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Great Lakes Symposium on VLSI (GLSVLSI)

作者： Song, Mingye Xu, Zhezhao Xue, Wei Yu, Wenjian Tsinghua Univ BNRist Dept Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9781450357241

Due to the advantages on scalability and reliability, the floating random walk (FRW) algorithm has been widely adopted for calculating the capacitances among three-dimensional (3-D) conductors. This is evidenced by the industrial practice of interconnect capacitance extraction during the design of high-performance very large-scale integrated (VLSI) circuits. In this work, the FRW algorithm is enhanced through the distributed parallel computing. With an efficient and adaptive task allocation scheme, the communication among different computer nodes is largely reduced. A distributed algorithm for accelerating the space management is also proposed. They have been implemented with Message Passing Interface (MPI) and applied to the high-precision capacitance simulation for touch-screen design and the interconnect capacitance extraction of VLSI circuits. Experiments on a computer cluster show that the proposed techniques achieve up to 114X speedup while using 120 cores, and build up the space management structure for a VLSI case including two million conductor blocks in just 22 seconds (37X parallel speedup on 60 cores).

关键词： design verification touchscreen design capacitance calculation floating random walk (frw) very large-scale integrated (vlsi) circuit distributed parallel computing

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distributed Network Reconstruction Based on Binary Compressed Sensing via ADMM

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2023年第4期10卷 2141-2153页

作者： Liu, Yishun Huang, Keke Yang, Chunhua Wang, Zhen Cent South Univ Sch Automat Changsha 410083 Hunan Peoples R China Northwestern Polytech Univ Ctr Opt Imagery Anal & Learning Xian 710072 Shaanxi Peoples R China Northwestern Polytech Univ Sch Mech Engn Xian 710072 Shaanxi Peoples R China

At present, network model is a general framework for the representation of complex system, and its structure is the fundamental and prerequisite for control and other applications of networked system. Due to the advent of Big Data era, the network structure scale is expanding sharply. Obviously, the traditional centralized reconstruction methods require high-performance computing resources and can hardly be suitable in practice. Therefore, it is a challenge to reconstruct large-scale networks with limited resources. To resolve the problem, a distributed local reconstruction method is proposed for unweighted networks. Specifically, the local reconstruction problems of nodes are distributed to multiple computing units. ADMM is introduced for compressed sensing framework to decompose the complex reconstruction problem into multiple subproblems, so it can reduce the high requirement of computing resources. Through parallel computing, network reconstruction subproblems are solved simultaneously. In addition, to further guarantee the reconstruction accuracy, a binary constraint is introduced based on the characteristics obtained by analyzing the network structure. Finally, extensive experiments are conducted to demonstrate the superiority of the proposed method. Compared with some state-of-the-art methods, the proposed method can reconstruct networks of different scales and types with limited computing resources, and it is accurate and robust against noise.

关键词： Compressed sensing Resistors Reconstruction algorithms Complex networks Topology Resistance Power system dynamics ADMM compressed sensing distributed parallel computing network structure

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A real-time physiological signal acquisition and analyzing method based on fractional calculus and stream computing

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SOFT computing 2021年第22期25卷 13933-13939页

作者： Lv, Taizhi Tong, Lian Zhang, Jun Chen, Yong Jiangsu Maritime Inst 309 Gezhi Rd Nanjing 211170 Peoples R China Nanjing Longyuan Microelect Co Ltd 7 Nanyou Rd Nanjing 211106 Peoples R China

The physiological signal acquisition and analyzing are important for intelligent health services, human-computer interaction and other applications. Due to the computing power limitation of terminal devices, many analyzing methods of physiological signals are in offline mode. However, in many applications, physiological signal should be analyzed in real time. To overcome this problem, a real-time physiological signal acquisition and analysis method based on fractional calculus and stream computing is proposed. Mobile terminals read the physiological data from sensors and upload them to the stream computing platform. A fractal index is used to estimate the physiological status. Based on the stream computing platform, this index is calculated by distributed parallel computing. The experiment results show this method can distinguish the heart health status and reflect driver mental status to some extent.

关键词： Physiological signal Stream computing Fractal calculus Apache storm distributed parallel computing

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Cloud computing Management Platform of Human Resource Based on Mobile Communication Technology

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WIRELESS PERSONAL COMMUNICATIONS 2018年第2期102卷 1293-1306页

作者： Lv, Zhengbao Tan, Zefu Wang, Qian Yang, Yanqiong Chongqing Three Gorges Univ Three Gorges Res Inst Chongqing Peoples R China Chongqing Three Gorges Univ Signal & Informat Proc Key Lab Chongqing Peoples R China Chongqing Three Gorges Univ Coll Publ Management Chongqing Peoples R China

For studying the cloud computing management platform of human resources, according to the plight of group enterprise human resource management research, a set of human resource management information system based on cloud computing technology is designed, which is used in various fields of group enterprise human resources management, such as personnel management, organization management, salary management, attendance management and so on. The results show that the group level human resource management information system based on cloud computing can help enterprises to complete the task of human resource management efficiently, which reduces the communication costs and improves the management efficiency. In addition, it achieves the group enterprise human resources data search of MapReduce engine under the framework of Hadoop, report data check and so on massive data computing task. In summary, it provides a cloud computing based group human resource management information system achieved based on JAVA programming language, and provides PC terminal, mobile terminal, flat terminal and other multi terminal operating platforms, which has high application value.

关键词： Cloud computing MapReduce distributed parallel computing Human resource management Information system

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Congestion control for asynchronous parallel computing on workstation networks

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parallel computing 1997年第13期23卷 1855-1875页

作者： Heddaya, A Park, K Boston Univ Dept Comp Sci Boston MA 02215 USA Purdue Univ Dept Comp Sci W Lafayette IN 47907 USA

Asynchronous parallel computing can result in high message generation rates, thus triggering network congestion. We characterize the communication requirements of a large class of supercomputing applications falling under the category of fixed-point problems amenable to solution by parallel iterative methods. In particular, we concentrate on asynchronous iterative algorithms whose communication/computation ratio is especially high resulting in degraded effective throughput if communication is not managed properly. Second, we show the effects of network contention and asynchrony on application performance in a local-area network environment and investigate methods of solution. Our approach is based on a congestion control algorithm called 'warp control' whose adaptive properties are exploited to yield significant performance enhancements when network contention is high. Although tested in a LAN environment for experimental control purposes, our solution follows the end-to-end paradigm and refrains from exploiting special MAC-layer properties to achieve applicability to general WAN environments. Third, we provide a framework wherein efficient congestion control can be facilitated, encompassing methods acting at the application layer as well as the transport/network layer, with emphasis on application-driven control. We conclude with a discussion of our experimental results and special issues arising in high-bandwidth ATM networks. (C) 1997 Elsevier Science B.V.

关键词： distributed parallel computing congestion control parallel iterative algorithms communication architecture

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A customized two-stage parallel computing algorithm for solving the combined modal split and traffic assignment problem

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COMPUTERS & OPERATIONS RESEARCH 2023年 154卷

作者： Zhang, Kai Zhang, Honggang Cheng, Qixiu Chen, Xinyuan Wang, Zewen Liu, Zhiyuan Southeast Univ Jiangsu Prov Collaborat Innovat Ctr Modern Urban T Sch Transportat Jiangsu Key Lab Urban ITS Nanjing Peoples R China Hong Kong Polytech Univ Dept Logist & Maritime Studies Kowloon Hong Kong Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing Peoples R China

Efficiently solving the traffic assignment problem (TAP) for large-scale transport networks is a critical problem for transportation studies. Most of the existing algorithms for TAP are serial ones based on single-computer mode, which has inherently limited the computational efficiency, compared with parallel computing methods. Thus, this paper aims to propose an efficient distributed multi-computer cluster resource allocation method for the parallel computing of TAP. Previous studies on the parallel computing of TAP are mainly based on a single -mode, which is extended to a more complex combined modal split and traffic assignment (CMSTA) case in this paper. In order to decompose the CMSTA problem, we proposed a block-decomposed model for solving the CMSTA problem. Then we designed an optimal parallel computing resource schedule for solving each block problem more quickly on the huge transportation network. Therefore, we implemented a customized two-stage parallel (TP) algorithm that can fully use parallel resources. The first parallel stage of the TP algorithm is used in the path generation phase, and the second parallel stage is used in the path flow adjustment phase. Besides, the parallel slowdown is uncovered in calculating each block problem of the path flow adjustment phase by using parallel resources. Numerical examples are taken to validate the efficiency and robustness of the proposed TP algorithm.

关键词： Traffic Assignment Problem Modal Split Gradient Projection distributed parallel computing

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Wrapping MPI-based legacy codes as Java/CORBA components

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2001年第2期18卷 213-223页

作者： Li, MZ Rana, OF Walker, DW Cardiff Univ Dept Comp Sci Cardiff CF24 3XF S Glam Wales

Techniques for wrapping an MPI-based molecular dynamics (MD) simulation code as Java/CORBA components, for use within a distributed component based problem solving environment (CB-PSE), is presented. A legacy code for simulating a Lennard-Jones fluid is first wrapped as a single CORBA object, followed by division of the code into computational sub-units, where each sub-unit is wrapped as a CORBA object containing MPI calls, and run on a cluster of workstations - enabling different MPI implementations to inter-operate. Using a Java implementation, users can submit simulation tasks through a Web based inter-face, without needing to know implementation details of the legacy code, or the exact interaction between sub-units within the code. We provide performance comparisons of wrapping the entire MD code as a single object versus wrapping sub-units within it, and offer a simple performance model to explain our findings. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： problem solving environments Java/CORBA components legacy code wrappers distributed parallel computing

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Optimization of magneto-hydrodynamic control of diffuser flows using micro-genetic algorithms and least-squares finite elements

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FINITE ELEMENTS IN ANALYSIS AND DESIGN 2001年第5期37卷 349-363页

作者： Dennis, BH Dulikravich, GS Univ Texas Dept Mech & Aerosp Engn Arlington TX 76019 USA Penn State Univ Dept Aerosp Engn University Pk PA 16802 USA

In this paper we consider the problem of multidisciplinary design and optimization (MDO) of a diffuser for a steady, incompressible magnetohydrodynamic (MHD) flow. Given a fixed diffuser shape, the optimizer should find the distribution of the wall magnets that will maximize the static pressure increase from inlet to outlet. This design problem is solved through the use of a genetic algorithm based optimization program coupled with a finite element based MHD simulation program. For MHD simulation, a least-squares finite element method (LSFEM) based program has been developed. The use of LSFEM allows the use of equal order approximation functions for all unknowns and is stable for high Reynolds numbers. Optimization was accomplished using a micro-genetic algorithm (GA) based program. The micro-GA is capable of searching the design space with a population much smaller than that required by classical GA. The optimization was performed on a parallel computer composed of commodity PC components. Results show that an applied magnetic field with the proper strength and distribution can significantly improve the static pressure rise over the case of no magnetic field. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： magnetohydrodynamics least-squares finite element method genetic algorithms optimization distributed parallel computing

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Improvement of Block IC Preconditioner Using Fill-In Technique for Linear Systems Derived From Finite-Element Method Including Thin Elements

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IEEE TRANSACTIONS ON MAGNETICS 2018年第3期54卷 1-4页

作者： Tsuburaya, Tomonori Okamoto, Yoshifumi Meng, Zhiqi Fukuoka Univ Dept Elect Engn Fukuoka 8140180 Japan Hosei Univ Dept Elect & Elect Engn Tokyo 1848584 Japan

The block incomplete-Cholesky (IC) preconditioner is often used for parallel preconditioner in finite-element method (FEM) supported by distributed computing. When many thin elements are included in an analyzed mesh such as magnetic shielding, the convergence characteristic of preconditioned conjugate gradient method would be deteriorated. At that time, IC preconditioner with fill-in makes the convergence characteristic of linear solver much better. This paper demonstrates the validity of block IC with fill-in on linear systems arising in FEM with many flat elements. First, the ability to improve the convergence property using the fill-in strategy is verified by the simulation of magnetic shielding. Next, the parallelization performance of block IC with fill-in is illustrated by using finite-element mesh of laminated core model and induction heating cooker.

关键词： distributed parallel computing fill-in finite-element mesh with thin element IC preconditioner

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Injection molding optimization with weld line design constraint using distributed multi-population genetic algorithm

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2011年第1-4期52卷 131-141页

作者： Wu, Chun-Yin Ku, Chih-Chiang Pai, Hsin-Yi Tatung Univ Dept Mech Engn Taipei Taiwan Micro Star Int Co Ltd Res Ctr Res & Dev Dept 3 Taipei Taiwan

Weld lines not only detract from an injection-molded part's surface quality, but also significantly reduce its mechanical strength. It is not always easy to completely eliminate weld lines by simply adjusting the relevant injection mold design or the molding conditions. One solution is to prevent the weld lines from forming in regions that are structurally or aesthetically sensitive. The influence of weld lines on the quality of injection-molded parts cannot be overlooked and weld lines should be regarded as an important design constraint, especially for parts with aesthetic concerns. Since precisely predicting the number of weld lines and their positions and lengths is difficult without executing simulation routines, especially when part geometry is considered a design variable, this study adopts an enhanced genetic algorithm, referred to as distributed multi-population genetic algorithm (DMPGA), combining an optimization algorithm and commercial MoldFlow software with a dominance-based constraint-handling technique and a master-slave distributed architecture. MoldFlow obtains relevant data regarding warpage and weld lines and evaluates the corresponding designs. The dominance-based constraint-handling technique handles the weld line design constraint without needing additional penalty factors. Finally, the master-slave distributed architecture reduces the formidable computational time required for injection molding optimization. To illustrate the high viability of DMPGA, this study provides an outer frame of a digital photo frame as an optimization example. The results of this study show that DMPGA cannot only effectively decrease maximum part warpage without violating the weld line constraint, but also conquer hurdles attributed to constraint handling and computational demand.

关键词： Injection molding optimization Multi-population genetic algorithm Moldflow simulation distributed parallel computing

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