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检索条件"任意字段=9th International Conference on Parallel and Distributed Computing, Applications and Technologies"

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Non-clairvoyant Assignment of Bag-of-Tasks applications Across Multiple Clouds

Non-clairvoyant Assignment of Bag-of-Tasks Applications Acro...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： M. Hoseiny Farahabady Young Choon Lee Albert Y. Zomaya The University of Sydney Sydney NSW AU Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney NSW Australia

ISBN: (纸本)9781467357043

Bag-of-Tasks applications are often composed of a large number of independent tasks, hence, they can easily scale out. With public clouds, the (dynamic) expansion of resource capacity in private clouds is much facilitated. Clearly, cost efficiently running BoT applications in a multi-cloud environment is of great practical importance. In this paper, we investigate how efficiently multiple clouds can be exploited for running BoT applications and present a fully polynomial time randomized approximation scheme (FPRAS) as a novel task assignment algorithm for BoT applications. the resulting task assignment can be optimized in terms of cost, make span or the tradeoff between them. the objective function incorporated into our algorithm is devised in the way the optimization objective is tunable based on user preference. Our task assignment decisions are made without any prior knowledge of the processing time of tasks, i.e., non-clairvoyant task assignment. We adopt a Monte Carlo sampling method to estimate unknown task running time. the experimental results shows our algorithm approximates the optimal solution with little overhead.

关键词： Cloud computing Estimation Equations Optimization Mathematical model Linear programming Approximation methods

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A QoS Scheduling Scheme with Availability Constraint in distributed Systems

A QoS Scheduling Scheme with Availability Constraint in Dist...

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Tong Zhao Kenli Li Zheng Xiao Qin Xiao College of Information Science and Engineering Hunan University Changsha Hunan CN College of Information Science and Engineering Hunan University Changsha China China Auburn University Auburn AL US

An efficient resource management mechanism is important in a heterogeneous system to discover available resources, to allocate an appropriate subset of resources to applications, and to map data or tasks onto selected resources. the key component, tasks scheduling, draws our attention. Make span is the principal concern many existing researches. But, other QoS requirements are also important in more and more realistic applications. Like Grid service it is expected that the service provider be reliable, robust, or highly available. In this study, an existing availability-aware scheduling model called SSAC is investigated first. then, we proposed an optimization approach to increase the availability and to reduce the make span of tasks running in heterogeneous systems. three quantitative conditions are used to guide the optimization. Our experimental results show that compared with three existing solutions (Minmin, SSAC and ACO), our algorithm significantly improves the availability and performance of multiclass tasks running in heterogeneous systems.

关键词： Availability Schedules Optimization Scheduling Computational modeling Scheduling algorithms

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the parallel computing of a molecular docking algorithm using the JavaSpaces service

The parallel computing of a molecular docking algorithm usin...

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international conference on Sciences of Electronics, technologies of Information and Telecommunications (SETIT)

作者： Mahdjoub Youcef Messabih Belhadri IVARM Université des Sciences et de la Technologie d'Oran Algeria Université des Sciences et de la Technologie d'Oran Algeria

the molecular docking is the focus of practical applications such as protein engineering and drug design. A docking algorithm is a procedure that predicts the assembly of two molecules like a key and a lock. To screen a large library of molecules, a docking algorithm requires high performance computing. parallel and distributed applications have long been recognized as powerful computational tools and effective in the field of bioinformatics. Jini technology is one of the powerful infrastructures network for building and deploying distributed systems that are organized as a federation of services. JavaSpaces is one of the services that come bundled with Jini, it is a shared associative memory accessible by the network and allows an easily developing of a massively parallel and distributed applications. this paper discusses the use of the JavaSpaces service to build a distributed application in order to minimize the running time of a molecular docking algorithm.

关键词： Proteins parallel processing Prediction algorithms Computational modeling Load modeling Java Computers

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Vitrall: Web-based distributed visualization system for creation of collaborative working environments 1

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9th international conference on parallel Processing and Applied Mathematics, PPAM 2011

作者： Śniegowski, Piotr Blazewicz, Marek Grzelachowski, Grzegorz Kuczyński, Tomasz Kurowski, Krzysztof Ludwiczak, Bogdan Poznan Supercomputer and Networking Center Z. Noskowskiego 12/14 61-704 Poznań Poland

ISBN: (数字)9783642314643

ISBN: (纸本)9783642314636

Advanced parallel computing solutions using GPU for general purpose processing are becoming more and more popular. applications like CFD or weather modeling take an extensive speed up using GPU-based clusters. Still, original purpose of graphic processing units - visualization, is not exploited as much as it could be in such powerful processing centres. Main reason of that situation is their fundamental difference from classic desktop configurations: being a structure remote and hidden from the actual viewer. Already existing GPU-based architectures consisting of many processing units may be used for visualization of complex issues from many points of view and in resolutions that are not accessible for single GPUs in real-time. Visualization is a very efficient way of collaboration, especially when collaborators can interact with presented content in a natural way, for example using multi-touch devices. Vitrall embraces these methods by introducing possibility of linkage between modern interfaces and complex visualizations. this paper will begin with summary of several researches that where conducted to establish actual concept of the Vitrall system. Next, proposed architecture of Vitrall will be introduced, following main and secondary usage scenarios. Finally, some of Vitrall's specific configurations will be shown, like real-time stereoscopic visualization. © 2012 Springer-Verlag.

关键词： Graphics processing unit

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parallelisation strategies for large scale cellular automata frameworks in pharmaceutical modelling

Parallelisation strategies for large scale cellular automata...

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2012 10th Annual international conference on High Performance computing and Simulation, HPCS 2012

作者： Bezbradica, Marija Crane, Martin Ruskin, Heather J. Centre for Scientific Computing and Complex Systems Modelling School of Computing Dublin City University Dublin 9 Ireland

ISBN: (纸本)9781467323598

Cellular Automata (CA) properties facilitate the detail required for the bottom-up approach to modelling and simulation of a broad range of physico-chemical reactions. In pharmaceutical applications, CA models use a combination of discrete-event rules based on probabilistic distributions and fundamental physical laws to predict the behaviour of active substances (drug molecules) and structural changes in Drug Dissolution Systems (DDS) over time. Several models of this type have been described so far in the scientific literature. Yet, practical applications are lacking in the context of large-scale, high-precision, high-fidelity simulations. the key obstacle to parallelisation of such models is not only the amount of data involved, but also the fact that many of these models incorporate agent-like behaviour within the CA framework in order to describe pharmaceutical components. this makes communication across process boundaries expensive. In this paper, we apply different parallelisation strategies to a large scale CA framework, used to model coated drug spheres. We use two parallel-computing application programming interfaces (APIs), namely OpenMP and MPI, to partition the simulation space. We analyse the applicability of each API to the problem individually, as well as in the hybrid solution. We examine speedup potential and overhead for local and global communication for simulation speed and solution scalability. For these types of problems, our results show that performance is much improved for appropriate combinations of parallelisation solutions. © 2012 IEEE.

关键词： Cellular automata

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Accelerating Computation of DCM for ERP with GPU-Based parallel Strategy

Accelerating Computation of DCM for ERP with GPU-Based Paral...

引用

international conference on Ubiquitous Intelligence & computing

作者： Wei-Jen Wang I-Fan Hsieh Chun-Chuan Chen Department of Computer Science and Information Engineering National Central University Graduate Institute of Biomedical Engineering National Central University

ISBN: (纸本)9781467330848

this paper presents the use of graphic processing unit (GPU) to accelerate a brain-activity analytical tool, the Dynamic Causal Modelling for Event Related Potential (DCM for ERP) in MATLAB. DCM for ERP is a recently developed advanced method for studying neuronal effective connectivity and making inference about the brain functions. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observed events (data) and the underlying probability model, such that the likelihood function is maximized. As the EM algorithm is computationally demanding, time consuming and largely data dependent, we propose a parallel computing scheme using GPUs to achieve a fast estimation of neural effective connectivity in DCM. the computational loading of EM was partitioned and dynamically distributed to either the threads or blocks according to the DCM model complex (i.e. the number of parameters to be estimated). the performance of this dynamic loading arrangement in terms of execution time and accuracy loss were evaluated using synthetic data. the results show that our method can accelerate a computation task by about 30 times as fast as the MATLAB version.

关键词： Dynamic causal modelling Expectation maximization CUDA parallel computing

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Towards Efficient Support for parallel I/O in Java HPC

Towards Efficient Support for Parallel I/O in Java HPC

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： Ammar Ahmad Awan Muhammad Sohaib Ayub Aamir Shafi Sungyoung Lee Department of Computer Engineering Kyung Hee University South Korea SEECS National University of Science and Technology Pakistan

ISBN: (纸本)9781467357043

Modern HPC applications put forward significant I/O requirements. To deal with them, MPI provides the MPI-IO API for parallel file access. ROMIO library implements MPI-IO and provides efficient support for parallel I/O in C and Fortran based applications. On the other hand, Java based MPI-like libraries such as MPJ Express and F-MPJ have emerged but they lack parallel I/O support. Little research has been done to provide Java based ROMIO-like libraries due to the non-availability of MPI-IO-like API for the Java language. In this paper, we take the first step towards the development of parallel I/O API in Java by evaluating the newly introduced Java NIO API versus the legacy Java I/O API. We propose two simple approaches for performing parallel file I/O using NIO and evaluate them on two different computational platforms. the implementation of proposed approaches exploits the view buffers concept of NIO API to perform efficient array based file I/O operations from multiple processes. We report encouraging speedups and suggest that design of a parallel I/O API in Java should be based on the NIO API.

关键词： Java Arrays File systems Libraries Bandwidth Writing Instruction sets

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parallel Implementation of LBP Based Face Recognition on GPU Using OpenCL

Parallel Implementation of LBP Based Face Recognition on GPU...

引用

IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： C.Y.N. Dwith G.N. Rathna Department of Electronics and Communication Engineering National Institute of Technology Warangal India Department of Electrical Engineering Indian Institute of Science Bangalore India

In this paper, we implement a novel parallelized approach of Local Binary Pattern (LBP) based face recognition algorithm on GPU. High performance rates have been achieved through maximizing the resource exploitation available in the GPU. the launch of GPU programming tools like Open source Computation Language (OpenCL) and (CUDA) have boosted the development of various applications on GPU. In this paper we implement a parallelized LBP algorithm on GPU using OpenCL programming tools. Programs developed under the OpenCL enable us to utilize GPU for general purpose computation with increased performance efficiency in terms of execution time. the experimental results based on the implementation on AMD 6500 GPU processor are observed to increase the computational performance of the system by to 30 folds in case of 1024×1024 images. the relative computational efficiency increases with increase in the size of the Image. this paper addresses several parallelization problems related to memory access and updating, divergent execution paths, understanding and realizing the OpenCL's concurrency and Execution models.

关键词： Graphics processing units Histograms Face recognition Face Vectors Computational modeling Algorithm design and analysis

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A distributed SVM ensemble for image classification and annotation

A distributed SVM ensemble for image classification and anno...

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international conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Nasullah Khalid Alham Maozhen Li Yang Liu Mahesh Ponraj Man Qi School of Engineering and Design Brunel University Uxbridge UK The Key Laboratory of Embedded Systems and Service Computing Ministry of Education University of Tongji China Department of Computing Canterbury Christ Church University Canterbury Kent UK

Combination of classifiers leads to a substantial reduction of classification errors in a wide range of applications. Among them SVM ensembles with bagging have shown better performance in classification than a single SVM. However, the training process of SVM ensembles is notably computationally intensive especially when the number of replicated training datasets is large. this paper presents MRESVM, a MapReduce based distributed SVM ensemble algorithm for image annotation which re-samples the training dataset based on bootstrapping and trains SVM on each dataset in parallel using a cluster of computers. MRESVM is evaluated in a experimental environment and the results show that the MRESVM algorithm reduces the training time significantly while achieves high level of accuracy in classifications.

关键词： Support vector machines Training Bagging Classification algorithms Accuracy Algorithm design and analysis Clustering algorithms

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A parallel Multiobjective Artificial Bee Colony Algorithm for Dealing with the Traffic Grooming Problem

A Parallel Multiobjective Artificial Bee Colony Algorithm fo...

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IEEE international conference on High Performance computing and Communications (HPCC)

作者： Álvaro Rubio-Largo Miguel A. Vega-Rodríguez Juan A. Gómez-Pulido Juan M. S'nchez-Pérez Department of Technologies of Computers and Communications University of Extremadura Caceres Spain Department of Technologies of Computers and Communications University of Extremadura Campus Universitario s/n Cáceres Spain

this work presents a novel parallel multiobjective approach based on the Artificial Bee Colony algorithm for grooming low-speed traffic requests onto high-capacity optical channels. the traffic grooming problem in mesh optical networks is an NP-hard problem, so the usage of metaheuristics and parallelism jointly for increasing the network performance is a great option in order to reduce execution times. the parallel multiobjective approach is implemented by using OpenMP. We have measured the speedup and efficiency obtained by our parallel approach with 2, 4, 8, and 16 cores. Efficient numerical results are reported in the experimental phase conducted on two optical networks. Finally, we present a comparative study with traditional methods; in which we show that the usage of swarm intelligence outperforms previous results published in the literature.

关键词： Topology Network topology Optical fiber networks Tin Equations Mathematical model Message systems

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