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Supercomputing - 29th international Conference, ISC 2014, Proceedings

Supercomputing - 29th International Conference, ISC 2014, Pr...

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29th international Supercomputing Conference, ISC 2014

ISBN: (纸本)9783319075174

The proceedings contain 35 papers. The topics discussed include: SNAP: strong scaling high fidelity molecular dynamics simulations on leadership-class computing platforms;exascale radio astronomy: can we ride the technology wave?;on the performance portability of structured grid codes on many-core computer architectures;performance predictions of multilevel communication optimal LU and QR factorizations on hierarchical platforms;hourglass: a bandwidth-driven performance model for sorting algorithms;sparsifying synchronization for high-performance shared-memory sparse triangular solver;automatic exploration of potential parallelism in sequential applications;impact of future trends on exascale grid and cloud computing;and framework and modular infrastructure for automation of architectural adaptation and performance optimization for HPC systems.

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A stochastic coordinate descent primal-dual algorithm and applications

A stochastic coordinate descent primal-dual algorithm and ap...

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IEEE workshop on Machine Learning for Signal Processing

作者： Pascal Bianchi Walid Hachem Iutzeler Franck Telecom ParisTech Paris France CNRS LTCI Telecom ParisTech Paris France Supélec Gif-sur-Yvette France

First, we introduce a splitting algorithm to minimize a sum of three convex functions. The algorithm is of primal dual kind and is inspired by recent results of Vũ and Condat. Second, we provide a randomized version of the algorithm based on the idea of coordinate descent. Finally, we address two applications of our method: (i) for stochastic minibatch optimization; and (ii) for distributed optimization.

关键词： Signal processing algorithms optimization Convex functions Approximation algorithms Machine learning algorithms Minimization Telecommunications

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Musculoskeletal Modeling and Physiological Validation 9

Musculoskeletal Modeling and Physiological Validation

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9th IEEE international workshop on Advanced Robotics and its Social Impacts (IEEE ARSO)

作者： Murai, Akihiko Takeichi, Kazunari Miyatake, Taira Nakamura, Yoshihiko Univ Tokyo Grad Sch Informat Sci & Technol Dept Mechanoinformat Bunkyo Ku 7-3-1 Hongo Tokyo Japan

ISBN: (纸本)9781479969685

Digital human models are applied in human motion analysis and simulation. They can be applied in rehabilitation, sports science, biomedicine, and so on. The difficulty of validation of models and analysis algorithms constricts their practical usage. In this paper, we show our work on human motion analysis using a whole-body musculoskeletal model and validate the analysis results in terms of physiology. First, we build the detailed musculoskeletal model that represents the kinematics and dynamics characteristics of human body. Optical motion capture, force plates and electromyography(EMG) are used for human motion capture. We estimate the muscle tensions required to generate the captured motion sequence based on an inverse kinematics and dynamics computation and a mathematical optimization. The estimated muscle tensions for locomotion cycles are compared with the tensions computed from the simultaneously measured EMG data and a physiological muscle model. The model and the analysis algorithm are also applied to a neurophysiological phenomenon, the nontrivial preferred direction that is a result of the cosine tuning. Our model and analysis algorithm achieves results that correspond with the experimental physiological data well. The possible applications of our model and algorithm involve rehabilitation, sports science, biomedicine, and robotics, e.g. a controller of an exoskeletal robot for human support.

关键词： image motion analysis image sequences mathematical analysis medical image processing optimisation physiology EMG cosine tuning digital human models dynamics computation electromyography force plates human motion analysis human motion capture human motion simulation inverse kinematics locomotion cycles mathematical optimization motion sequence muscle tensions musculoskeletal modeling optical motion capture physiological muscle model physiological validation whole body musculoskeletal model Computational modeling Data models Electromyography Joints Mathematical model Muscles Electromyogram motion sequence force plate inverse kinematics Human motion image motion analysis motion capture data models Medical image processing image sequences muscles mathematical analysis Computational modeling Physiology Joints

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MIC-SVM: Designing A Highly Efficient Support Vector Machine For Advanced Modern Multi-Core and Many-Core Architectures

MIC-SVM: Designing A Highly Efficient Support Vector Machine...

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IEEE 28th international Parallel & Distributed Processing Symposium (IPDPS)

作者： You, Yang Song, Shuaiwen Leon Fu, Haohuan Marquez, Andres Dehnavi, Maryam Mehri Barker, Kevin Cameron, Kirk W. Randles, Amanda Peters Yang, Guangwen Tsinghua Univ Ctr Earth Sci Minist Educ Key Lab Earth Syst Modeling Beijing 100084 Peoples R China Tsinghua Univ TNList Beijing Peoples R China Pacific NW Natl Lab Richland WA 02139 USA Harvard Univ MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA Virginia Tech Blacksburg VA USA Lawrence Livermore Natl Lab Livermore CA USA

ISBN: (纸本)9780769552071

Support Vector Machine (SVM) has been widely used in data-mining and Big Data applications as modern commercial databases start to attach an increasing importance to the analytic capabilities. In recent years, SVM was adapted to the field of High Performance Computing for power/performance prediction, auto-tuning, and runtime scheduling. However, even at the risk of losing prediction accuracy due to insufficient runtime information, researchers can only afford to apply offline model training to avoid significant runtime training overhead. Advanced multi-and many-core architectures offer massive parallelism with complex memory hierarchies which can make runtime training possible, but form a barrier to efficient parallel SVM design. To address the challenges above, we designed and implemented MIC-SVM, a highly efficient parallel SVM for x86 based multi-core and many-core architectures, such as the Intel Ivy Bridge CPUs and Intel Xeon Phi co-processor (MIC). We propose various novel analysis methods and optimization techniques to fully utilize the multilevel parallelism provided by these architectures and serve as general optimization methods for other machine learning tools. MIC-SVM achieves 4.4-84x and 18-47x speedups against the popular LIBSVM, on MIC and Ivy Bridge CPUs respectively, for several real-world data-mining datasets. Even compared with GPUSVM, run on a top of the line NVIDIA k20x GPU, the performance of our MIC-SVM is competitive. We also conduct a cross-platform performance comparison analysis, focusing on Ivy Bridge CPUs, MIC and GPUs, and provide insights on how to select the most suitable advanced architectures for specific algorithms and input data patterns.

关键词： Support Vector Machine Multi & Many-Core architectures Parallelization optimization Techniques Performance Analysis

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multilevel thresholding for image segmentation based on parallel distributed optimization

Multilevel thresholding for image segmentation based on para...

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international Conference of Soft Computing and Pattern Recognition (SOCPAR)

作者： Mohamed Sandeli Mohamed Batouche Software and Information Technology Department University Constantine 2 ALGERIA Computer Science and Applications Department University Constantine 2 ALGERIA

Image segmentation is a platform for many high-level applications. It aims to identify the different homogeneous regions of an image. In our work, we cast the problem as a parallel distributed optimization task and we present a new method for image segmentation by multilevel thresholding based on generalized island model (GIM). This model is characterized by the cooperation of three metaheuristics namely Particle Swarm optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC). The cooperation is ensured by the use of a migration pattern the purpose of which is to avoid getting stuck in local optima. The effectiveness of the proposed method has been assessed and compared to each of the algorithms of the GIM model when used separately and other methods from the literature like Darwinian PSO (DPSO), Fractional-Order Darwinian PSO (FO-DPSO). The obtained results are very promising and show the positive impact of the use of a parallel distributed model. They also show that the proposed method competes and even outperforms the other methods.

关键词： Image segmentation optimization Sociology Statistics Genetic algorithms Mathematical model MATLAB

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Performances optimization and characteristics of the voltage generated by multilevel inverters

Performances optimization and characteristics of the voltage...

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international Conference on Applied and Theoretical Electricity (ICATE)

作者： Horia Balan Mircea Buzdugan Adrian Augustin Pop Radu Adrian Munteanu Power Engineering and Management Technical University of Cluj-Napoca Cluj-Napoca Romania Electrical Engineering and Measurements Technical University of Cluj-Napoca Cluj-Napoca Romania

Several fixed frequency applications of multilevel converters require a very low level of distortion factor of the output voltage. Bringing the output voltage to a form as close as possible to a sine wave is usually done through linearization methods of the Newton-Raphson algebraic equations. The method proposed in section III uses for the waveforms optimization a genetic algorithm, having a positive impact on the total harmonic distortion reduction. Experimental validation of the method is performed using a programmable source which drives an induction motor.

关键词： Inverters Harmonic analysis Commutation optimization Genetic algorithms Equations Total harmonic distortion

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Determination of microscopic parameters of piezoceramic materials under electrical loading using genetic algorithm

Determination of microscopic parameters of piezoceramic mate...

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IEEE international Symposium on applications of Ferroelectrics (ISAF)

作者： J. Bustillo M. Domenjoud J. Fortineau G. Gautier M. Lethiecq GREMAN UMR 7347 University of Tours CEA Tours France

The purpose of this study is the characterization of microscopic parameters of piezoceramic materials, such as spontaneous polarization and spontaneous strain. In previous works, a model has been developed by bridging characteristics of microscopic domain distribution into the macroscopic behavior. It reproduces longitudinal strain and electrical displacement as a function of uniaxial electrical loading, according to material parameters and applied electrical field. optimization is performed between theoretical and experimental hysteresis curves. This method is based on a genetic algorithm procedure in order to ensure robust convergence even if the system is multimodal. Materials used in this study are PLZT8/65/35 and PZT-5A. After optimization, experimental curves are well fitted to theoretical curves and a good agreement has been shown between retrieved parameters and values reported in literature. This validates domain wall modeling and genetic algorithm as an efficient way to characterize piezoceramic materials under harsh operating conditions.

关键词： Genetic algorithms Materials optimization Strain Loading Convergence Piezoelectric polarization

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Bio-inspired heuristic for optimizing protein structure alignment using distributed modified extremal optimization

Bio-inspired heuristic for optimizing protein structure alig...

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IEEE international workshop on Computational Intelligence & applications (IWCIA)

作者： Keiichi Tamura Hajime Kitakami Yoshifumi Takahashi Graduate School of Information Sciences Hiroshima City University Hiroshima Japan

Proteins with similar three-dimensional structures usually have similar biological functions and interactions in living organisms. Thus, detecting similar structures in proteins is presently one of the most attractive research topics in computational biology. Many techniques for the comparison of protein structures are based on protein structure alignment. This is similar to sequence alignment, and is one of the most effective methods for extracting similar structures. The contact map overlap (CMO) maximization problem (hereafter, the CMO problem) is formulated as a combinatorial optimization to find the optimal structure alignment. The CMO problem is known to be NP-hard; hence, a number of researchers have been developing heuristic approaches. In this paper, we propose a novel bio-inspired heuristic algorithm using distributed modified extremal optimization (DMEO) for the CMO problem. DMEO is a hybrid of population-based modified extremal optimization (PMEO) and distributed genetic algorithms inspired by the island model. In the island model, a population is divided into two or more sub-populations (called islands), and each island evolves separately. Islands can maintain different types of individuals at the end of alternation of generations. Therefore, DMEO can maintain more diversity than PMEO. The experiments compared the DMEO-based heuristic with the PMEO-based heuristic, and the results show that DMEO performs well for 25 out of 32 protein pairs.

关键词： Proteins optimization Sociology Statistics Heuristic algorithms Biological system modeling Linear programming

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ILP model and algorithms for restoration of anycast flows in Elastic Optical Networks

ILP model and algorithms for restoration of anycast flows in...

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international workshop on Reliable Networks Design and Modeling (RNDM)

作者： Krzysztof Walkowiak Michał Kucharzak Paweł Kopeć Andrzej Kasprzak Department of Systems and Computer Networks Wroclaw University of Technology Poland

Elastic Optical Network (EON) is a promising technology proposed recently to provide flexible and multi-bitrate data transmission in the optical layer. EONs utilize various modulation format conversion and smaller spectrum granularity, what provide more efficient use of spectrum resources comparing to currently used fix-grid WDM networks. Concurrently, growing popularity of network services provided by Data Centers located in different network nodes and related to cloud computing and Content Delivery Network applications triggers the need to address anycast transmissions as an effective way to improve network performance. This paper focuses on modeling and optimization of anycast flows in EONs in the context of network restoration. Specifically, we formulate an original NP-hard Routing and Spectrum Allocation for Restoration of Anycast Flows (RSA/RAF) problem. In order to solve the problem, we design, implement and evaluate four greedy algorithms and a metaheuristic derived from Simulated Annealing. Extensive numerical experiments prove high practical applicability of presented algorithms.

关键词： Heuristic algorithms optimization Tuning Modulation Resource management Optical fiber networks Routing

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A Generic Algorithmic Framework to Solve Special Versions of the Set Partitioning Problem

A Generic Algorithmic Framework to Solve Special Versions of...

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international Conference on Tools for Artificial Intelligence (ICTAI)

作者： Robin Lamarche-Perrin Yves Demazeau Jean-Marc Vincent Max - Planck-Institute for Mathematics in the Sciences Leipzig Germany CNRS Laboratoire d'lnformatique de Grenoble France Université Grenoble Alpes Laboratoire d'lnformatique de Grenoble France

ISBN: (纸本)9781479965731

Given a set of individuals, a collection of subsets, and a cost associated to each subset, the Set Partitioning Problem (SPP) consists in selecting some of these subsets to build a partition of the individuals that minimizes the total cost. This combinatorial optimization problem has been used to model dozens of problems arising in specific domains of Artificial Intelligence and Operational Research, such as coalition structures generation, community detection, multilevel data analysis, workload balancing, image processing, and database optimization. All these applications are actually interested in special versions of the SPP where assumptions regarding the admissible subsets constraint the search space and allow tractable optimization algorithms. However, there is a major lack of unity regarding the identification, the formalization, and the resolution of these strongly-related problems. This paper hence proposes a generic framework to design dynamic programming algorithms that fit with the particular algebraic structure of special versions of the SPP. We show how this framework can be applied to two well-known versions, thus opening a unified approach to solve new ones that might arise in the future.

关键词： Partitioning algorithms Heuristic algorithms Sociology Statistics optimization Dynamic programming Search problems

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