程大钊
武汉大学计算机学院 计算机科学系 人工智能研究所 教授 (博导)
姓名：程大钊 主页： 性别：男 职称：教授 (博导,) 学历学位：博士 电话：027-68776120 办公地点：计算机学院E401 E-mail：dcheng ▇ whu.edu.cn 请手工替换符号 领域：并行分布计算,高性能计算,人工智能,云计算与大数据处理,智能计算, 招生信息：年度招收硕士0名，招收方向：。 招收博士0名，招收方向：。 |
研究方向
程大钊，武汉大学计算机学院 教授、博导。研究方向主要包括云计算、人工智能、大数据平台等分布式系统。
在加盟武汉大学之前，曾在美国北卡罗来纳大学夏洛特分校计算机系担任 Tenure Track 助理教授，作为独立 PI 主持了2项美国国家自然科学基金面上项目和1项北卡罗来纳州青年基金项目共计约100万美元，参与项目经费约300万美元。同时，多次担任美国和加拿大国家自然科学基金专家评委，并获评IEEE高级会员。
目前，已经在权威计算机系统领域的国际期刊和会议上发表论文31篇（第一/通讯作者发表24篇），其中以第一/通讯作者发表高质量论文12篇（ 9篇CCF A 类期刊、会议论文， 3篇SCI一区论文），包括TC、TPDS、PPoPP、HPDC、INFOCOM、Middleware、IPDPS、ICDCS、ICPP等。
实验室主页：icslab.whu.edu.cn
欢迎对分布式系统和AI System感兴趣的同学加入，有意向者请把简历、成绩单和专业排名发邮件至：dcheng@whu.edu.cn ！
教育背景
(1) 2011-8至2016-5, 美国科罗拉多大学, 计算机科学, 博士
(2) 2006-9至2009-6, 中国科学技术大学, 模式识别与人工智能，硕士
(3) 2002-9至2006-6, 合肥工业大学, 自动化, 学士
工作经验
(1) 2020-9至现在, 武汉大学, 计算机学院, 教授
(2) 2016-7至2020-9, 美国北卡罗来纳大学, 计算机科学系, 助理教授
教授课程
《大数据分析与处理》。
发表论文
§ 期刊论文
[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一区）
[3] W Rang; D Yang; D Cheng*: Dependency-aware Tensor Scheduler for Industrial AI Applications. IEEE Industrial Electronics Magazine (IEM), 2021.（SCI一区）
[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类）
[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一区）
[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类）
[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类）
[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类）
[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类）
[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类）
[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类）
[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类）
[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.
§ 会议论文
[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类）
[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.
科研课题
1.美国自然科学基金委员会，面上项目2项；
2.北卡莱罗纳州科研基金委员会，青年基金项目1项。
研究团队
2020年9月至今，在武汉大学计算机学院担任教授期间，已组建了拥有4名博士和5名硕士研究生的科研团队。
知识产权
[1] Y Chen, DS Milojicic, D Cheng: Managing data processing resources. US Patent 10,037,230
学术服务
IEEE Transactions on Cloud Computing (TOC) 审稿人
IEEE Transactions on Parallel and Distributed Systems (TPDS) 审稿人
IEEE Conference on Computer Communications (INFOCOM’14,15,16) 审稿人
USENIX International Conference on Autonomic Computing (ICAC’13,14,15) 审稿人
成果展示
其他
