实验室以输出有影响的理论、开源系统和工具为导向，开展基础研究，并发表高影响力论文。

研究方向：先进计算（超级计算；边缘计算；云计算与服务；高性能数据存储和数据中心；计算架构；高级建模和仿真；数据处理和分析技术）、评价科学与工程（评价学和基准学）、人工智能（AI系统框架；AI保证和评估技术；生成式AI系统；多模态和大语言模型；用于训练、调优和测试的合成数据方法；提高AI安全、信任、安全性和负责任使用的技术）以及操作系统。

我的研究兴趣、目标和愿景

评价是人类的基本活动之一。先进计算系统将有助于解放人类的创造能力，创造更好的世界。我未来的两个研究目标包括：（1）建立统一的评价科学与工程；（2）研究基础理论、模型和方法，以构建和管理简单、安全和公平的基于先进计算的社会基础设施。

未来五年（2025-2030），我计划从事以下研究课题：

评价学和基准学研究（Evaluatology和Benchmarkology）。我很幸运地创造了这两个词（我的博士生李鸿霄对创造Evaluatology有贡献）。 在所有学科中，如何评价是一个根本性的问题。 不幸的是，在大多数学科里，评估方法都是ad-hoc（特定场景相关）和经验性的。如何提出统一的评价的原理和方法是一个挑战性的问题。 我已经提出了评价学的基本概念、统一术语、公理、理论、方法学和基础问题。我将进一步在安全关键、任务关键和商业关键的AI系统、智能、能耗效率、科技和技术、社会基础设施、计算机、医学和药物、安全（特别是AI安全）等学科或者场景下完善评价学和基准学。我计划未来出版5卷英文专著。

基于先进计算的社会基础设施研究。我将引入新的抽象简化基于先进计算的社会基础设施，同时基于评价学的成果保证这类核心基础设施的安全性和公平性。我会进一步完善我之前提出的开源计算机系统倡议 (OpenCS)。开源计算机系统计划有助于基于先进计算的社会基础设施研究。它不会重新发明轮子。 相反，我将提出新的抽象和方法来应对这些重大挑战。

我的教学兴趣与理念声明

我不是一个传统的老师。我的主要教学经验是指导博士生和硕士生参与挑战性的项目。我曾写过一篇文章，提出支配技术兴衰的三大定律。 建议在阅读以下总结之前，参考我之前的文章《技术三大定律》。

我将自己的教学兴趣和理念总结为四点。

参与挑战性的研究项目是最好的学习过程或体验。

如果你难以在一个挑战性的问题上获得成功，我建议你致力于一个对社区有价值的开源工具。 有三个理由可以证明它的合理性。 首先，大多数初级研究人员难以胜任解决重大的挑战问题。 其次，对我们社区有价值的开源工具将帮助你赢得声誉。 第三，工具的研究和开发会训练你的技能，这将帮助你找到工作。

如果你有经验和自信，我鼓励你去发现并解决一个具有挑战性的问题。 即使是十年解决一个挑战问题也是值得的。 但你不能期望太多。

系统创新极具挑战性，需要取舍。 许多人计划构建创新的系统原型。 但是作为博士生或者初级研究员，你必须考虑人和时间的预算。由于预算有限，系统容易出错或过于简单，无法证明其动机。最重要的是，您需要定义一组最小的功能来展示令人信服的创新，并展示变革力（我在技术三大定律里定义的一个概念）。变革力得到验证后，就该用双倍预算实现成熟的功能了。

过去取得的主要成绩(英文）：

Evaluation is a crucial aspect of human existence and plays a vital role in various fields[1]. However, it is often approached in an empirical and ad-hoc manner, lacking consensus on universal concepts, terminologies, theories, and methodologies. I formally introduce the discipline of evaluatology, which encompasses the science and engineering of evaluation. Derived from the essence of evaluation, I propose five axioms focusing on key aspects of evaluation outcomes as the foundational evaluation theory. These axioms serve as the bedrock upon which a universal framework for evaluation is proposed, encompassing concepts, terminologies, theories, and methodologies that can be applied across various disciplines. Building upon the science of evaluation, I propose a formal definition of a benchmark as a simplified and sampled evaluation condition that guarantees different levels of equivalency. This concept serves as the cornerstone for a universal benchmark-based engineering approach to evaluation across various disciplines, which I refer to as benchmarkology.

Under my leadership, the big data and AI benchmarking projects, BigDataBench [2,3] and AIBench [4,5], have had significant impacts. BigDataBench is widely adopted in academia and industry worldwide, with the article published at HPCA'14 receiving 726 citations.

I am the founding chair of the International Open Benchmark Council (BenchCouncil) (https://www.benchcouncil.org ). Renowned scholars such as Matsuoka, Satoshi, Andrew A. Chien, Jeffrey S. Vetter, and John Shalf have ranked BenchCouncil's contributions alongside SPEC, founded in 1988, and before MLCommons, which was founded by Google and other industry and academic leaders such as Stanford and Facebook [6]. In their citation, they state, "Other commonly used benchmarking sets have been curated by organizations such as the Standard Performance Evaluation Corporation (SPEC), the International Open Benchmark Council (BenchCouncil), or MLCommons—with proxies for CPUs, distributed systems, accelerators, artificial intelligence—or have been developed by companies such as Intel (HiBench), Baidu (DeepBench), and Google (PerfKit)."

[1] Jianfeng Zhan, Lei Wang, Wanling Gao et al. Evaluatology: The Science and Engineering of Evaluation. arXiv preprint arXiv:2404.00021, 2024.
[2] Wang, Lei, Jianfeng Zhan, et al. "Bigdatabench: A big data benchmark suite from internet services." In 2014 IEEE 20th international symposium on high-performance computer architecture (HPCA), pp. 488-499. IEEE, 2014. Google Citations: 711. The first author, Lei Wang, is my Ph. D student.
[3] Jia, Zhen, Lei Wang, Jianfeng Zhan, et al. "Characterizing data analysis workloads in data centers." IISWC 2013 Best Paper Award.
[4]Hao, Tianshu, …Jianfeng Zhan. "Edge AIBench: Towards comprehensive end-to-end edge computing benchmarking." In Benchmarking, Measuring, and Optimizing: First BenchCouncil International Symposium, Bench 2018, Seattle, WA, USA, December 10-13, 2018. Google Citations: 81. The first author, Tianshu Hao, is my Ph. D student.
[5] Tang, Fei, Wanling Gao, Jianfeng Zhan, et al. "AIBench training: Balanced industry-standard AI training benchmarking." In 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 24-35. IEEE, 2021. Google Citations: 21. The first author, Fei Tang, is my Ph. D student.
[6] Matsuoka, Satoshi, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Andrew A. Chien, Raymond Bair, Jeffrey S. Vetter, and John Shalf. "Preparing for the Future—Rethinking Proxy Applications." Computing in Science & Engineering 24, no. 2 (2022): 85-90.

I spearheaded the research and development of the cluster operating system [7] for the Dawning 4000A, which achieved the 10th position on the Top 500 supercomputer list in June 2004 (source: https://www.top500.org/system/173564/). As mentioned in Sugon's initial public offering prospectus, my team's patent titled "A Method for Autonomously Constructing Cluster Operating System Kernels and an Intelligent Constructor," along with two other patents and one software IP, were transferred to Sugon, accounting for 34.44% of its total equity share [8]. Sugon is China's leading supercomputer company. In recognition of my contributions, I received the Outstanding Science and Technology Achievement Prize from the Chinese Academy of Sciences in 2005 and the Second Prize of The State Scientific and Technological Progress Award from the Central People's Government of the People's Republic of China in 2006.

Furthermore, I played a pivotal role in the design and implementation of cutting-edge cloud computing systems, namely PhoenixCloud [9,11] and DawningCloud [10], on the Dawning 5000 and 6000 Supercomputers. These innovative solutions revolutionized the support for high-performance computing and the consolidation of heterogeneous workloads on cloud systems. Additionally, I transferred 34 OS patents to a world-class communication and IT company.

[7] Jianfeng Zhan, and Ninghui Sun. "Fire Phoenix cluster operating system kernel and its evaluation." In 2005 IEEE International Conference on Cluster Computing, pp. 1-9. IEEE, 2005.
[8] Sugon’ initial public offering prospectus. Page 1-1-62. https://pdf.dfcfw.com/pdf/H2_AN201410230007390902_1.pdf .Accessed at September 10, 2023
[9] Jianfeng Zhan, Lei Wang, Bibo Tu, Yong Li, Peng Wang, Wei Zhou, and Dan Meng. "Phoenix cloud: Consolidating heterogeneous workloads of large organizations on cloud computing platforms." The first workshop on Cloud Computing and its Applications (CCA'08), 2008. https://www.alcf.anl.gov/events/cca-cloud-computing-and-its-applications
[10] Wang, Lei, Jianfeng Zhan, Weisong Shi, and Yi Liang. "In cloud, can scientific communities benefit from the economies of scale?" IEEE Transactions on Parallel and Distributed Systems 23, no. 2 (2011): 296-303. Google Citations: 214. The first author Lei Wang is my Ph. D student at the publication.
[11] Jianfeng Zhan, et al. "Cost-aware cooperative resource provisioning for heterogeneous workloads in data centers." IEEE Transactions on Computers 62, no. 11 (2012): 2155-2168. Google Citations: 69.

我招生有兴趣、能坚持、有能力的学生。无论出生，不论性别。

已经培养学生和工程师近90名，毕业生代表有美国知名大学的教授和核心互联网企业的架构师。

081201-计算机系统结构

面向大数据和人工智能的软硬件协同设计

1999-09--2002-07   中国科学院研究生院   博士学位

中国科学院大学（中科院软件所）， 1999年09月--2002年7月，计算机软件与理论专业博士 毕业

西南交通大学，1996年09月-1999年3月，固体力学专业，硕士学位

西南交通大学，1992年09月-19996年7月，铁道与道路工程专业，学士学位

中国科学院大学（中科院软件所  19990901--20020701  工学博士学位  

2022年2月1日，先进计算机系统研究中心主任

2013年7月1日-2022年2月1日，先进计算机系统研究中心副主任

2012年10月1日-至今，研究员

2011 年9 月-至今，先进计算机系统研究中心软件系统实验室主任。 

2010 年10 月-至今，被聘任为博士生导师。

2004 年3 月-2012年,副研究员,中科院计算所高性能计算机中心

2002 年7 月-2004 年3 月,助理研究员,中科院计算所高性能计算机研究中心 

2021-08-01-2023-04-30,Eidtor-in-Chief, BenchCouncil Transaction on Benchmarks, Standards and Evaluation

向国际和国内著名企业转移专利超过35项，包括美国专利8项。

建议使用Google Scholar来了解我的最新的论文。

Computation Abstractions

·       Wanling Gao, Jianfeng Zhan, Lei Wang, Chunjie Luo, Daoyi Zheng, Fei Tang, Biwei Xie, Chen Zheng, Xu Wen, Xiwen He and Hainan Ye: Data Motifs: A Lens Towards Fully Understanding Big Data and AI Workloads. Parallel Architectures and Compilation Techniques (PACT) 2018.

AI Benchmarking

·       Zihan Jiang, Lei Wang, Xingwang Xiong, Wanling Gao, Chunjie Luo, Fei Tang, Chuanxin Lan, Hongxiao Li, Jianfeng Zhan. HPC AI500: The Methodology, Tools, Roofline Performance Models, and Metrics for Benchmarking HPC AI Systems. arXiv preprint arXiv:2007.00279

·       Wanling Gao, Fei Tang, Lei Wang, Jianfeng Zhan, Chunxin Lan, Chunjie Luo, Yunyou Huang, Chen Zheng, Jiahui Dai, Zheng Cao, Daoyi Zheng, Haoning Tang, Kunlin Zhan, Biao Wang, Defei Kong, Tong Wu, Minghe Yu, Chongkang Tan, Huan Li, Xinhui Tian, Yatao Li, Junchao Shao, Zhenyu Wang, Xiaoyu Wang, Hainan Ye. AIBench: an industry standard internet service AI benchmark suite. arXiv preprint arXiv:1908.08998

·       Tianshu Hao, Yunyou Huang, Xu Wen, Wanling Gao, Fan Zhang, Chen Zheng, Lei Wang, Hainan Ye, Kai Hwang, Zujie Ren, Jianfeng Zhan. Edge AIBench: towards comprehensive end-to-end edge computing benchmarking. 2018 BenchCouncil International Symposium on Benchmarking, Measuring and Optimization

Big Data Benchmarking

·       Lei Wang, Jianfeng Zhan, Chunjie Luo, Yuqing Zhu, Qiang Yang, Yongqiang He, Wanling Gao, Zhen Jia, Yingjie Shi, Shujie Zhang, Chen Zheng, Gang Lu, Kent Zhan, Xiaona Li, Bizhu Qiu: BigDataBench: A big data benchmark suite from internet services. HPCA 2014: 488-499.

·       Zijian Ming, Chunjie Luo, Wanling Gao, Rui Han, Qiang Yang, Lei Wang, Jianfeng Zhan: BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking. WBDB 2013: 138-154.

·       Zhen Jia, Lei Wang, Jianfeng Zhan, Lixin Zhang, Chunjie Luo: Characterizing data analysis workloads in data centers. IISWC 2013: 66-76.

Cloud Benchmarking

·       Chuniie Luo, Jianfeng Zhan, Lei Wang, Gang Lu, Lixin Zhang, Chengzhong Xu, and Ninghui Sun, Cloudrank-d: benchmarking and ranking cloud computing systems for data processing applications, Frontiers of Computer Science 6 (4), 347-362

Computing Paradigms

·       Gang Lu, Jianfeng Zhan, Tianshu Hao, Lei Wang: 10-millisecond Computing. CoRR abs/1610.01267 (2016).

·       Jianfeng Zhan, Lixin Zhang, Ninghui Sun, Lei Wang, Zhen Jia, Chunjie Luo, High volume throughput computing: Identifying and characterizing throughput oriented workloads in data centers, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum

·       Xinhui Tian, Rui Han, Lei Wang, Gang Lu, Jianfeng Zhan, Latency critical big data computing in finance, The Journal of Finance and Data Science, 2015

Operating Systems

·       Gang Lu, Jianfeng Zhan, Chongkang Tan, Xinlong Lin, Defei Kong, Tianshu Hao, Lei Wang, Fei Tang, Chen Zheng: Isolate First, Then Share: A New OS Architecture for Datacenter Computing. arXiv:1604.01378.

·       Chen Zheng, Lei Wang, Sally A McKee, Lixin Zhang, Hainan Ye, Jianfeng Zhan. XOS: An Application-Defined Operating System for Datacenter Computing. 2018 IEEE International Conference on Big Data (Big Data)

Cluster and Cloud Resource management

·       Jianfeng Zhan, Lei Wang, Xiaona Li, Weisong Shi, Chuliang Weng, Wenyao Zhang, Xiutao Zang: Cost-Aware Cooperative Resource Provisioning for Heterogeneous Workloads in Data Centers. IEEE Trans. Computers 62(11): 2155-2168 (2013).

·       Lei Wang, Jianfeng Zhan, Weisong Shi, Yi Liang: In Cloud, Can Scientific Communities Benefit from the Economies of Scale? IEEE Trans. Parallel Distrib. Syst. 23(2): 296-303 (2012).

·       Jianfeng Zhan, L Wang, B Tu, Y Li, P Wang, W Zhou, D Meng, Phoenix cloud: Consolidating heterogeneous workloads of large organizations on cloud computing platforms, Proceedins of CCA 08, 2008

·       Jianfeng Zhan, Ninghui Sun: Fire Phoenix Cluster Operating System Kernel and its Evaluation. CLUSTER 2005: 1-9.

Programming Systems

·       Peng Wang, Dan Meng, Jizhong Han, Jianfeng Zhan, Bibo Tu, Xiaofeng Shi, Le Wan: Transformer: A New Paradigm for Building Data-Parallel Programming Models. IEEE Micro 30(4): 55-64 (2010).

·       Xinhui Tian, Biwei Xie, Jianfeng Zhan. Cymbalo: An Efficient Graph Processing Framework for Machine Learning. 2018 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Ubiquitous Computing & Communications, Big Data & Cloud Computing, Social Computing & Networking, Sustainable Computing & Communications

Performance Analytics, Management, and Optimization

·       Biwei Xie, Jianfeng Zhan, Xu Liu, Wanling Gao, Zhen Jia, Xiwen He, Lixin Zhang. CVR: efficient vectorization of SpMV on x86 processors. Proceedings of the 2018 International Symposium on Code Generation and Optimization

·       Zhen Jia, Chao Xue, Guancheng Chen, Jianfeng Zhan, Lixin Zhang, Yonghua Lin, Peter Hofstee. Auto-tuning Spark big data workloads on POWER8: Prediction-based dynamic SMT threading. 2016 International Conference on Parallel Architecture and Compilation Techniques (PACT)

·       Xiaoyu Fu, Rui Ren, Jianfeng Zhan, Wei Zhou, Zhen Jia, Gang Lu: LogMaster: Mining Event Correlations in Logs of Large-Scale Cluster Systems. SRDS 2012: 71-80.

·       Zhihong Zhang, Jianfeng Zhan, Yong Li, Lei Wang, Dan Meng, Bo Sang: Precise request tracing and performance debugging for multi-tier services of black boxes. DSN 2009: 337-346.

Deep learning and Its applications

·       Chunjie Luo, Jianfeng Zhan, X Xue, Lei Wang, Rui Ren, Qiang Yang, Cosine normalization: Using cosine similarity instead of dot product in neural networks, 2018 International Conference on Artificial Neural Networks, 382-391

·       Xiexuan Zhou, Wenfeng Zeng, H Chi, C Luo, C Liu, Jianfeng Zhan, SM He, Z Zhang, pdeep: Predicting MS/MS spectra of peptides with deep learning, Analytical chemistry 89 (23), 12690-12697

已指导学生

邱必祝  硕士研究生  081202-计算机软件与理论  

桑波  硕士研究生  081202-计算机软件与理论  

臧秀涛  硕士研究生  081201-计算机系统结构  

袁琳  硕士研究生  081201-计算机系统结构  

黄雅斌  硕士研究生  081201-计算机系统结构  

刘雪娅  硕士研究生  081280-软件工程  

宫士敏  硕士研究生  081201-计算机系统结构  

任睿  硕士研究生  081201-计算机系统结构  

罗纯杰  硕士研究生  081203-计算机应用技术  

周俊平  硕士研究生  081280-软件工程  

杨强  硕士研究生  081202-计算机软件与理论  

谭崇康  硕士研究生  081202-计算机软件与理论  

明子鉴  硕士研究生  081202-计算机软件与理论  

王磊  博士研究生  081202-计算机软件与理论  

陆钢  博士研究生  081202-计算机软件与理论  

田昕晖  博士研究生  081201-计算机系统结构  

周撷璇  博士研究生  081202-计算机软件与理论  

何习文  硕士研究生  081201-计算机系统结构  

郭远晴  硕士研究生  085211-计算机技术  

王标  硕士研究生  081202-计算机软件与理论  

唐昊宁  硕士研究生  085212-软件工程  

高婉铃  博士研究生  081202-计算机软件与理论  

孔德飞  硕士研究生  085212-软件工程  

任睿  博士研究生  081202-计算机软件与理论  

黄运有  博士研究生  081202-计算机软件与理论  

杜梦佳  硕士研究生  081202-计算机软件与理论  

戴绍鹏  硕士研究生  081202-计算机软件与理论  

现指导学生

周润林  博士研究生  085271-电子与信息  

江梓涵  博士研究生  081201-计算机系统结构  

王娜娜  博士研究生  081201-计算机系统结构  

罗纯杰  博士研究生  081202-计算机软件与理论  

康国新  博士研究生  081201-计算机系统结构  

李亚韬  博士研究生  081202-计算机软件与理论  

郝天舒  博士研究生  081202-计算机软件与理论  

温旭  硕士研究生  081201-计算机系统结构  

陈家楠  硕士研究生  081201-计算机系统结构  

黄成  硕士研究生  081201-计算机系统结构  

汤飞  博士研究生  081201-计算机系统结构  

李鸿霄  博士研究生  081201-计算机系统结构  

刘可  硕士研究生  085211-计算机技术  

范帆达  博士研究生  081201-计算机系统结构  

International Open Benchmark Council（BenchCouncil), Chair 

IEEE Transactions on Parallel and Distributed Systems, Associate Editor