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Taiga: Performance Optimization of the C4.5 Decision Tree Construction Algorithm

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Tsinghua Science and Technology 2016年第4期21卷 415-425页

作者： Yi Yang wenguang chen Department of Computer Science and Technology Tsinghua University Technology Innovation Center at Yinzhou Yangtze Delta Region Institute of Tsinghua University

Classification is an important machine learning problem, and decision tree construction algorithms are an important class of solutions to this problem. RainForest is a scalable way to implement decision tree construction algorithms. It consists of several algorithms, of which the best one is a hybrid between a traditional recursive implementation and an iterative implementation which uses more memory but involves less write operations. We propose an optimized algorithm inspired by RainForest. By using a more sophisticated switching criterion between the two algorithms, we are able to get a performance gain even when all statistical information fits in memory. Evaluations show that our method can achieve a performance boost of 2.8 times in average than the traditional recursive implementation.

关键词： C4.5 RainForest decision trees machine learning performance optimization

MetaOJ: A Massive Distributed Online Judge System

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Tsinghua Science and Technology 2021年第4期26卷 548-557页

作者： Miao Wang Wentao Han wenguang chen Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

Online Judge(OJ) systems are a basic and important component of computer education. Here, we present MetaOJ, an OJ system that can be used for holding massive programming tests online. MetaOJ is designed to create a distributed, fault-tolerant, and easy-to-scale OJ system from an existing ordinary OJ system by adding several interfaces into it and creating multiple instances of it. Our case on modifying the TUOJ system shows that the modification adds no more than 3% lines of code and the performance loss on a single OJ instance is no more than 12%. We also introduce mechanisms to integrate the system with cloud infrastructure to automate the deployment process. MetaOJ provides a solution for those OJ systems that are designed for a specific programming contest and are now facing performance bottlenecks.

关键词： online judge programming test distributed systems

STrans:A Comprehensive Framework for Structure Transformation

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Tsinghua Science and Technology 2016年第2期21卷 231-240页

作者： Jiangzhou He wenguang chen Zhizhong Tang Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and TechnologyTsinghua UniversityBeijing 100084China Google lnc 1600 Amphitheatre PkwyMountain ViewCA 94043USA. Research Institute of Tsinghua University in Shenzhen Shenzhen 518057China

Structure Data Layout Optimization （SDLO） is a prevailing compiler optimization technique to improve cache efficiency. Structure transformation is a critical step for SDLO. Diversity of transformation methods and existence of complex data types are major challenges for structure transformation. We have designed and implemented STrans, a well-defined system which provides controllable and comprehensive functionality on structure transformation. Compared to known systems, it has less limitation on data types for transformation. In this paper we give formal definition of the approach STrans transforms data types. We have also designed Transformation Specification Language, a mini language to configure how to transform structures, which can be either manually tuned or generated by compiler. STrans supports three kinds of transformation methods, i.e., splitting, peeling, and pool-splitting, and works well on different combinations of compound data types. STrans is the transformation system used in ASLOP and is well tested for all benchmarks for ASLOR

关键词： Structure Data Layout Optimization (SDLO) STrans ASLOP structure transformation

Heterogeneous Parallel Algorithm Design and Performance Optimization for WENO on the Sunway TaihuLight Supercomputer

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Tsinghua Science and Technology 2020年第1期25卷 56-67页

作者： Jianqiang Huang Wentao Han Xiaoying Wang wenguang chen State Key Laboratory of Plateau Ecology and Agriculture Department of Computer Technology and ApplicationsQinghai UniversityXining 810016China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

A Weighted Essentially Non-Oscillatory scheme(WENO) is a solution to hyperbolic conservation laws,suitable for solving high-density fluid interface instability with strong intermittency. These problems have a large and complex flow structure. To fully utilize the computing power of High Performance Computing(HPC) systems, it is necessary to develop specific methodologies to optimize the performance of applications based on the particular system’s architecture. The Sunway TaihuLight supercomputer is currently ranked as the fastest supercomputer in the world. This article presents a heterogeneous parallel algorithm design and performance optimization of a high-order WENO on Sunway TaihuLight. We analyzed characteristics of kernel functions, and proposed an appropriate heterogeneous parallel model. We also figured out the best division strategy for computing tasks,and implemented the parallel algorithm on Sunway TaihuLight. By using access optimization, data dependency elimination, and vectorization optimization, our parallel algorithm can achieve up to 172× speedup on one single node, and additional 58× speedup on 64 nodes, with nearly linear scalability.

关键词： parallel algorithms Weighted Essentially Non-Oscillatory scheme(WENO) optimization many-core Sunway TaihuLight

Characterizing and optimizing TPC-C workloads on large-scale systems using SSD arrays

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Science China(Information Sciences) 2016年第9期59卷 33-46页

作者： Jidong ZHAI Feng ZHANG Qingwen LI wenguang chen Weimin ZHENG Department of Computer Science and Technology Tsinghua University

Transaction processing performance council benchmark C(TPC-C) is the de facto standard for evaluating the performance of high-end computers running on-line transaction processing applications. Differing from other standard benchmarks, the transaction processing performance council only defines specifications for the TPC-C benchmark, but does not provide any standard implementation for end-users. Due to the complexity of the TPC-C workload, it is a challenging task to obtain optimal performance for TPC-C evaluation on a large-scale high-end computer. In this paper, we designed and implemented a large-scale TPC-C evaluation system based on the latest TPC-C specification using solid-state drive(SSD) storage devices. By analyzing the characteristics of the TPC-C workload, we propose a series of system-level optimization methods to improve the TPC-C performance. First, we propose an approach based on Small File table space to organize the test data in a round-robin method on all of the disk array partitions; this can make full use of the underlying disk ***, we propose using a NOOP-based disk scheduling algorithm to reduce the utilization rate of processors and improve the average input/output service time. Third, to improve the system translation lookaside buffer hit rate and reduce the processor overhead, we take advantage of the huge page technique to manage a large amount of memory resources. Lastly, we propose a locality-aware interrupt mapping strategy based on the asymmetry characteristic of non-uniform memory access systems to improve the system performance. Using these optimization methods, we performed the TPC-C test on two large-scale high-end computers using SSD arrays. The experimental results show that our methods can effectively improve the TPC-C performance. For example, the performance of the TPC-C test on an Intel Westmere server reached 1.018 million transactions per minute.

关键词： TPC-C benchmark OLTP workload performance analysis performance optimization high-end computers

Auxo: A Temporal Graph Management System

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Big Data Mining and Analytics 2019年第1期2卷 58-71页

作者： Wentao Han Kaiwei Li Shimin chen wenguang chen Department of Computer Science and Technology Tsinghua University Institute of Computing Technology Chinese Academy of Sciences

As real-world graphs are often evolving over time, interest in analyzing the temporal behavior of graphs has grown. Herein, we propose Auxo, a novel temporal graph management system to support temporal graph analysis. It supports both efficient global and local queries with low space overhead. Auxo organizes temporal graph data in spatio-temporal chunks. A chunk spans a particular time interval and covers a set of vertices in a *** propose chunk layout and chunk splitting designs to achieve the desired efficiency and the abovementioned goals. First, by carefully choosing the time split policy, Auxo achieves linear complexity in both space usage and query time. Second, graph splitting further improves the worst-case query time, and reduces the performance variance introduced by splitting operations. Third, Auxo optimizes the data layout inside chunks, thereby significantly improving the performance of traverse-based graph queries. Experimental evaluation showed that Auxo achieved 2:9 to 12:1 improvement for global queries, and 1:7 to 2:7 improvement for local queries, as compared with state-of-the-art open-source solutions.

关键词： graphs and networks temporal databases composite structures

Exploring differentiated improvement strategies of cultivated land quality in China

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Frontiers of Agricultural Science and Engineering 2024年第2期11卷 282-291页

作者： wenguang chen Xiangbin KONG Yubo LIAO College of Land Science and Technology China Agricultural UniversityBeijing 100193China

Quality is the core feature of cultivated land. In the face of deteriorating cultivated land quality and growing food demand, improving cultivated land quality is a top priority for guaranteeing the sustainable use of resources and national food security. Cultivated land quality in the new era can be considered in four dimensions: suitability, contiguity, resistance and ecological stress. Cultivated land suitability in China shows a decreasing trend from east to west, cultivated land contiguity is high in the north-east and low in the south-west. In terms of cultivated land resistance, the number of strongly and weakly resistant cropping fields is small and spatially clustered. Cultivated land with ecological stress is mainly located in the northern region. Based on the current situation of cultivated land quality and the strategic needs of national high-quality development, China's future goals for improving cultivated land quality include four aspects: promoting the sustainable use of resources,improving the economic benefits of farming, coping with extreme meteorological disasters and meeting the transition of the food *** the backdrop of a volatile international environment and high domestic demand for food, China should guarantee a safe supply of staples, a stable supply of animal feed and a moderate supply of high-nutrient food. In the future, China should create three major food production spaces: highstandard, low-to medium-yield, and marginal cultivated land. China urgently needs to construct three paths to implement the goal of improving cultivated land quality, namely the development of high-standard cultivated land with the core of spatial optimization, resilience enhancement and scale coupling,the transformation of low-to medium-yield cultivated land with the core of obstacle elimination, tenure adjustment, ecological sustainable, and the conservation development of marginal cultivated land with a focus on sustainable use.

关键词： China cultivated land quality differentiated improvement food security

Helmholtz Solving and Performance Optimization in Global/Regional Assimilation and Prediction System

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Tsinghua Science and Technology 2021年第3期26卷 335-346页

作者： Jianqiang Huang Wei Xue Haodong Bian Wenxin Yan Xiaoying Wang wenguang chen Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Department of Computer Technology and Applications Qinghai UniversityXining 810016China

Despite efficient parallelism in the solution of physical parameterization in the Global/Regional Assimilation and Prediction System(GRAPES),the Helmholtz equation in the dynamic core,with the increase of resolution,can hardly achieve sufficient parallelism in the solving process due to a large amount of communication and irregular *** this paper,optimizing the Helmholtz equation solution for better performance and higher efficiency has been an urgent *** optimization scheme for the parallel solution of the Helmholtz equation is proposed in this ***,the geometrical multigrid optimization strategy is designed by taking advantage of the data anisotropy of grid points near the pole and the isotropy of those near memory equator in the Helmholtz equation,and the Incomplete LU(ILU)decomposition preconditioner is adopted to speed up the convergence of the improved Generalized Conjugate Residual(GCR),which effectively reduces the number of iterations and the computation *** overall solving performance of the Helmholtz equation is improved by thread-level parallelism,vectorization,and reuse of data in the *** experimental results show that the proposed optimization scheme can effectively eliminate the bottleneck of the Helmholtz equation as regards the solving *** the test results on a 10-node two-way server,the solution of the Helmholtz equation,compared with the original serial version,is accelerated by 100,with one-third of iterations reduced.

关键词： Global/Regional Assimilation and Prediction System(GRAPES) Helmholtz equation Generalized Conjugate Residual(GCR) performance optimization Incomplete LU(ILU)

A survey of cloud resource management for complex engineering applications

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Frontiers of Computer Science 2016年第3期10卷 447-461页

作者： Haibao chen Song WU Hai JIN wenguang chen Jidong ZHAI Yingwei LUO Xiaolin WANG Services Computing Technology and System Lab Cluster and Grid Computing LabSchool of Computer Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Institute of High Performance Computing Tsinghua University Beijing 100084 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China School of Computer and Information Engineering Chuzhou University Chuzhou 239000 China

Traditionally, complex engineering applications （CEAs）, which consist of numerous components （software） and require a large amount of computing resources, usu- ally run in dedicated clusters or high performance computing （HPC） centers. Nowadays, Cloud computing system with the ability of providing massive computing resources and cus- tomizable execution environment is becoming an attractive option for CEAs. As a new type on Cloud applications, CEA also brings the challenges of dealing with Cloud resources. In this paper, we provide a comprehensive survey of Cloud resource management research for CEAs. The survey puts forward two important questions： 1） what are the main chal- lenges for CEAs to run in Clouds？ and 2） what are the prior research topics addressing these challenges？ We summarize and highlight the main challenges and prior research topics. Our work can be probably helpful to those scientists and en- gineers who are interested in running CEAs in Cloud envi- ronment.

关键词： Cloud computing complex engineering application resource management virtualization