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检索条件"任意字段=Conference on High Performance Algorithms and Software for Nonlinear Optimization"

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Task Partitioning Oriented Architecture Exploration Method for Dynamic Reconfigurable Architectures

Task Partitioning Oriented Architecture Exploration Method f...

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IFIP International conference on Very Large Scale Integration (VLSI-SoC)

作者： Ittetsu Taniguchi Kyoko Ueda Keishi Sakanushi Yoshinori Takeuchi Masaharu Imai Graduate School of Information Science and Technology Osaka University Osaka Japan

Many dynamic reconfigurable processors are evolving rapidly that offer fast and run-time reconfiguration. To efficiently utilize run-time reconfiguration, we must consider additional memory access cycles due to reconfiguration. In general, dynamic reconfigurable processors read input data from external memory after reconfiguration and write output data to external memory before the next reconfiguration. To realize high performance, we must schedule tasks considering the total execution cycles that include reconfiguration time and memory access overhead. In this paper, we propose a parameterized reconfigurable processor model (PRP-model) and a task partitioning optimization algorithm for the architecture exploration of multicontext dynamic reconfigurable processors. The proposed task partitioning algorithm corresponds to various dynamic reconfigurable architectures by changing parameters and can realize the evaluation of a lot of reconfigurable architectures. Experimental results showed that the proposed algorithm can quickly find near optimal solutions. Using the proposed algorithm, designers can easily evaluate the performance of various dynamic reconfigurable architectures for specific applications

关键词： Reconfigurable architectures Partitioning algorithms Memory architecture Application software Runtime Read-write memory Information systems Hardware Circuits Field programmable gate arrays

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3D Surface Matching and Recognition Using Conformal Geometry

3D Surface Matching and Recognition Using Conformal Geometry

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Sen Wang Yang Wang Miao Jin Xianfeng Gu D. Samaras Computer Science Department State University of New York Stony Brook Stony Brook NY USA

3D surface matching is a fundamental issue in computer vision with many applications such as shape registration, 3D object recognition and classification. However, surface matching with noise, occlusion and clutter is a challenging problem. In this paper, we analyze a family of conformal geometric maps including harmonic maps, conformal maps and least squares conformal maps with regards to 3D surface matching. As a result, we propose a novel and computationally efficient surface matching framework that uses least squares conformal maps. According to conformal geometry theory, each 3D surface with disk topology can be mapped to a 2D domain through a global optimization and the resulting map is a diffeomorphism, i.e., one-to-one and onto. This allows us to simplify the 3D surface-matching problem to a 2D image-matching problem, by comparing the resulting 2D conformal geometric maps, which are stable, insensitive to resolution changes and robust to occlusion and noise. Therefore, highly accurate and efficient 3D surface matching algorithms can be achieved by using conformal geometric maps. Finally, the performance of conformal geometric maps is evaluated and analyzed comprehensively in 3D surface matching with occlusion, noise and resolution variation. We also provide a series of experiments on real 3D face data that achieve high recognition rates.

关键词： Least squares methods Computational geometry Computer vision Application software Shape Object recognition Noise shaping Harmonic analysis Topology Image resolution

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nonlinear programming: algorithms, software, and applications - From small to very large scale optimization

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21st conference on System Modeling and optimization

作者： Schittkowski, K Zillober, C Univ Bayreuth Dept Comp Sci D-95440 Bayreuth Germany

ISBN: (纸本)1402077602

We introduce some methods for constrained nonlinear programming that are widely used in practice and that are known under the names SQP for sequential quadratic programming and SCP for sequential convex programming. In both cases, convex subproblems are formulated, in the first case a quadratic programming problem, in the second case a separable nonlinear program in inverse variables. The methods are outlined in a uniform way and the results of some comparative performance tests are listed. We especially show the suitability of sequential convex programming methods to solve some classes of very large scale nonlinear programs, where implicitly defined systems of equations seem to support the usage of inverse approximations. The areas of interest are structural mechanical optimization, i.e., topology optimization, and optimal control of partial differential equations after a full discretization. In addition, a few industrial applications and case studies are shown to illustrate practical situations under which the codes implemented by the authors are in use.

关键词： sequential quadratic programming SQP sequential convex programming SCP comparative tests industrial applications topology optimization optimal control of semilinear elliptic equations

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Dynamic optimization of migration topology in internet-based distributed genetic algorithms 05

Dynamic optimization of migration topology in internet-based...

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Genetic and Evolutionary Computation conference

作者： Berntsson, Johan Tang, Maolin Queensland Univ Technol Sch Software Engn & Data Commun Brisbane Qld 4001 Australia

ISBN: (纸本)1595930108

Distributed Genetic algorithms (DGAs) designed for the Internet have to take its high communication cost into consideration. For island model GAs, the migration topology has a major impact on DGA performance. This paper describes and evaluates an adaptive migration topology optimizer that keeps the communication load low while maintaining high solution quality. Experiments on benchmark problems show that the optimized topology outperforms static or random topologies of the same degree of connectivity. The applicability of the method on real-world problems is demonstrated on a hard optimization problem in VLSI design.

关键词： performance algorithms genetic algorithms migration topology adaptation Internet computing

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Efficient 3D nonlinear warping of computed tomography: Two high performance implementations using OpenGL

Efficient 3D nonlinear warping of computed tomography: Two h...

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Medical Imaging 2005 conference

作者： Levin, D Dey, D Slomka, P Univ Western Ontario Dept Med Biophys London ON Canada

ISBN: (纸本)0819457183

We have implemented two hardware accelerated Thin Plate Spline (TPS) warping algorithms. The first algorithm is a hardware-software approach (HW-TPS) that uses OpenGL Vertex Shaders to perform a grid warp. The second is a Graphics Processor based approach (GPU-TPS) that uses the OpenGL Shading Language to perform all warping calculations on the GPU. Comparison with a software TPS algorithm was used to gauge the speed and quality of both hardware algorithms. Quality was analyzed visually and using the Sum of Absolute Difference (SAD) similarity metric. Warping was performed using 92 user-defined displacement vectors for 512x512x173 serial lung CT studies, matching normal-breathing and deep-inspiration scans. On a Xeon 2.2 Ghz machine with an ATI Radeon 9800XT GPU the GPUTPS required 26.1 seconds to perform a per-voxel warp compared to 148.2 seconds for the software algorithm. The HWTPS needed 1.63 seconds to warp the same study while the GPU-TPS required 1.94 seconds and the software grid transform required 22.8 seconds. The SAD values calculated between the outputs of each algorithm and the target CT volume were 15.2%, 15.4% and 15.5% for the HW-TPS, GPU-TPS and both software algorithms respectively. The computing power of ubiquitous 3D graphics cards can be exploited in medical image processing to provide order of magnitude acceleration of nonlinear warping algorithms without sacrificing output quality.

关键词： nonlinear warping thin plate spline GPU OpenGL hardware-accelerated

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nonlinear Dynamic Data Reconciliation using general optimization solvers within Matlab

Nonlinear Dynamic Data Reconciliation using general optimiza...

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International conference on Integrated Modeling and Analysis in Applied Control and Automation, IMAACA 2005, Held at the International Mediterranean Modeling Multiconference, I3M 2005

作者： Pérez-Correa, Ricardo Biegler, Lorenz T. Departamento de Ingeniería Química y Bioprocesos Pontificia Universidad Católica de Chile Vicuña Mackenna 4860 Santiago Chile Dept. of Chemical Engineering Doherty Hall Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA 15213 United States

ISBN: (纸本)9781629934693

Reliable measurements and parameter estimates are required in order to properly apply Model Based Control in industrial facilities. Powerful algorithms have been described in the literature for nonlinear Dynamic Data Reconciliation (NDDR) of chemical processes based on nonlinear programming techniques. In some instances, these have been shown to be more reliable than the commonly used Extended Kalman Filtering (EKF) approach. Often, efficient NDDR algorithms require the provision of analytical derivatives and are difficult to apply, requiring a high degree of coding. Here we present and evaluate, using a simple chemical reactor model, an easy to use NDDR methodology applying three general purpose nonlinear programming codes within Matlab environment. The NDDR problem is tackled using the simultaneous optimization solution approach, which has been shown to be more efficient than the sequential approach. The performance of the NDDR algorithm has been compared with that of a second order nonlinear filter and practical guidelines to simplify the application of these algorithms in real time are provided.

关键词： Extended Kalman filters

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Multiobjective evolutionary optimal design of N-version software system

Multiobjective evolutionary optimal design of N-version soft...

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16th European Safety and Reliability conference, ESREL 2005

作者： Yamachi, H. Yamamoto, H. Tsujimura, Y. Nippon Institute of Technology Japan Tokyo Metropolitan Institute of Technology Japan

ISBN: (纸本)0415383420

N-version Programming (NVP) is a programming approach to fault tolerant software systems employs functionally equivalent, yet independently developed software components. Generally, an optimization model for NVP is used for selecting the optimal set of versions for each module. We formulate the optimal design problem of NVP as a bi-objective 0-1 nonlinear integer programming problem. And to solve the problem, a Multi-objective Genetic Algorithm (MOGA) is employed. When implementing genetic algorithm, using an appropriate genetic representation scheme is one of the most important issues to good performance in genetic search. We employ the random-key representation in our MOGA to provide effective genetic search ability. Our MOGA is based on elitism, i.e., we introduce the Pareto-based selection. © 2005 Taylor & Francis Group, London.

关键词： Genetic algorithms

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Three parallel algorithms for solving nonlinear systems and optimization problems

Three parallel algorithms for solving nonlinear systems and ...

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6th International conference - high performance Computing for Computational Science - VECPAR 2004

作者： Peinado, Jesús Vidal, Antonio M. Departamento de Sistemas Informáticos y Computación Universidad Politécnica de Valencia Valencia 46071 Spain

In this work we describe three sequential algorithms and their parallel counterparts for solving nonlinear systems, when the Jacobian matrix is symmetric and positive definite. This case appears frequently in unconstrained optimization problems. Two of the three algorithms are based on Newton's method. The first solves the inner iteration with Cholesky decomposition while the second is based on the inexact Newton methods family, where a preconditioned CG method has been used for solving the linear inner iteration. In this latter case and to control the inner iteration as far as possible and avoid the oversolving problem, we also parallelized several forcing term criteria and used parallel preconditioning techniques. The third algorithm is based on parallelizing the BFGS method. We implemented the parallel algorithms using the SCALAPACK library. Experimental results have been obtained using a cluster of Pentium II PC's connected through a Myrinet network. To test our algorithms we used four different problems. The algorithms show good scalability in most cases. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Parallel algorithms

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CHIADO - Compilation of high-level computationally intensive algorithms to dynamically reconfligurable computing systems

CHIADO - Compilation of high-level computationally intensive...

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conference on VLSI Circuits and Systems II

作者： Cardoso, JMP Univ Algarve Fac Sci & Technol P-8000117 Faro Portugal

ISBN: (纸本)0819458325

Reconfigurable computing has already confirmed a significant potential for accelerating certain computing tasks. However, the most successful applications relied on user expertise to design a specific architecture implemented by the hardware structures of the reconfigurable computing device. Hence, one of the most challenging issues is to map, efficiently and automatically, computations (described in software programming languages) to reconfigurable computing devices. This paper presents CHIADO, a research project aiming a compiler framework to map efficiently software programs to reconfigurable computing platforms, especially the ones based on FPGA (Field-Programmable Gate Array) devices. The framework is also intended to support research of new optimization techniques. The project, based on our previous work on compiling Java bytecodes to FPGAs, focuses on high-performance solutions, schemes to estimate the impact of some transformations supported by the compiler (partial/full loop unrolling), and schemes to take advantage of dynamic reconfiguration (e.g., temporal partitioning). This paper gives an overview about the CHIADO project, shows the framework, and enumerates the main project goals.

关键词： compilation reconfigurable computing FPGAs

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An efficient multi-objective evolutionary algorithm: OMOEA-II

An efficient multi-objective evolutionary algorithm: OMOEA-I...

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3rd International conference on Evolutionary Multi-Criterion optimization (EMO 2005)

作者： Zeng, SY Yao, SZ Kang, LS Liu, Y China Univ Geosci Dept Comp Sci Wuhan 430074 Peoples R China Zhuzhou Inst Technol Dept Comp Sci Zhuzhou 412008 Hunan Peoples R China Wuhan Univ State Key Lab Software Engn Wuhan 430072 Hubei Peoples R China

ISBN: (纸本)3540249834

An improved orthogonal multi-objective evolutionary algorithm (OMOEA), called OMOEA-II, is proposed in this paper. Two new crossovers used in OMOEA-II are orthogonal crossover and linear crossover. By using these two crossover operators, only small orthogonal array rather than large orthogonal array is needed for exploiting optimal in the global space. Such reduction in orthogonal array can avoid exponential creation of solutions of OMOEA and improve the performance in robusticity without degrading precision and distribution of solutions. Experimental results show that OMOEA-II can solve problems with high dimensions and large number of local Pareto-optimal fronts better than some existing algorithms recently reported in the literatures.

关键词： evolutionary algorithms multi-objective optimization Pareto optimal set

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