程大釗
437bwin必贏國際官網 計算機科學系 人工智能研究所 教授 (博導)
姓名：程大釗 主頁： 性別：男 職稱：教授 (博導,) 學歷學位：博士 電話：027-68776120 辦公地點：437bwin必贏國際官網E401 E-mail：dcheng ▇ whu.edu.cn 請手工替換符號 領域：并行分布計算,高性能計算,人工智能,云計算與大數據處理,智能計算, 招生信息：年度招收碩士0名，招收方向：。 招收博士0名，招收方向：。
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研究方向
程大釗，437bwin必贏國際官網 教授、博導。主要從事存算一體化、分布式計算等方面的研究工作，近期致力于研究面向人工智能負載的新型存內計算架構，具有豐富的計算機系統研究基礎和經驗。先后入選為湖北省“百人計劃”特聘教授，“武漢英才”創新人才。同時，擔任437bwin必贏國際官網副院長，CCF分布式計算與系統專委會常務委員、國家重點研發計劃和基金委重點項目首席科學家。2016-2020年在美國北卡大學計算機系擔任Tenure Track助理教授，曾擔任國家科技部、廣東省和湖北省科技廳重點項目、美國和加拿大國家科學基金等評審專家。在權威計算機系統領域的期刊和會議上發表論文50篇并申請專利10多項，其中第一/通訊作者發表30余篇（含CCF A類20余篇）。先后主持了國家重點研發計劃1項、國家自然科學基金委重點項目1項，美國NSF面上項目2項和其它省部級項目若干，共主持過科研項目經費約1700萬元。同時應邀在多個國際國內學術組織中任職，擔任4個學術期刊客座編委，5個國際會議的主席，28個國際會議的技術委員會委員。
實驗室主頁：icslab.whu.edu.cn
歡迎對分布式系統和AI System感興趣的同學加入，有意向者請把簡歷、成績單和專業排名發郵件至：dcheng@whu.edu.cn ！
教育背景
(1) 2011-8至2016-5, 美國科羅拉多大學, 計算機科學, 博士
(2) 2006-9至2009-6, 中國科學技術大學, 模式識別與人工智能，碩士
(3) 2002-9至2006-6, 合肥工業大學, 自動化, 學士
工作經驗
(1) 2020-9至現在, 437bwin必贏國際官網, 437bwin必贏國際官網, 教授
(2) 2016-7至2020-9, 美國北卡羅來納大學, 計算機科學系, 助理教授
教授課程
《大數據分析與處理》。
發表論文
§ 期刊論文
[1] T Li; Z Qiu; D Cheng; W Wang; X Shi; Y Wang*: Privacy-Preserving Participant Grouping for Mobile Social Sensing over Edge Clouds. IEEE Transactions on Network Science and Engineering (TNSE), 2021.
[2] D Cheng; Y Wang; D Dai*: Dynamic Resource Provisioning for Iterative Workloads on Apache Spark. IEEE Transactions on Cloud Computing (TCC), 2021.（SCI一區）
[3] W Rang; D Yang; D Cheng*: Dependency-aware Tensor Scheduler for Industrial AI Applications. IEEE Industrial Electronics Magazine (IEM), 2021.（SCI一區）
[4] W Rang; D Yang; D Cheng*: Yu Wang; Data Life Aware Model Updating Strategy for Stream-based Online Deep Learning. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2021.（CCF A類）
[5] D Yang, D Cheng*, W Rang, Y Wang: Joint Optimization of MapReduce Scheduling and Network Policy in Hierarchical Data Centers. IEEE Transactions on Cloud Computing (TCC), 2019.（SCI一區）
[6] D Cheng*, X Zhou, Y Xu, L Liu, C Jiang: Deadline-aware MapReduce job scheduling with dynamic resource availability. IEEE transactions on parallel and distributed systems (TPDS), 2018:30 (4), 814-826.（CCF A類）
[7] D Cheng*, X Zhou, Z Ding, Y Wang, M Ji: Heterogeneity aware workload management in distributed sustainable datacenters. IEEE Transactions on Parallel and Distributed Systems (TPDS),2018:30 (2), 375-387.（CCF A類）
[8] D Cheng*, X Zhou, Y Wang, C Jiang: Adaptive scheduling parallel jobs with dynamic batching in spark streaming. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2018:29 (12), 2672-2685.（CCF A類）
[9] D Cheng*, X Zhou, P Lama, M Ji, C Jiang: Energy efficiency aware task assignment with dvfs in heterogeneous hadoop clusters. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2017:29 (1), 70-82.（CCF A類）
[10] D Cheng, X Zhou*, P Lama, J Wu, C Jiang: Cross-platform resource scheduling for spark and mapreduce on yarn. IEEE Transactions on Computers (TC). 2017:66 (8), 1341-1353.（CCF A類）
[11] D Cheng, J Rao, Y Guo, C Jiang, X Zhou*: Improving performance of heterogeneous mapreduce clusters with adaptive task tuning. IEEE Transactions on Parallel and Distributed Systems (TPDS), 2016:28 (3), 774-786.（CCF A類）
[12] Y Guo, J Rao, D Cheng, X Zhou*: ishuffle: Improving hadoop performance with shuffle-on-write. IEEE transactions on parallel and distributed systems (TPDS), 2016:28 (6), 1649-1662.
[13] D Cheng, J Rao, C Jiang, X Zhou*: Elastic power-aware resource provisioning of heterogeneous workloads in self-sustainable datacenters. IEEE Transactions on Computers (TC). 2015:65 (2), 508-521.（CCF A類）
[14] D Cheng, Y Guo, C Jiang, X Zhou*: Self-tuning batching with dvfs for performance improvement and energy efficiency in internet servers. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 2015:10 (1), 1-32.
§ 會議論文
[1] W Rang, D Yang, D Cheng: A Shared Memory Cache Layer across Multiple Executors in Apache Spark.2020 IEEE International Conference on Big Data (Big Data), 477-482.
[2] D Yang, W Rang, D Cheng: Mitigating Stragglers in the Decentralized Training on Heterogeneous Clusters.Proceedings of the 21st International Middleware Conference (Middleware), 386-399.
[3] W Rang, D Yang, D Cheng*, K Suo, W Chen: Data Life Aware Model Updating Strategy for Stream-based Online Deep Learning.2020 IEEE International Conference on Cluster Computing (CLUSTER), 392-398.
[4] K Suo, Y Shi, X Xu, D Cheng, W Chen:Tackling Cold Start in Serverless Computing with Container Runtime Reusing.Proceedings of the Workshop on Network Application Integration/CoDesign, 54-55.
[5] D Yang, D Cheng: Efficient gpu memory management for nonlinear dnns. Proceedings of the 29th International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 185-196.
[6] J Tian, S Di, C Zhang, X Liang, S Jin, D Cheng, D Tao*, F Cappello: Wavesz: A hardware-algorithm co-design of efficient lossy compression for scientific data. Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), 74-88.
[7] D Yang, W Rang, D Cheng, Y Wang, J Tian, D Tao:Elastic Executor Provisioning for Iterative Workloads on Apache Spark. 2019 IEEE International Conference on Big Data (Big Data), 413-422.
[8] TBG Perez, X Zhou, D Cheng: Reference-distance eviction and prefetching for cache management in spark. Proceedings of the 47th International Conference on Parallel Processing (ICPP), 1-10 12.
[9] D Yang, W Rang, D Cheng: Joint optimization of mapreduce scheduling and network policy in hierarchical clouds. Proceedings of the 47th International Conference on Parallel Processing (ICPP), 1-10.
[10] P Lama, S Wang, X Zhou, D Cheng: Performance isolation of data-intensive scale-out applications in a multi-tenant cloud. 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 85-94.
[11] D Cheng, Y Chen, X Zhou, D Gmach, D Milojicic: Adaptive scheduling of parallel jobs in spark streaming. IEEE INFOCOM 2017-IEEE Conference on Computer Communicationsc(INFOCOM), 1-9.（CCF A類）
[12] D Cheng, P Lama, C Jiang, X Zhou: Towards energy efficiency in heterogeneous hadoop clusters by adaptive task assignment. 2015 IEEE 35th International Conference on Distributed Computing Systems (ICDCS). 359-368.
[13] D Cheng, J Rao, C Jiang, X Zhou: Resource and deadline-aware job scheduling in dynamic hadoop clusters. 2015 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 956-965.
[14] Y Guo, J Rao, D Cheng, C Jiang, CZ Xu, X Zhou: Storeapp: A shared storage appliance for efficient and scalable virtualized hadoop clusters. 2015 IEEE Conference on Computer Communications (INFOCOM), 594-602.
[15] D Cheng, J Rao, Y Guo, X Zhou: Improving mapreduce performance in heterogeneous environments with adaptive task tuning. Proceedings of the 15th International Middleware Conference (Middleware), 97-108.
[16] D Cheng, C Jiang, X Zhou: Heterogeneity-aware workload placement and migration in distributed sustainable datacenters. 2014 IEEE 28th International Parallel and Distributed Processing Symposium (IPDPS), 307-316.
[17] D Cheng, Y Guo, X Zhou: Self-tuning batching with dvfs for improving performance and energy efficiency in servers. 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS),40-49.
科研課題
1.美國自然科學基金委員會，面上項目2項；
2.北卡萊羅納州科研基金委員會，青年基金項目1項。
研究團隊
2020年9月至今，在437bwin必贏國際官網擔任教授期間，已組建了擁有4名博士和5名碩士研究生的科研團隊。
知識產權
[1] Y Chen, DS Milojicic, D Cheng: Managing data processing resources. US Patent 10,037,230
學術服務
IEEE Transactions on Cloud Computing (TOC) 審稿人
IEEE Transactions on Parallel and Distributed Systems (TPDS) 審稿人
IEEE Conference on Computer Communications (INFOCOM’14,15,16) 審稿人
USENIX International Conference on Autonomic Computing (ICAC’13,14,15) 審稿人
成果展示
其他
