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IEEE international workshop on Multi-/Many-core Computing Systems

作者： Orhan Kislal Wei Ding Mahmut Kandemir Ilteris Demirkiran Department of Computer Science and Engineering The Pennsylvania State University Embry-Riddle Aeronautical University

ISBN: (纸本)9781479910090

After hitting the power wall, the dramatic change in computer architecture from single core to multicore/manycore brings us new challenges on high performance computing, especially for the data intensive applications. Sparse matrix-vector multiplication (SpMV) is one of the most important computations in this area, and has therefore received a lot of attention in recent decades. In contrast to the uniform/regular dense matrix computations, SpMV's irregular data access patterns with compact data structure for storage make the SpMV optimization more complex than optimizing regular/dense matrix computation. In this work, we look at the SpMV optimization problem in the context of emerging multicores from a different architecture conscious perspective, and propose an optimization strategy that has three key components: mapping, scheduling and data layout reorganization. Specifically, the mapping component derives a suitable iteration-to-core mapping;the scheduling component determines the execution order of loop iterations assigned to each core in the target multicore architecture;and finally, the data layout reorganization component prepares multiple memory layouts for the source (input) vector customized for different row patterns. A distinguishing characteristic of our approach is that it is cache hierarchy aware, that is, all three components take the underlying cache hierarchy of the target multicore architecture into account, and therefore, the derived solution is, in a sense, customized to the target architecture. We evaluate the proposed strategy using 10 sparse matrices with two different multicore systems. Our experimental evaluation reveals that the proposed optimization algorithm brings significant performance improvements (up to 26.5%) over the unoptimized case.

关键词： algorithms Performance Compiler optimization Data Locality Data Transformation Loop Transformation Sparse Matrix-Vector Multiplication Multicore

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Frontiers in Algorithmics and Algorithmic Aspects in Information and Management: Third Joint international Conference, FAW-AAIM 2013, Dalian, China, June 26-28, 2013. Proceedings 1

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丛书名： Lecture Notes in Computer Science 7924

2013年

作者： Dániel Marx (auth.), Michael Fellows, Xuehou Tan, Binhai Zhu (eds.)

ISBN: (数字)9783642387562

ISBN: (纸本)9783642387555;9783642387562

This book constitutes the refereed proceedings of the 7th international Frontiers of Algorithmics workshop, FAW 2013, and the 9th international Conference on Algorithmic Aspects in Information and Management, AAIM 2013, jointly held in Dalian, China, in June 2013. The 33 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 60 submissions. The Joint Conference provide a focused forum on current trends of research on algorithms, discrete structures, operation research, combinatorial optimization and their applications, and will bring together international experts at the research frontiers in these areas to exchange ideas and to present significant new results. The mission of the Joint Conference is to stimulate the various fields for which algorithmics can become a crucial enabler, and to strengthen the ties between the Eastern and Western research communities of algorithmics and applications.

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applications of Ground Penetrating Radar in civil engineering — COST action TU1208

Applications of Ground Penetrating Radar in civil engineerin...

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international workshop on Advanced Ground Penetrating Radar (IWAGPR)

作者： Lara Pajewski Andrea Benedetto Xavier Derobert Antonis Giannopoulos Andreas Loizos Guido Manacorda Marian Marciniak Christina Plati Giuseppe Schettini Immo Trinks Department of Engineering Roma Tre University Rome Italy Institut Français Sciences Technologies Transports Aménagement Réseaux (IFSTTAR) LUNAM Université Bouguenais France School of Engineering Institute for Infrastructure and Environment University of Edinburgh Edinburgh UK Department of Transportation Planning and Engineering National Technical University of Athens Athens Greece Georadar Division IDS Ingegneria Dei Sistemi S.p.A. Pisa Italy National Institute of Telecommunications Warsaw Poland Ludwig Boltzmann Institute for Ludwig Boltzmann Institute for Archaeological prospection and Virtual Archaeology Vienna Austria

This paper focuses on the use of Ground Penetrating Radar (GPR) in civil engineering. Open issues in this field are identified and desirable advances in GPR technology, application procedures, data processing algorithms and analysis tools, are addressed. European associations, institutes and consortia interested in this topic are mentioned, together with the main relevant international events. The new COST (European COoperation in Science and Technology) Action TU1208 “Civil Engineering applications of Ground Penetrating Radar” is presented, started in April 2013: this interdisciplinary project offers important research opportunities and will strengthen European excellence in all the fields concerning the success of GPR technique, with a main focus on its applications in civil engineering. Four Working Groups (WGs) carry out the research activities: WGI focuses on the design of innovative GPR equipment, on the building of prototypes, as well as on the testing and optimization of new systems; WG2 focuses on the GPR surveying of pavement, bridges, tunnels and buildings, as well as on the sensing of underground utilities and voids; WG3 deals with the development of electromagnetic forward and inverse scattering methods and of advanced data processing algorithms; WG4 explores the use of GPR in fields different from civil engineering and the integration of GPR with other nondestructive testing techniques. The COST Action TU1208 is still open to the participation of new parties: in this paper, information is provided for scientists and scientific institutions willing to join the Action and participate to its activities.

关键词： Ground penetrating radar Europe Civil engineering Electromagnetic scattering Testing Electromagnetics Buildings

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A novel partitioning and tracing approach for distributed systems based on vector clocks

A novel partitioning and tracing approach for distributed sy...

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IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Robert Hoettger Burkhard Igel Erik Kamsties University of Applied Sciences and Arts Pimes Research Institute Dortmund Germany

Tracking, partitioning and tracing in modern dynamic high performance computing systems are three of the most innovative and important development aspects for performance optimization purposes and state-of-the-art advanced quality. This paper discusses these three aspects with respect to distributed systems and proposes new mechanisms for an advanced utilization of software in this domain. We present a specific tracking mechanism via vector clocks for model and code partitioning purposes and the determination of causality relations. Further, a tracing approach for an effective analysis and thereby utilization of code and the corresponding architecture is introduced. The combination of both approaches leads to a high degree of parallelism and a fine-grained structure of execution units, that further traced, supports a precise analysis of synchronous and asynchronous system's behavior as well as an optimal load balancing. The mechanisms are introduced with respect to a model based control engineering tool and event diagrams.

关键词： Clocks Vectors Parallel processing Partitioning algorithms optimization Computer architecture Load management

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A multi-objective genetic algorithm for community discovery

A multi-objective genetic algorithm for community discovery

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IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Ertan Bütün Mehmet Kaya Department of Computer Engineering Firat University Elazi□ÄŸ Turkey

Community discovery in complex network has become an interesting topic in recent years. Multi-objective optimizations can entirely handle community discovery problem instead of single objective optimizations. Thus a multi-objective genetic algorithm approach is proposed for community discovery in complex networks in this paper. We improved MOGA-Net [1] proposed by Pizzuti by applying effective searching on search space at genetic algorithm steps. We tested our approach and achieved better results on synthetic networks and real life networks.

关键词： Communities Genetic algorithms optimization Linear programming Sociology Statistics Genetics

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Cyber Security Problem based on Multi-Objective Distributed Constraint optimization Technique

Cyber Security Problem based on Multi-Objective Distributed ...

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Annual IEEE/IFIP international Conference on Dependable Systems and Networks workshops

作者： Tenda Okimoto Naoto Ikegai Katsumi Inoue Hitoshi Okada Tony Ribeiro Hiroshi Maruyama Transdisciplinary Research Integration Center Tokyo National Institute of Informatics Tokyo The Graduate University for Advanced Studies Tokyo Institute of Mathematical Statistics Tokyo

ISBN: (纸本)9781479901807

A cyber security problem is an important application domain for systems resilience. The increase of malware, computer viruses, and intensive cyber attacks are serious problems for our information society. In this paper, we introduce a new presentation of a cyber security problem. Our model is based on a Multi-Objective Distributed Constraint optimization Problem (MO-DCOP) which is a fundamental problem that can formalize various applications related to multi-agent cooperation. MO-DCOP is suitable for modeling a cyber security problem, since cyber security problems involve multiple criteria, e.g., risk (security), surveillance (privacy) and cost. Furthermore, MO-DCOP is a decentralized model. In this model, variables and constraints are distributed among agents. Since there exists no single agent which maintains all information, it is resilient against intensive cyber attacks. Furthermore, we develop a novel algorithm for solving a cyber security problem which utilizes well-known and widely used branch and bound technique and depth-first search strategy and finds all trade-off solutions. We also propose the extension of this algorithm which utilizes a preprocessing technique called soft Arc Consistency. The softAC is a well-known preprocessing technique which transforms a constraint optimization problem into a simplified problem that can be solved efficiently. In the experiments, we examine the run time of our proposed algorithms in cyber security problems and show that our algorithms can solve cyber security problems quickly.

关键词： Cyber Security Problem Multi-Objective Distributed Constraint optimization Network security Constrained optimization Runtime decentralised control Computer viruses information society

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SI-based scheduling of scientific experiments on Clouds

SI-based scheduling of scientific experiments on Clouds

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IEEE international workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Elina Pacini Cristian Mateos Carlos García Garino Universidad Nacional de Cuyo Mendoza AR ISISTAN-CONICET Tandil Buenos Aires Argentina

Scientists and engineers usually require huge amounts of computing power for performing their experiments. Precisely, Parameter Sweep Experiments (PSE) allow these kind of users to perform simulations by running the same scientific code with different input data, which results in many CPU-intensive jobs and thus computing environments such as Clouds must be used. We describe two Cloud schedulers based on two popular swarm intelligence (SI) techniques, namely ant colony optimization (ACO) and particle swarm optimization (PSO), to allocate virtual machines (VM) to physical Cloud resources. The main performance metrics to study are the number of serviced users by the Cloud -i.e., the number of Cloud users that the scheduler is able to successfully serve- and the total number of created VMs, in dynamic (non-batch) scheduling scenarios. Simulated experiments performed by using CloudSim and real PSE job data suggest that our schedulers, through a weighted metric, perform competitively with respect to the number of serviced users and achieve an effective assignment of VMs compared to a scheduler based on Genetic algorithms.

关键词： Measurement Silicon Processor scheduling Particle swarm optimization Dynamic scheduling Insects

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Comparison of GPU architectures for asynchronous communication with finite-differencing applications

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2012年第1期24卷 73-83页

作者： Playne, D. P. Hawick, K. A. Massey Univ Inst Informat & Math Sci Auckland New Zealand

Graphical processing units (GPUs) are good data-parallel performance accelerators for solving regular mesh partial differential equations (PDEs) whereby low-latency communications and high compute to communications ratios can yield very high levels of computational efficiency. Finite-difference time-domain methods still play an important role for many PDE applications. Iterative multi-grid and multilevel algorithms can converge faster than ordinary finite-difference methods but can be much more difficult to parallelize with GPU memory constraints. We report on some practical algorithmic and data layout approaches and on performance data on a range of GPUs with CUDA. We focus on the use of multiple GPU devices with a single CPU host and the asynchronous CPU/GPU communications issues involved. We obtain more than two orders of magnitude of speedup over a comparable CPU core. Copyright (C) 2011 John Wiley & Sons, Ltd.

关键词： finite-difference GPU multiple device CUDA

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Modelling process and optimization of EMC filters for power electronics applications

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COMPEL-THE international JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING 2012年第3期31卷 747-763页

作者： Gerbaud, Laurent Toure, Baidy Schanen, Jean-Luc Carayon, Jean-Pierre Grenoble Elect Engn Lab G2Elab St Martin Dheres France Aerosp Toulouse SAS Toulouse France Liebherr Aerosp Toulouse SAS Toulouse France

Purpose - The frequency simulation and optimisation of electromagnetic compatibility (EMC) filter is often computation time consuming. The purpose of this paper is to propose an approach for easy and fast modelling and optimization of power electronics structures. Design/methodology/approach - The paper proposes an approach for easy and fast modelling and optimization of power electronics structures. It focuses on the EMC filter design. To achieve this task time simulation, FFT and automatic frequency modelling are combined. Findings - An automatic frequency modelling is proposed and also gives automatically the model gradients. Therefore, the model can be used to optimize the EMC filter, but also can help in choosing its topology. Several optimization algorithms are used and compared. Research limitations/implications - The power electronics load is supposed to be a set of predefined harmonic sources, obtained by time simulation + FFT before the optimisation process. Practical implications - The frequency model allows for the rapid designing and comparing of several structures or modelling hypothesis with regard to the parasitic elements and circuit imperfections. Originality/value - The frequency model is automatically generated, and sizing criteria on the component (e.g. inductors, capacitor) can be added in an analytical form, for example, to deal with volume or mass criteria.

关键词： Electric power systems Power electronics filters Optimum design Automatic frequency modelling Electromagnetic compatibility Filter design optimization

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A multilevel Thresholding Method for Image Segmentation Using a Novel Hybrid Intelligent Approach

A Multilevel Thresholding Method for Image Segmentation Usin...

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12th international Conference on Hybrid Intelligent Systems (HIS)

作者： Yazdani, Danial Sepas-Moghaddam, Alireza Arabshahi, Alireza Dehshibi, Mohammad Mahdi Islamic Azad Univ Mashhad Branch Young Researchers Club Mashhad Iran Univ Informat Technol & Management Tehran Iran Islamic Azad Univ Qazvin Branch Dept Comp & IT Engn Qazvin Iran Islamic Azad Univ Parand Branch Dept Comp & IT Engn Tehran Iran

ISBN: (纸本)9781467351157;9781467351164

Swarm intelligence algorithms have been extensively used in clustering based applications e.g. image segmentation which is one of the fundamental components in image analysis and pattern recognition domains. Particle swarm optimization is amongst swarm intelligence algorithms that performs based on population and random search. In this paper, a hybrid algorithm based on PSO, k-means and learning automata is proposed for image segmentation. In the proposed algorithm, learning automata is responsible for activating and deactivating PSO and k-means methods based on current conditions of the segmentation problem. The proposed approach along with other comparative studies has been applied for segmenting benchmark images. Efficiency of the proposed method has been compared with that of other methods and experimental results show the superiority proposed algorithm.

关键词： Image Segmentation Data Clustering Particle Swarm optimization Learning Automata multilevel Thresholding

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