: Making Large Model Serving Easy”, Weizheng Lu, Lingfeng Xiong, Feng Zhang, Xuye Qin, Yueguo Chen. EMNLP demo, 2024.

[TPDS’23] “Compressed Data Direct Computing for Databases”, Weitao Wan, Feng Zhang, Chenyang Zhang, Mingde Zhang, Jidong Zhai, Yunpeng Chai, Huanchen Zhang, Wei Lu, Yuxing Chen, Haixiang Li, Anqun Pan, Xiaoyong Du. TPDS 2023.

[TC’23] “Optimizing DNNs with Partially Equivalent Transformations and Automated Corrections”, Haojie Wang, Jidong Zhai, Mingyu Gao, Feng Zhang, Tuowei Wang, Zixuan Ma, Shizhi Tang, Liyan Zheng, Wen Wang, Kaiyuan Rong, Yuanyong Chen, Zhihao Jia. TC 2023.

[TPDS’23] “Enabling Efficient Random Access to Hierarchically Compressed Text Data on Diverse GPU Platforms”, Yihua Hu, Feng Zhang, Yifei Xia, Zhiming Yao, Letian Zeng, Haipeng Ding, Zhewei Wei, Xiao Zhang, Jidong Zhai, Xiaoyong Du, Siqi Ma. TPDS 2023.

[DAC’23 POSTER] “Enabling Efficient NVM-Based Text Analytics without Decompression”, Xiaokun Fang, Feng Zhang, Junxiang Nong, Mingxing Zhang, Puyun Hu, Yunpeng Chai, Xiaoyong Du. DAC 2023.

[CCF THPC’23] “Compressed Data Direct Computing for Chinese Dataset on DCU”, Yani Liu, Feng Zhang, Zaifeng Pan, Xiaoguang Guo, Yihua Hu, Xiao Zhang, and Xiaoyong Du. CCF THPC 2023.

[TKDE’23] “Expanding the Edge: Enabling Efficient Winograd CNN Inference with Deep Reuse on Edge Device”, Feng Zhang, Ruofan Wu, Jiawei Guan, Zhen Zheng, Xiaoguang Guo, Xiao Zhang, Xiaoyong Du, Xipeng Shen. TKDE 2023.

[DASFAA’23] “Efficient Anomaly Detection in Property Graphs”, Jiamin Hou, Yuhong Lei, Zhe Peng, Wwe Lu, Feng Zhang, Xiaoyong Du. DASFAA 2023.

[ASPLOS’23] “Space-Efficient TREC for Enabling Deep Learning on Microcontrollers”, Jiesong Liu, Feng Zhang, Jiawei Guan, Hsin-Hsuan Sung, Xiaoguang Guo, Xiaoyong Du, Xipeng Shen. ASPLOS 2023.

[ICDE’23] “CompressStreamDB: Fine-Grained Adaptive Stream Processing without Decompression”, Yu Zhang, Feng Zhang, Hourun Li, Shuhao Zhang, Xiaoyong Du. IEEE International Conference on Data Engineering (ICDE 2023).

[SIGMOD’23] “CompressGraph: Efficient Parallel Graph Analytics with Rule-Based Compression”, Zheng Chen, Feng Zhang, JiaWei Guan, Jidong Zhai, Xipeng Shen, Huanchen Zhang, Wentong Shu, Xiaoyong Du. SIGMOD, 2023.

[ICDE’23] “EdgeNN: Efficient Neural Network Inference for CPU-GPU Integrated Edge Devices”, Chenyang Zhang, Feng Zhang, Kuangyu Chen, Mingjun Chen, Bingsheng He, Xiaoyong Du. ICDE, 2023.

[SBACPAD’22] “Taming the Big Data Monster: Managing Petabytes of Data with Multi-Model Databases”, Yang Chen, Feng Zhang, et al. SBACPAD, 2022.

[CCCF’22] “跨域数据管理的内涵与挑战”, 柴云鹏, 李彤, 范举, 卢卫, 张峰, & 杜小勇. 中国计算机学会通讯, 18(11), 29-33, 2022.

[DSE’22] “An Adaptive Elastic Multi-Model Big Data Analysis and Information Extraction System”, Qiang Yin, Jianhua Wang, Sheng Du, Jianquan Leng, Jintao Li, Yinhao Hong, Feng Zhang, Yunpeng Chai, Xiao Zhang, Xiaonan Zhao, Mengyu Li, Song Xiao, Wei Lu. Data Science and Engineering, 2022.

[NeurIPS’22] “TREC: Transient Redundancy Elimination-based Convolution”, Jiawei Guan, Feng Zhang, Jiesong Liu, Hsin-Hsuan Sung, Ruofan Wu, Xiaoyong Du, Xipeng Shen. NeurIPS, 2022.

[VLDB’22] “Efficient Load-Balanced Butterfly Counting on GPU”, Qingyu Xu, Feng Zhang, Zhiming Yao, Lv Lu, Xiaoyong Du, Dong Deng, Bingsheng He. PVLDB, 2022.

[SC’22] “Optimizing Random Access to Hierarchically-Compressed Data on GPU”, Feng Zhang, Yihua Hu, Haipeng Ding, Zhiming Yao, Zhewei Wei, Xiao Zhang, Xiaoyong Du. SC, 2022.

[TPDS’22] “Detecting Performance Variance for Parallel Applications without Source Code”, Jidong Zhai, Liyan Zheng, Feng Zhang, Xiongchao Tang, Haojie Wang, Teng Yu, Yuyang Jin, Shuaiwen Leon Song, Wenguang Chen. TPDS, 2022.

[TPDS’22] “Exploring Query Processing on CPU-GPU Integrated Edge Device”, Jiesong Liu, Feng Zhang, Hourun Li, Dalin Wang, Weitao Wan, Xiaokun Fang, Jidong Zhai, Xiaoyong Du. TPDS, 2022.

[WoWMoM’22] “An In-depth Analysis of Subflow Degradation for Multi-path TCP on High Speed Rails”, Tong Li, Li Li, Xiangxiang Wang, Xu Zhang, Feng Zhang, Kao Wan. WoWMoM, 2022.

[SIGMOD’22] “CompressDB: Enabling Efficient Compressed Data Direct Processing for Various Databases”, Feng Zhang, Weitao Wan, Chenyang Zhang, Jidong Zhai, Yunpeng Chai, Haixiang Li, Xiaoyong Du. SIGMOD, 2022.

[TPDS’22] “Leveraging Code Snippets to Detect Variations in the Performance of HPC Systems”, Jidong Zhai, Liyan Zheng, Jinghan Sun, Feng Zhang, Xiongchao Tang, Xuehai Qian, Bingsheng He, Wei Xue, Wenguang Chen, Weimin Zheng. TPDS, 2022.

[WWW’22] “DREW: Efficient Winograd CNN Inference with Deep Reuse”, Ruofan Wu, Feng Zhang, Jiawei Guan, Zhen Zheng, Xipeng Shen, Xiaoyong Du. The Web Conference, 2022.

[VLDBJ’22] “Payment Behavior Prediction on Shared Parking Lots with TR-GCN”, Qingyu Xu, Feng Zhang, Mingde Zhang, Jidong Zhai, Bingsheng He, Cheng Yang, huhao Zhang, Jiazao Lin, Haidi Liu, Xiaoyong Du. VLDB Journal, 2022.

[TPDS’22] “POCLib: A High-Performance Framework for Enabling Near Orthogonal Processing on Compression”, Feng Zhang, Jidong Zhai, Xipeng Shen, Onur Mutlu, Xiaoyong Du. TPDS, 2022.

[Journal of Computer’21] “Evaluation and Optimization for Huawei Ascend Neural Network Accelerator”, Weizheng Lu, Feng Zhang, Yinxuan He, Yueguo Chen, Jidong Zhang, Xiaoyong Du. Journal of Software, 2021(华为昇腾神经网络加速器性能评测与优化,计算机学报).

[TPDS’21] “Exploring Data Analytics without Decompression on Embedded GPU Systems”, Zaifeng Pan, Feng Zhang, Yanliang Zhou, Jidong Zhai, Xipeng Shen, Onur Mutlu, Xiaoyong Du. TPDS, 2021.

[CLUSTER’21] “FineQuery: Fine-Grained Query Processing on CPU-GPU Integrated Architectures”, Dalin Wang, Feng Zhang, Hourun Li, Weitao Wan, Xiaoyong Du. IEEE CLUSTER, 2021.

[TPDS’21] “G-SLIDE: A GPU-Based Sub-Linear Deep Learning Engine via LSH Sparsification”, Zaifeng Pan, Feng Zhang, Hourun Li, Chenyang Zhang, Xiaoyong Du, Dong Deng. TPDS, 2021.

[TPDS’21] “Fine-Grained Multi-Query Stream Processing on Integrated Architectures”, Feng Zhang, Chenyang Zhang, Lin Yang, Shuhao Zhang, Bingsheng He, Wei Lu, Xiaoyong Du. TPDS, 2021.

[TKDE’21] “Periodic Weather-Aware LSTM with Event Mechanism for Parking Behavior Prediction”, Feng Zhang, Yani Liu, Ningxuan Feng, Cheng Yang, Jidong Zhai, Shuhao Zhang, Bingsheng He, Jiazao Lin, Xiao Zhang, Xiaoyong Du. IEEE Transactions on Knowledge and Data Engineering, 2021 (TKDE 2021).

[TPDS’21] “DTransE: Distributed Translating Embedding for Knowledge Graph”, Dandan Song, Feng Zhang, Meiyan Lu, Sicheng Yang, Heyan Huang. IEEE Transactions on Parallel and Distributed Systems, 2021 (TPDS 2021).

[TPDS’21] “YuenyeungSpTRSV: A Thread-Level and Warp-Level Fusion Synchronization-Free Sparse Triangular Solve”, Feng Zhang, Jiya Su, Weifeng Liu, Bingsheng He, Ruofan Wu, Xiaoyong Du, Rujia Wang. IEEE Transactions on Parallel and Distributed Systems, 2021 (TPDS 2021).

[ICDE’21] “G-TADOC: Enabling Efficient GPU-Based Text Analytics without Decompression”, Feng Zhang, Zaifeng Pan, Yanliang Zhou, Jidong Zhai, Xipeng Shen, Onur Mutlu, Xiaoyong Du. 37th IEEE International Conference on Data Engineering (ICDE 2021).

[TPDS’21] “An Efficient Parallel Secure Machine Learning Framework on GPUs”, Feng Zhang, Zheng Chen, Chenyang Zhang, Amelie Chi Zhou, Jidong Zhai, Xiaoyong Du. IEEE Transactions on Parallel and Distributed Systems, 2021 (TPDS 2021).

[PPoPP’21] “POSTER: Exploring Deep Reuse in Winograd CNN Inference”, Ruofan Wu, Feng Zhang, Zhen Zheng, Xiaoyong Du, Xipeng Shen. 26th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, Seoul, S. Korea (PPoPP 2021).

[TPDS’20] “iMLBench: A Machine Learning Benchmark Suite for CPU-GPU Integrated Architectures”, Chenyang Zhang, Feng Zhang, Xiaoguang Guo, Bingsheng He, Xiao Zhang, and Xiaoyong Du. IEEE Transactions on Parallel and Distributed Systems, 2020.

[NPC’20] “Payment Behavior Prediction and Statistical Analysis for Shared Parking Lots”, Qingyu Xu, Feng Zhang, Mingde Zhang, Jidong Zhai, Jiazao Lin,Haidi Liu, Xiaoyong Du. International Conference on Network and Parallel Computing (NPC 2020).

[VLDBJ’20] “TADOC: Text Analytics Directly on Compression”, Feng Zhang, Jidong Zhai, Xipeng Shen, Dalin Wang, Zheng Chen, Onur Mutlu, Wenguang Chen, Xiaoyong Du. VLDB Journal.

[ICPP’20] “CapelliniSpTRSV: A Thread-Level Synchronization-Free Sparse Triangular Solve on GPUs”, Jiya Su, Feng Zhang, Weifeng Liu, Bingsheng He, Ruofan Wu, Xiaoyong Du, Rujia Wang. The 49th International Conference on Parallel Processing (ICPP 2020), 17-20 August 2020, Edmonton, AB, Canada.

[ICPP’20] “ParSecureML: An Efficient Parallel Secure Machine Learning Framework on GPUs”, Zheng Chen, Feng Zhang, Amelie Chi Zhou, Jidong Zhai, Chenyang Zhang, Xiaoyong Du. The 49th International Conference on Parallel Processing (ICPP 2020), 17-20 August 2020, Edmonton, AB, Canada.

[Journal of Software’20] “Survey on Performance Analysis, Optimization, and Applications of Heterogeneous Fusion Processors”, Feng Zhang, Jidong Zhai, Zheng Chen, Jiazao Lin, Xiaoyong Du. Journal of Software, 2020 (面向异构融合处理器的性能分析、优化及应用综述, 软件学报).

[USENIX ATC’20] “FineStream: Fine-Grained Window-Based Stream Processing on CPU-GPU Integrated Architectures”, Feng Zhang, Lin Yang, Shuhao Zhang, Bingsheng He, Wei Lu, Xiaoyong Du. USENIX ATC, September 2020.

[IJCAI’20] “PewLSTM: Periodic LSTM with Weather-Aware Gating Mechanism for Parking Behavior Prediction”, Feng Zhang, Ningxuan Feng, Yani Liu, Cheng Yang, Jidong Zhai, Shuhao Zhang, Bingsheng He, Jiazao Lin, Xiaoyong Du. IJCAI, July 2020.

[ICDCS’20] “Exploration of TransE in a Distributed Environment”, Meiyan Lu, Dandan Song, Feng Zhang, Lejian Liao. ICDCS Poster, July 2020.

[SIGMOD Record’20] “Hardware-Conscious Stream Processing: A Survey”, Shuhao Zhang, Feng Zhang, Yingjun Wu, Bingsheng He, Paul Johns. ACM SIGMOD Record, February 2020.[PDF]

[TPDS’20] “Modeling Analysis and Cost-performance Ratio Optimization of Virtual Machine Scheduling in Cloud Computing”, Bo Wan, Jiale Dang, Zhetao Li, Hongfang Gong, Feng Zhang, Sangyoon Oh. IEEE Transactions on Parallel and Distributed Systems, 2020.

[ICDE’20] “Towards Concurrent Stateful Stream Processing on Multicore Processors”, Shuhao Zhang, Yingjun Wu, Feng Zhang, Bingsheng He. IEEE ICDE, 2020.

[ICDE’20] “Enabling Efficient Random Access to Hierarchically-Compressed Data”, Feng Zhang, Jidong Zhai, Xipeng Shen, Onur Mutlu, and Xiaoyong Du. IEEE ICDE, 2020.[PDF][SLIDES][VIDEO]

[TKDE’19] “Automatic Irregularity-Aware Fine-Grained Workload Partitioning on Integrated Architectures”, Feng Zhang, Jidong Zhai, Bo Wu, Bingsheng He, Wenguang Chen, Xiaoyong Du. IEEE Transactions on Knowledge and Data Engineering, September 1, 2019.

[NPC’19] “Statistical Analysis and Prediction of Parking Behavior”, Ningxuan Feng, Feng Zhang, Jiazao Lin, Jidong Zhai, Xiaoyong Du. The 16th IFIP International Conference on Network and Parallel Computing (NPC 2019), August 23–24, 2019, Inner Mongolia, China.

[ICPP’19] “Distributed Join Algorithms on Multi-GPU Clusters with GPUDirect RDMA”, Chengxin Guo, Hong Chen, Feng Zhang, Cuiping Li. The 48th International Conference on Parallel Processing (ICPP 2019), August 5–8, 2019, Kyoto, Japan.

[CCF THPC’19] “Performance evaluation and analysis of sparse matrix and graph kernels on heterogeneous processors”, Feng Zhang, Weifeng Liu, Ningxuan Feng, Jidong Zhai, Xiaoyong Du. CCF Transactions on High Performance Computing, 2019. [PDF]

[HPCC’19] “Parallel Hybrid Join Algorithm on GPU”, Chengxin Guo, Hong Chen, Feng Zhang, Cuiping Li. The 21st IEEE International Conference on High Performance Computing and Communications (HPCC 2019), August 10–12, 2019, Zhangjiajie, China.

[Journal of Software’19] “History, Present, and Future of Big Data Management Systems”, Xiaoyong Du, Wei Lu, Feng Zhang. Journal of Software, 2019(大数据管理系统的历史、现状与未来,软件学报).

[VLDB’18] “Efficient Document Analytics on Compressed Data: Method, Challenges, Algorithms, Insights”, Feng Zhang, Jidong Zhai, Xipeng Shen, Onur Mutlu, and Wenguang Chen. The 44th International Conference on Very Large Data Bases, Rio de Janeiro, Brazil, August 27-31, 2018. [PDF]

[ICS’18] “Zwift: A Programming Framework for High Performance Text Analytics on Compressed Data”, Feng Zhang, Jidong Zhai,Xipeng Shen, Onur Mutlu, and Wenguang Chen. The 32nd ACM International Conference on Supercomputing, Beijing, China, June 12-15, 2018. [PDF]

[TJSC’18] “An Adaptive Breadth-First Search Algorithm on Integrated Architectures”, Feng Zhang, Heng Lin, Jidong Zhai, Jie Cheng, Dingyi Xiang, Jizhong Li, Yunpeng Chai, Xiaoyong Du. The Journal of Supercomputing, 2018. [PDF]

[CGO’17] “FinePar: Irregularity-Aware Fine-Grained Workload Partitioning on Integrated Architectures”, Feng Zhang, Jidong Zhai, Wenguang Chen, Bingsheng He and Shuhao ZhangHe. Proceedings of the 2017 International Symposium on Code Generation and Optimization. IEEE Press, 2017: 27-38.  [PDF]

[TPDS’17] “Understanding Co-running Behaviors on Integrated CPU/GPU Architectures”, Feng Zhang, Jidong Zhai, Bingsheng He, Shuhao Zhang, Wenguang Chen. IEEE Transactions on Parallel and Distributed Systems, 2017, 28(3): 905-918.  [CODE] [PDF]

[SCIS’16] “Characterizing and optimizing TPC-C workloads on large-scale systems using SSD arrays”, ZHAI JiDong, ZHANG Feng, LI QingWen, CHEN WenGuang, ZHENG WeiMin. SCIENCE CHINA Information Sciences, 2016, 59(9): 92104.  [PDF]

[MASCOTS’15] “To Co-Run, or Not To Co-Run: A Performance Study on Integrated Architectures”, Feng Zhang, Jidong Zhai, Wenguang Chen, Bingsheng He and Shuhao Zhang. IEEE 23nd International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, October 5-7, 2015, Atlanta, GA, USA. [CODE] [PDF]

[ICPPW’15] “HPC-Oriented Power Evaluation Method”, Feng Zhang, and Liang Chen. IEEE 44th International Conference on Parallel Processing Workshops, September 1-4, 2015, Beijing, China. [PDF]

[APSys’14] “Implementation and Evaluation of Deep Neural Networks (DNN) on Mainstream Heterogeneous Systems”, Junli Gu, Maohua Zhu, Zhitao Zhou, Feng Zhang, Zhen Lin, Qianfeng Zhang, Mauricio Breternitz. Proceedings of 5th Asia-Pacific Workshop on Systems, ACM, June 25-26, 2014, Beijing, China.  [PDF]

Awards:

- ICDE 2024 Industrial and Application Best Paper runner up.

- Distinguished Artifact Awards in the ASPLOS Fall'23 cycle.

- 2022 Best Paper Runner-up for IEEE Transaction on Parallel and Distributed Systems.

- 2021 Best Paper for IEEE Transaction on Parallel and Distributed Systems.

- 2020 ACM CHINA COUNCIL SIGHPC CHAPTER RISING STAR AWARD.