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International Conference on Computational Science and engineering

作者： Yang, Chao-Tung Chen, Lung-Teng Chou, Wei-Li Wang, Kuan-Chieh Department of Computer Science High-Performance Computing Laboratory Tunghai University Taichung 40704 Taiwan

ISBN: (纸本)9780769543239

Large scale cluster based on cloud technologies has been widely used in many areas, including the data center and cloud computing environment. The purpose of presenting the research paper in this field was to solve the challenge in Medical Image exchanging, storing and sharing issues of EMR (Electronic Medical Record). In recent years, many countries invested significant resources on the projects of EMR topics. The benefit of the EMR included: Patient-centered Care, Collaborative Teams, Evidence-based Care, Redesigned Business Processes, Relevant Data Capture and Analysis and Timely Feedback and Education. For instance, the ARRA-HIT project in Untied States (2011 - 2015), Health Infoway project in Canada (2001 - 2015) and NHIP project in Taiwan, etc. Aim to the topic of EMR, we presented a system called MIFAS (Medical Image File Accessing System) to solve the exchanging, storing and sharing on Medical Images of crossing the different hospitals issues. Through this system we can enhance efficiency of sharing information between patients and their caregivers. Furthermore, the system can make the best-possible patient-care decisions. © 2010 IEEE.

关键词： Cloud computing

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Stabilized approximate inverse preconditioners for indefinite matrices 46

Stabilized approximate inverse preconditioners for indefinit...

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46th Annual Southeast Regional Conference on XX, ACM-SE 46

作者： Lee, Eun-Joc Laboratory for High Performance Scientific Computing and Computer Simulation Department of Computer Science University of Kentucky United States

ISBN: (纸本)9781605581057

A two-phase preconditioning strategy based on a factored sparse approximate inverse is proposed for solving sparse indefinite matrices. In each phase, the strategy first makes the original matrix diagonally dominant to enhance the stability by a shifting method, and constructs an inverse approximation of the shifted matrix by utilizing a factored sparse approximate inverse preconditioner. The two inverse approximation matrices produced from each phase are then combined to be used as a preconditioner. Experimental results show that the presented strategy improves the accuracy and the stability of the preconditioner on solving indefinite sparse matrices. Furthermore, the strategy ensures that convergence rate of the preconditioned iterations of the two-phase preconditioning strategy is much better than that of the standard sparse approximate inverse ones for solving indefinite matrices. Copyright 2008 ACM.

关键词： Matrix algebra

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Using unified parallel C to parallelize the FDTD method of computational electrodynamics

Using unified parallel C to parallelize the FDTD method of c...

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2009 IEEE 13th International Multitopic Conference, INMIC 2009

作者： Hussain, A. Shafi, A. Raza, J. Center for High Performance Scientific Computing Department of Computing NUST School of Electrical Engineering and Computer Science Pakistan

ISBN: (纸本)9781424448722

This paper discusses a parallel implementation of the Finite-Difference Time-Domain (FDTD) method using Unified Parallel C (UPC). UPC is an extension of ANSI C - primarily designed for programming distributed memory parallel hardware. The FDTD method is a powerful and widely used numerical technique in computational electromagnetics community. It is a resource - CPU cycles and memory - hungry technique. Consequently, a parallel implementation is highly desirable to decrease time-to-solution and be able to study larger problems with limited resources. To the best of our knowledge, this is the first attempt to exploit UPC to parallelize the FDTD method. We evaluate the performance of our implementation on a cluster of four SunFire v890 compute nodes-each equipped with 16 processing cores - and report impressive speedups. ©2009 IEEE.

关键词： Finite difference time domain method

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Topology-aware virtual network embedding based on closeness centrality

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Frontiers of computer Science 2013年第3期7卷 446-457页

作者： Zihou WANG Yanni HAN Tao LIN Yuemei XU Song CI Hui TANG High Performance Network Laboratory Institute of Acoustics Chinese Academy of Sciences Beijing 100190 China Department of Computer and Electronics Engineering University of Nebraska-Lincoln NE 68182 USA

Network virtualization aims to provide a way to overcome ossification of the Internet. However, making efficient use of substrate resources requires effective techniques for embedding virtual networks： mapping virtual nodes and virtual edges onto substrate networks. Previous research has presented several heuristic algorithms, which fail to consider that the attributes of the substrate topology and virtual net- works affect the embedding process. In this paper, for the first time, we introduce complex network centrality analysis into the virtual network embedding, and propose virtual network embedding algorithms based on closeness centrality. Due to considering of the attributes of nodes and edges in the topology, our studies are more reasonable than existing work. In addition, with the guidance of topology quantitative evalua- tion, the proposed network embedding approach largely improves the network utilization efficiency and decreases the embedding complexity. We also investigate our algorithms on real network topologies （e.g., AT＆T, DFN） and random network topologies. Experimental results demonstrate the usability and capability of the proposed approach.

关键词： network virtualization virtual network embedding complex networks closeness centrality

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Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G

arXiv

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arXiv 2025年

作者： Zhang, Jiayi Liu, Ziheng Zhu, Yiyang Shi, Enyu Xu, Bokai Yuen, Chau Niyato, Dusit Debbah, Mérouane Jin, Shi Ai, Bo Shen, Xuemin School of Electronic and Information Engineering The Frontiers Science Center for Smart High-Speed Railway System Beijing jiaotong University Beijing100044 China School of Electrical and Electronics Engineering Nanyang Technological University 639798 Singapore College of Computing and Data Science Nanyang Technological University 639798 Singapore KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

The introduction of intelligent interconnectivity between the physical and human worlds has attracted great attention for future sixth-generation (6G) networks, emphasizing massive capacity, ultra-low latency, and unparalleled reliability. Wireless distributed networks and multi-agent reinforcement learning (MARL), both of which have evolved from centralized paradigms, are two promising solutions for the great attention. Given their distinct capabilities, such as decentralization and collaborative mechanisms, integrating these two paradigms holds great promise for unleashing the full power of 6G, attracting significant research and development attention. This paper provides a comprehensive study on MARL-assisted wireless distributed networks for 6G. In particular, we introduce the basic mathematical background and evolution of wireless distributed networks and MARL, as well as demonstrate their interrelationships. Subsequently, we analyze different structures of wireless distributed networks from the perspectives of homogeneous and heterogeneous. Furthermore, we introduce the basic concepts of MARL and discuss two typical categories, including model-based and model-free. We then present critical challenges faced by MARL-assisted wireless distributed networks, providing important guidance and insights for actual implementation. We also explore an interplay between MARL-assisted wireless distributed networks and emerging techniques, such as information bottleneck and mirror learning, delivering in-depth analyses and application scenarios. Finally, we outline several compelling research directions for future MARL-assisted wireless distributed networks. Copyright © 2025, The Authors. All rights reserved.

关键词： Adversarial machine learning

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Segmentation of Hematoxylin-Eosin stained breast cancer histopathological images based on pixel-wise SVM classifier

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Science China(Information Sciences) 2015年第9期58卷 56-68页

作者： QU AiPing CHEN JiaMei WANG LinWei YUAN JingPing YANG Fang XIANG QingMing MASKEY Ninu YANG GuiFang LIU Juan LI Yan State Key Laboratory of Software Engineering School of Computer Wuhan University Center of High Performance Computing Huaihua University Department of Oncology Zhongnan Hospital of Wuhan University Hubei Key Laboratory of Tumor Biological Behaviors & Hubei Cancer Clinical Study Center Department of Pathology Zhongnan Hospital of Wuhan University

Hematoxylin-Eosin(HE) staining is the routine diagnostic method for breast cancer(BC), and large amounts of HE stained histopathological images are available for analysis. It is emergent to develop computational methods to efficiently and objectively analyze these images, with the aim of providing potentially better diagnostic and prognostic information for BC. This work focuses on analyzing our in-house HE stained histopathological images of breast cancer tissues. Since tumor nests(TNs) and stroma morphological characteristics can reflect the biological behaviors of breast invasive ductal carcinoma(IDC), accurate segmentation of TNs and the stroma is the first step towards the subsequent quantitative analysis. We first propose a method based on the pixel-wise support vector machine(SVM) classifier for segmenting TNs and the stroma, then extract four morphological characters related to the TNs from the images and investigate their relationships with the patients’ 8-year disease free survival(8-DFS). The evaluation result shows that the classification based segmentation method is able to distinguish between TNs and stroma with 87.1% accuracy and 80.2% precision,suggesting that the proposed method is promising in segmenting HE stained IDC histopathological images. The Kaplan-Meier survival curves show that three morphological characters(number of TNs, total perimeter, and average area of TNs) in the images have statistical correlations with 8-DFS of the patients, illustrating that the segmented images can help to identify new morphological factors in IDC TNs for the prediction of BC prognosis.

关键词： breast cancer histopathology images segmentation image analysis support vector machine survival analysis

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An overview of the haplotype problems and algorithms

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中国高等学校学术文摘·计算机科学 2007年第3期1卷 272-282页

作者： ZHAO Yuzhong XU Yun ZHANG Qiangfeng CHEN Guoliang Computer Science Department University of Science and Technology of ChinaHefei 230027China Anhui Province-MOST Co-Key Laboratory of High Performance Computing and Its Application Hefei 230027China

A single nucleotide polymorphism (SNP),as the most common form of genetic variation,has been widely studied to help analyze the possible association between diseases and *** gain more information,SNPs on a single chromosome are usually studied together,which constitute a *** haplotypes from biological experiments is usually very costly and time-consuming,which causes people to develop efficient methods to determine haplotypes from the computational *** problems and algorithms about haplotypes have been proposed to reduce the cost of studies of disease *** general,four categories of problems are widely researched:the haplotype assembly problem,the haplotype inference problem,the haplotype block partition problem,and the haplotype tagging SNP selection *** former two problems have been well reviewed by many researchers,whereas the latter two have not been comprehensively surveyed to our *** this paper,we try to make a detailed introduction to the four problems,especially the latter two.

关键词： bioinformatics haplotype single nucleotide polymorphism (SNP) algorithm complexity

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EXPECTED PRESENT VALUE OF TOTAL DIVIDENDS IN THE COMPOUND BINOMIAL MODEL WITH DELAYED CLAIMS AND RANDOM INCOME

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Acta Mathematica Scientia 2013年第6期33卷 1639-1651页

作者：周杰明莫晓云欧辉杨向群 College of Mathematics and Computer Science Key Laboratory of High Performance Computing and Stochastic Information Processing Ministry of Education of ChinaHunan Normal University Department of Mathematics Hunan University of Finance and Economics

In this paper, a compound binomial model with a constant dividend barrier and random income is considered. Two types of individual claims, main claims and by-claims, are defined, where every by-claim is induced by the main claim and may be delayed for one time period with a certain probability. The premium income is assumed to another binomial process to capture the uncertainty of the customer＇s arrivals and payments. A system of difference equations with certain boundary conditions for the expected present value of total dividend payments prior to ruin is derived and solved. Explicit results are obtained when the claim sizes are Kn distributed or the claim size distributions have finite support. Numerical results are also provided to illustrate the impact of the delay of by-claims on the expected present value of dividends.

关键词： compound binomial model main claim by-claim dividend random income

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Study on optimization of agent initial positions in land combat simulation

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自然科学进展(英文版) 2004年第3期14卷 257-261页

作者： WU Chunguo LIANG Yanchun LEE Heow Pueh LU Chun Yang Xiaowei College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China Institute of High Performance Computing Singapore 117528 Singapore Institute of High Performance Computing Singapore 117528 Singapore Department of Applied Mathematics South China University of Technology Guangzhou 510640 China Centre for ACES Department of Mechanical Engineering National University of Singapore 119260 Singapore

The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector machine (SVM) is presented. The optimization on the width of the Gaussian kernel function and the combination of the SVM with the radial basis function neural network are performed in the proposed method. Simulation results show that the proposed method can improve the running efficiency drastically compared with that using the traditional SVM with the same precision. We also summarize and present some experiences and trends in the study on the optimization problem in land combat simulation.

关键词： multi-agent support vector machine radial basis function genetic algorithm regression

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Understanding co-run performance on CPU-GPU integrated processors： observations, insights, directions

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Frontiers of computer Science 2017年第1期11卷 130-146页

作者： Qi ZHU Bo WU Xipeng SHEN Kai SHEN Li SHEN Zhiying WANG National Key Laboratory of High Performance Computing National University of Defense Technology Changsha 410073 China Department of Computer Science North Carolina State University Raleigh NC 27695 USA Department of Electrical Engineering & Computer Science Colorado School of Mines Golden CO 80401 USA Department of Computer Science University of Rochester Rochester NY 14627 USA

Recent years have witnessed a processor develop- ment trend that integrates central processing unit （CPU） and graphic processing unit （GPU） into a single chip. The inte- gration helps to save some host-device data copying that a discrete GPU usually requires, but also introduces deep re- source sharing and possible interference between CPU and GPU. This work investigates the performance implications of independently co-running CPU and GPU programs on these platforms. First, we perform a comprehensive measurement that covers a wide variety of factors, including processor ar- chitectures, operating systems, benchmarks, timing mecha- nisms, inputs, and power management schemes. These mea- surements reveal a number of surprising observations. We an- alyze these observations and produce a list of novel insights, including the important roles of operating system （OS） con- text switching and power management in determining the program performance, and the subtle effect of CPU-GPU data copying. Finally, we confirm those insights through case studies, and point out some promising directions to mitigate anomalous performance degradation on integrated heteroge- neous processors.

关键词： performance analysis GPGPU co-run degrada-tion fused processor program transformation

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