基本情况 |
姓名: |
谭婧炜佳 |
![](/__local/C/11/06/6EDFDE0F397F54BAE858C78CA31_F3BB59DF_1677.jpg)
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性别: |
女 |
职称: |
副教授 |
最高学历: |
研究生 |
最高学位: |
博士 |
Email: |
jtan@jlu.edu.cn |
所在学科专业 |
计算机系统结构 |
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个人简介:
谭婧炜佳,博士,副教授,博士生导师。现为中国计算机学会高级会员,中国计算机学会体系结构专业委员会执行委员,中国计算机学会容错计算专业委员会执行委员。2016年博士毕业于美国休斯顿大学,2017年菠菜导航网海外引进博士A 类人才,2019 年吉林省青年人才托举工程入选者,2020年首批吉林省人才“18条”政策-D类(省级领军人才)入选者。2018年获得EDA 领域顶级会议DATE’ 2018的最佳论文奖提名。2023年国家级虚拟仿真实验教学一流课程《云计算技术综合虚拟仿真实验》课程团队成员。
发表CCF 推荐A、B 类期刊和会议及中科院一区等高水平论文30余篇,包括顶级期刊和会议IEEE TC, IEEE TPDS, IEEE TCAD, SC, MICRO, ACM TODAES, ACM TECS, JSA, PACT, ICCD, IPDPS, DATE等。授权国家发明专利6 项,主持国家自然科学基金2项(面上、青年),吉林省科技发展计划项目4 项。多次担任TC, TMC, JSA, TAES, ESL, TJSC, JCSC, IET CDT 等著名国际期刊审稿人,以及NPC’2022, NAS’2022, RSDA’2022, RSDA’2021 等知名国际会议及研讨会程序委员会委员、IPDRM’2016 研讨会宣传主席。
长期从事计算机体系结构领域的研究,在高性能并行计算机体系结构的可靠性方面提出了多项创新研究成果。建立了面向GPGPU和CNN加速器的体系结构级和程序级错误注入工具、分析模型框架、分析预测模型、错误保护及容错设计方法等,建立了面向多芯片模块集成GPU的电压噪声分析框架及体系结构级缓解方法,提出了多项硬件变异性感知的GPU体系结构设计方法。目前主要关注高性能处理器所面临的新兴应用场景、架构、工艺、器件等带来的高能粒子、电压噪声、制成变异、老化、电磁、热等可靠性挑战,从程序、编译、体系结构、电路等层面进行软硬件协同设计研究。
研究方向:
计算机体系结构、处理器芯片架构设计、硬件可靠性、GPGPU、AI加速器、高能效计算
招生信息:
每年招收多名学硕及专硕,名额充足,欢迎感兴趣的同学报考。
长期招收本科实习生,欢迎感兴趣的同学与我联系。
指导的已毕业硕士研究生,全部获得研究生优秀奖学金、研究生学业奖学金、优秀毕业研究生荣誉。硕士期间均发表包括TC(CCF-A期刊)、TCAD(CCF-A期刊)、ICCD(CCF-B会议)、FGCS(中科院一区期刊)等在内的高水平论文和发明专利授权,毕业后进入国内著名公司、企业、研究机构等从事计算机体系结构及相关方向研发工作。
协助指导的已毕业博士研究生博士期间发表SC(CCF-A会议)、TCAD(CCF-A期刊)、FGCS(中科院一区期刊)、DATE(CCF-B会议)等高水平论文,毕业后入选菠菜导航网鼎新学者。
指导的本科生收到多所美国及香港一流大学的全奖博士offer,目前在美国弗吉尼亚大学、美国爱荷华大学等著名高校攻读博士学位。
教育经历:
2014-2016,美国休斯顿大学,电气与计算机工程系,博士
2011-2014,美国堪萨斯大学,电气工程与计算机科学系,硕士
2007-2011,菠菜导航网,菠菜导航,本科
工作经历:
2017至今,菠菜导航网,副教授
2016-2017,美国高通公司,高级工程师
2015、2016,美国太平洋西北国家实验室,博士实习生
主持科研项目:
1. 国家自然科学基金,面上项目,2024-2027,在研。
2. 吉林省科技厅,2023-2025,在研。
3. 吉林省科技厅,重点研发项目,2022-2025,在研。
4. 吉林省科技厅,2019-2021,已结题。
5. 国家自然科学基金,青年科学基金,2019-2021,已结题。
6. 吉林省教育厅,2019-2020,已结题。
7. 吉林省科技厅,2018-2020,已结题。
代表性学术论文:
著作章节:
1. Jingweijia Tan, and Xin Fu, Addressing Hardware Reliability Challenges in General-Purpose GPUs, in Advances in GPU Research and Practice, Elsevier Publishing, 2016.
期刊论文:
1. Jingweijia Tan, L. Ping, Q. Wang, K. Yan, Saca-AVF: A Quantitative Approach to Analyze the Architectural Vulnerability Factors of CNN Accelerators. IEEE Transactions on Computers (TC), 2023. (CCF-A类)
2. Jingweijia Tan, K. Chen, W. Wang, K. Yan, X. Wei, MCM-GPU Voltage Noise Characterization and Architecture-Level Mitigation. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2023. (CCF-A类)
3. Jingweijia Tan, M. Chen, Y. Yi, and X. Fu, Mitigating the Impact of Hardware Variability for GPGPUs Register File, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2016. (CCF-A类)
4. H. Yue, X. Wei, Jingweijia Tan, N. Jiang, M. Qiu, Eff-ECC: Protecting GPGPUs Register File With a Unified Energy-Efficient ECC Mechanism. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2022. (CCF-A类,通讯作者)
5. Jingweijia Tan, Q. Wang, K. Yan, X. Wei. Saca-FI: A microarchitecture-level fault injection framework for reliability analysis of systolic array based CNN accelerator. Future Generation Computer Systems (FGCS), 2023. (中科院SCI一区)
6. X. Wei, H. Yue, S. Gao, L. Li, R. Zhang, Jingweijia Tan, G-SEAP: Analyzing and characterizing soft-error aware approximation in GPGPUs. Future Generation Computer Systems (FGCS), 2020. (中科院SCI一区,通讯作者)
7. Jingweijia Tan, W. Wang, M. Ma, X. Wei, K. Yan, Improving the Performance of CNN Accelerator Architecture Under the Impact of Process Variations. ACM Transactions on Design Automation of Electronic Systems (TODAES), 2023. (CCF-B类)
8. T. Bu, K. Yan, Jingweijia Tan, Towards Fine-Grained Online Adaptive Approximation Control for Dense SLAM on Embedded GPUs. ACM Transactions on Design Automation of Electronic Systems (TODAES), 2022. (CCF-B类)
9. K. Yan, Jingweijia Tan, L. Liu, X. Zhang, S. R. Brankovic, J. Chen, X. Fu, Toward Customized Hybrid Fuel-Cell and Battery-powered Mobile Device for Individual Users, ACM Transactions on Embedded Computing Systems (TECS), 2020. (CCF-B类)
10. Jingweijia Tan, K. Yan, S. L. Song, X. Fu, Energy-Efficient GPU L2 Cache Design Using Instruction-Level Data Locality Similarity, ACM Transactions on Design Automation of Electronic Systems (TODAES), 2020. (CCF-B类)
11. K. Yan, Jingweijia Tan, X. Fu, Improving Energy Efficiency of Mobile Devices by Characterizing and Exploring User Behaviors, Journal of System Architecture (JSA) 2019. (CCF-B类)
12. Jingweijia Tan and K. Yan, Efficiently Managing the Impact of Hardware Variability on GPUs' Streaming Processors, ACM Transactions on Design Automation of Electronic Systems (TODAES), 2019. (CCF-B类)
13. Jingweijia Tan, Z. Li, M. Chen, and X. Fu, Exploring Soft-Error Robust and Energy-Efficient Register File in GPGPUs using Resistive Memory, ACM Transactions on Design Automation of Electronic Systems (TODAES), 2016. (CCF-B类)
14. Jingweijia Tan, Y. Yi, F. Shen, and X. Fu, Modeling and Characterizing GPGPU Reliability in the Presence of Soft Errors, Elsevier Journal of Parallel Computing (ParCo), 2013. (CCF-B类)
会议论文:
1. H. Yue, X. Wei, G. Li, J. Zhao, N. Jiang, Jingweijia Tan, G-SEPM: Building an Accurate and Efficient Soft Error Prediction Model for GPGPUs, International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2021. (CCF-A类, 通讯作者)
2. K. Yan, X. Zhang, Jingweijia Tan, and X. Fu, Redefining QoS and Customizing the Power Management Policy to Satisfy Individual Mobile Users, International Symposium on Microarchitecture (MICRO), 2016. (CCF-A类)
3. Jingweijia Tan and K. Yan, HVSM: Hardware-Variability Aware Streaming Processors' Management Policy in GPUs, Design, Automation and Test in Europe Conference & Exhibition (DATE), 2018. (CCF-B类, 最佳论文奖提名)
4. Jingweijia Tan, K. Chen, K. Yan, MG-Voltage: Characterizing and Mitigating Voltage Noise in MCM-GPU Architectures, International Conference on Computer Design (ICCD), 2022. (CCF-B类)
5. X. Wei, H. Yue, Jingweijia Tan, LAD-ECC: Energy-Efficient ECC Mechanism for GPGPUs Register File, Design, Automation and Test in Europe Conference & Exhibition (DATE), 2020. (CCF-B类, 通讯作者)
6. M. Ma, Jingweijia Tan, X. Wei, K. Yan, Process Variation Mitigation on Convolutional Neural Network Accelerator Architecture, International Conference on Computer Design (ICCD), 2019. (CCF-B类, 通讯作者)
7. Jingweijia Tan, K. Yan, S. L. Song, and X. Fu, LoSCache: Leveraging Locality Similarity to Build Energy-Efficient GPU L2 Cache, Design, Automation and Test in Europe Conference & Exhibition (DATE), 2019. (CCF-B类)
8. Jingweijia Tan, S. Song, K. Yan, X. Fu, A. Marquez, and D. Kerbyson, Combating the Reliability Challenge of GPU Register File at Low Supply Voltage, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2016. (CCF-B类)
9. Jingweijia Tan, and X. Fu, Mitigating the Susceptibility of GPGPUs Register File to Process Variations, IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2015. (CCF-B类)
10. Jingweijia Tan, Z. Li, and X. Fu, Soft-Error Reliability and Power Co-Optimization for GPGPU Register File using Resistive Memory, Design, Automation and Test in Europe Conference & Exhibition (DATE), 2015. (CCF-B类)
11. Jingweijia Tan, and X. Fu, RISE: Improving the Streaming Processors Reliability Against Soft Errors in GPGPUs, International Conference on Parallel Architectures and Compilation Techniques (PACT), 2012. (CCF-B类)
12. Jingweijia Tan, N. Goswami, T. Li, and X. Fu, Analyzing Soft-Error Vulnerability on GPGPU Microarchitecture, IEEE International Symposium on Workload Characterization (IISWC), 2011.
主讲课程:
1. 《计算机系统结构》,菠菜导航本科生必修课,2019年至今。
2. 《GPGPU异构高性能计算》,菠菜导航本科生选修课,2021年至今。
3. 《计算机硬件系统设计实验I》,菠菜导航本科生必修实验课,2023年至今。
4. 《计算机硬件系统设计实验II》,菠菜导航本科生选修实验课,2024年起。
5. 《云计算技术》,软件学院本科生选修课,2018-2020年。
6. 《云计算与分布式计算》,菠菜导航研究生选修课,2022年。