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Multi-Clock Snapshot Isolation Concurrency Control for NVM Database

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tsinghua science and technology 2022年第6期27卷 925-938页

作者： Xuyang Liu Kang Chen Mengxing Liu Shiyu cai Yongwei Wu Weimin Zheng department of computer science and technology Tsinghua UniversityBeijing 100084China

Multi-Clock Snapshot Isolation(MCSI)is a concurrency control mechanism that implements snapshot isolation on a single-layer Non-Volatile Memory(NVM)*** stores a single copy of data by using multi-version storage to ensure durability and runtime *** multi-clock transaction timestamp assignment,MCSI can efficiently generate snapshots with vector clocks and use per-thread transaction status arrays to identify uncommitted versions in *** evaluation,we compared MCSI with the PostgreSQL-style concurrency control used in the single-layer NVM database *** maximum transaction throughput of MCSI is 101%–195%higher than that of N2DB for the YCSB workloads,and 25%–49%higher for the TPC-C ***,the transaction latency of MCSI remains relatively stable as the thread count *** 18 worker threads,the average transaction latency of MCSI is 65%–84%lower than that of N2DB for the YCSB workloads and 16%–43%lower for the TPC-C workloads.

关键词： Non-Volatile Memory(NVM) snapshot isolation Multi-Version Concurrency Control(MVCC) vector clock

Consideration of the Local Correlation of Learning Behaviors to Predict Dropouts from MOOCs

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tsinghua science and technology 2020年第3期25卷 336-347页

作者： Yimin Wen Ye Tian Boxi Wen Qing Zhou Guoyong cai Shaozhong Liu Guangxi Key Laboratory of Trusted Software and the School of computer science and Information Security Guilin University of Electronic TechnologyGuilin 541004China. the School of Business Guilin University of Electronic TechnologyGuilin 541004China. the College of computer science Chongqing UniversityChongqing 400044China. the College of Foreign Studies Guilin University of Electronic TechnologyGuilin 541004China.

Recently, Massive Open Online Courses(MOOCs) have become a major online learning methodology for millions of people worldwide. However, the dropout rates from several current MOOCs are high. Usually, dropout prediction aims to predict whether a learner will exhibit learning behaviors during several consecutive days in the future. Therefore, the information related to the learning behaviors of a learner in several consecutive days should be considered. After in-depth analysis of the learning behavior patterns of the MOOC learners, this study reports that learners often exhibit similar learning behaviors on several consecutive days, i.e., the learning status of a learner for the subsequent day is likely to be similar to that for the previous day. Based on this characteristic of MOOC learning,this study proposes a new simple feature matrix for keeping information related to the local correlation of learning behaviors and a new Convolutional Neural Network(CNN) model for predicting the dropout. Extensive experimental validations illustrate that the local correlation of learning behaviors should not be neglected. The proposed CNN model considers this characteristic and improves the dropout prediction accuracy. Furthermore, the proposed model can be used to predict dropout temporally and early when sufficient data are collected.

关键词： Massive Open Online Courses(MOOCs) dropout prediction local correlation of learning behaviors Convolutional Neural Network(CNN) educational data mining

Three Dimensional Metal-Surface Processing Parameter Generation Through Machine Learning-Based Nonlinear Mapping

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清华大学学报:自然科学版(英文版) 2023年第4期28卷 754-768页

作者： Min Zhu Yanjun Dong Bingqing Shen Haiyan Yu Lihong Jiang Hongming cai School of Software Shanghai Jiao Tong UniversityShanghai 200240China School of Mechanical Engineering Donghua UniversityShanghai 200240China

The accuracy and efficiency of three-dimensional(3D)surface forming,which directly affects the cycle and quality of production,is important in *** practice,given the uncertainty of metal plate springback,an error exists between the actual plate and the target surface,which creates a nonlinear mapping from computer aided design models to bending *** need to reconfigure parameters and process a surface multiple times to delicately control springback,which greatly wastes human and material *** study aims to address the springback control problem to improve the efficiency and accuracy of sheet metal forming.A basic computation approach is proposed based on the DeepFit model to calculate the springback value in 3D surface *** address the sample data shortage problem,we put forward an advanced approach by combining a deep learning model with case-based reasoning(CBR).Next,a multi-model fused bending parameter generation framework is devised to implement the advanced springback computation approach through surface data preprocessing,CBR-based model matching,convolution neural network-based machining surface generation,and bending parameter generation with a series of model ***,the proposed approaches and the framework are verified by considering saddle surface processing as an ***,this study provides a new idea to improve the accuracy and efficiency of surface processing.

关键词： 3D surface point-cloud machine learning case-based reasoning industrial software

Garbage Collection and Data Recovery for N2DB

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tsinghua science and technology 2022年第3期27卷 630-641页

作者： Shiyu cai Kang Chen Mengxing Liu Xuyang Liu Yongwei Wu Weimin Zheng department of computer science and technology Tsinghua UniversityBejing 100084China

Non-Volatile Memory(NVM) offers byte-addressability and persistency. Because NVM can be plugged into memory and provide low latency, it offers a new opportunity to build new database systems with a single-layer storage design. A single-layer NVM-Native DataBase(N2 DB) provides zero copy and log freedom. Hence, all data are stored in NVM and there is no extra data duplication and logging during execution. N2 DB avoids complex data synchronization and logging overhead in the two-layer storage design of disk-oriented databases and in-memory databases. Garbage Collection(GC) is critical in such an NVM-based database because memory leaks on NVM are durable. Moreover, data recovery is equally essential to guarantee atomicity, consistency, isolation, and durability properties. Without logging, it is a great challenge for N2 DB to restore data to a consistent state after crashes and recoveries. This paper presents the GC and data recovery mechanisms for N2 DB. Evaluations show that the overall performance of N2 DB is up to 3:6 higher than that of InnoDB. Enabling GC reduces performance by up to 10%,but saves storage space by up to 67%. Moreover, our data recovery requires only 0:2% of the time and half of the storage space of InnoDB.

关键词： Non-Volatile Memory(NVM) Garbage Collection(GC) data recovery

Guest Editorial: Special Issue on Parameterized Complexity

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tsinghua science and technology 2014年第4期19卷 323-324页

作者： Liming cai Iyad Kanj Frances A.Rosamond Institute of Bioinformatics University of Georgia Athens GA 30602-7229 USA College of Computing and Digital Media DePaul University Chicago IL 60604 USA School of Engineering and Information technology Charles Darwin University DarwinNT 0909 Australia

*** Special Issue on Parameterized Complexity of tsinghua science and technology is a tribute to the influential contributions of Jianer Chen to parameterized complexity *** is an occasion to celebrate the many important contributions to this new and prospering branch of theoretical computer science made by Jianer Chen,as he reaches the ripe young age of 60.

关键词： Guest Editorial Special Issue on Parameterized Complexity Chen view FPT

Reliable buffered clock tree routing algorithm with process variation tolerance

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science in China(Series F) 2005年第5期48卷 670-680页

作者： cai Yicit XIONG Yan HONG Xianlong LIU Yi department of computer science and technology University of Science and Technology of ChinaHefei 230026 China department of computer science and technology Tsinghua University Beijing 100084 China

When IC technology is scaled into the very deep sub-micron regime, the optical proximity effects （OPE） turn into noticeable in optical lithography. Consequently, clock skew becomes more and more susceptible to process variations, such as OPE. In this paper, we propose a new buffered clock tree routing algorithm to prevent the influence of OPE and process variations to clock skew. Based on the concept of BSF （branch sensitivity factor）, our algorithm manages to reduce the skew sensitivity of the clock tree in the topology generation. The worst case skew due to the wire width change has been estimated, and proper buffers are inserted to avoid large capacitance load. Experimental results show that our algorithm can produce a more reliable, processinsensitive clock tree, and control clock skews in their permissible range evidently.

关键词： clock routing process variation clock skew branch sensitivity factor buffer insertion.

Malicious Code Detection Model Based on Behavior Association

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tsinghua science and technology 2014年第5期19卷 508-515页

作者： Lansheng Han Mengxiao Qian Xingbo Xu cai Fu Hamza Kwisaba Lab.of Information Security School of Computer ScienceHuazhong University of Science and Technology

Malicious applications can be introduced to attack users and services so as to gain financial rewards, individuals＇ sensitive information, company and government intellectual property, and to gain remote control of systems. However, traditional methods of malicious code detection, such as signature detection, behavior detection, virtual machine detection, and heuristic detection, have various weaknesses which make them unreliable. This paper presents the existing technologies of malicious code detection and a malicious code detection model is proposed based on behavior association. The behavior points of malicious code are first extracted through API monitoring technology and integrated into the behavior; then a relation between behaviors is established according to data dependence. Next, a behavior association model is built up and a discrimination method is put forth using pushdown automation. Finally, the exact malicious code is taken as a sample to carry out an experiment on the behavior＇s capture, association, and discrimination, thus proving that the theoretical model is viable.

关键词： malicious code behavior monitor behavior association pushdown automation

Achieving Differential Privacy of Genomic Data Releasing via Belief Propagation

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tsinghua science and technology 2018年第4期23卷 389-395页

作者： Zaobo He Yingshu Li Ji Li Kaiyang Li Qing cai Yi Liang department of computer science Georgia State University Atlanta GA 30303 USA School of computer science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

Privacy preserving data releasing is an important problem for reconciling data openness with individual privacy. The state-of-the-art approach for privacy preserving data release is differential privacy, which offers powerful privacy guarantee without confining assumptions about the background knowledge about attackers. For genomic data with huge-dimensional attributes, however, current approaches based on differential privacy are not effective to handle. Specifically, amount of noise is required to be injected to genomic data with tens of million of SNPs （Single Nucleotide Polymorphisms）, which would significantly degrade the utility of released data. To address this problem, this paper proposes a differential privacy guaranteed genomic data releasing method. Through executing belief propagation on factor graph, our method can factorize the distribution of sensitive genomic data into a set of local distributions. After injecting differential-privacy noise to these local distributions, synthetic sensitive data can be obtained by sampling on noise distribution. Synthetic sensitive data and factor graph can be further used to construct approximate distribution of non-sensitive data. Finally, non-sensitive genomic data is sampled from the approximate distribution to construct a synthetic genomic dataset.

关键词： differential privacy SNP/trait associations belief propagation factor graph data releasing

BaTiO_(3)基超薄层BME MLCC的可靠性机理

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物理化学学报 2024年第1期40卷 32-41页

作者：朱超琼蔡子明冯培忠张伟晨惠可臻曹秀华付振晓王晓慧中国矿业大学材料与物理学院江苏徐州221116 清华大学材料学院新型陶瓷与精细工艺国家重点实验室北京100084 风华高新科技股份有限公司新型电子元器件关键材料与工艺国家重点实验室广东肇庆526000

多层陶瓷电容器(Multilayer ceramic capacitors,MLCC)作为市场占有率最高的无源电子元器件,是基础电子元件产业中需要突破关键技术的重点产品之一,在汽车电子、5G通讯、电网调频、航空航天等领域有广泛的应用。在小型化、薄层化发展趋... 详细信息

多层陶瓷电容器(Multilayer ceramic capacitors,MLCC)作为市场占有率最高的无源电子元器件,是基础电子元件产业中需要突破关键技术的重点产品之一,在汽车电子、5G通讯、电网调频、航空航天等领域有广泛的应用。在小型化、薄层化发展趋势下,MLCC的介质层厚度不断降低,单层介质在相同电压下的电场显著增大,尤其是中高压超薄层MLCC。因此,MLCC的可靠性愈发成为一项关键的产品质量指标。本文结合加速老化测试、高温阻抗谱、漏电流测试,系统研究超薄层MLCC的劣化机理,揭示抑制氧空位的迁移与富集是保证超薄层MLCC可靠性的重中之重。为此,应减小介质层内部的氧空位浓度,增大其迁移所需的激活能,提高界面肖特基势垒,从而提升超薄层MLCC的可靠性。本文的研究成果为超薄层MLCC介质材料的设计提供了有力指导。

关键词：钛酸钡多层陶瓷电容器可靠性加速老化氧空位

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