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Element-wise Implementation of Iterative Solvers for FEM Problems on the Cell Processor

Element-wise Implementation of Iterative Solvers for FEM Pro...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Noriyuki Kushida Center of Computational Science and E-systems Japan Atomic Energy Agency Ibaraki Japan

A new implementation of the finite element method(FEM) that is suitable for the Cell processor. Since the Cell processors have a far greater performance and lower byte per-flop (B/F) rate than traditional scalar processors, the amount of memory transfer was reduced and a technique was used to hide the number of memory accesses. The amount of memory transfer was reduced by accepting additional floating-point operations without storing the data if the data were required repeatedly. In the present study, such memory access reduction was applied to the conjugate gradient (CG)method. In order to achieve memory access reduction in the CG method, element-wise computation was used in order to avoid global coefficient matrices, which cause frequent memory accesses. Moreover, all data transfer times are incorporated into the calculation time. As a result, the new implementation performed 10 times better than a traditional implementation run on a PPU.

关键词： Finite element methods Bandwidth Memory management Microprocessors Equations Multicore processing

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International conference on Computational Science, ICCS 2003

International Conference on Computational Science, ICCS 2003

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International conference on Computational Science, ICCS 2003

ISBN: (纸本)3540401970

The proceedings contain 118 papers. The special focus in this conference is on Terascale Performance Analysis and Computational Chemistry in the 21st Century. The topics include: A model for predicting the optimum checkpoint interval for restart dumps;scaling molecular dynamics to 3000 processors with projections;real-time terascale implementation of tele-immersion;performance analysis of PHASTA on NCSA intel IA-64 linux cluster;performance instrumentation and measurement for terascale systems;logging kernel events on clusters;recent advances in QM and QM/MM methods;local correlation models;multiresolution quantum chemistry in multiwavelet bases;management of web and associated grid technologies for quantum chemistry computation;the extensible computational chemistry environment;computational quantum chemistry experiments via the web;a fortran based object-oriented system for quantum chemistry and crystallography;explicitly correlated second order perturbation theory with frozen gaussian-type geminals;molecular potential energy surfaces by interpolation;interfacing computer aided parallelization and performance analysis;dynamic performance tuning of distributed programming libraries;parallel program debugging with mad;enhancing prediction accuracy in PCM-based file prefetch by constrained pattern replacement algorithm;an adaptive load balancing algorithm for large data parallel processing with communication delay;a flexible multiagent parallel file system for clusters;computational aspects of chemical data assimilation into atmospheric models;virtual telemetry for dynamic data-driven application simulations;tornado detection with support vector machines;computational science simulations based on web services;a data driven environment for multiphysics applications and discrete event solution of gas dynamics within the DEVS framework.

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On overlapping partitions

On overlapping partitions

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International conference on parallel processing (ICPP)

作者： J. Galtier S. Lanteri France Telecom Research and Development and INRIA France INRIA France

parallelization strategies based on domain partitioning techniques have been widely adopted for parallel finite element computations because of their suitability to distributed memory platforms. In most cases, this parallelization is based on non-overlapping partitions especially for Computational Structural Mechanics applications. However, finite volume (or mixed finite element/finite volume) discretization methods, which are frequently implemented in Computational Fluid Dynamics applications, generally require the use of overlapping mesh partitions to keep the parallelization work simple. Unfortunately, many tools on which the partitioning step relies give poor results when asked for overlapping partitions. In this paper, we describe an efficient method to transform a non-overlapping partition of a domain into an overlapping one. We also propose an optimization strategy for overlapping partitions that mainly aims at reducing the computational load unbalance as well as the size of the interfaces. The new algorithms demonstrate significant improvements as they are applied to generate overlapping partitions in the context of a parallel mixed finite element/finite volume three-dimensional flow solver.

关键词： Finite element methods Partitioning algorithms Computational fluid dynamics Computer interfaces Iterative algorithms Research and development Concurrent computing distributed computing Telecommunication computing Fluid dynamics

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parallel mesh regularization and resampling algorithm for improved mesh registration

Parallel mesh regularization and resampling algorithm for im...

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National conference on Computer Vision, Pattern Recognition, image processing and Graphics (NCVPRIPG)

作者： Sumandeep Banerjee Somnath Dutta Prabir Kumar Biswas Partha Bhowmick Department of Electronics and Electrical Communication Engineering Department of Computer Science and Engineering Indian Institute of Technology Kharagpur

In this paper, we present a fast and efficient algorithm for regularization and resampling of triangular meshes generated by 3D reconstruction methods such as stereoscopy, laser scanning etc. We also present a scheme for efficient parallel implementation of the proposed algorithm and the time gain with increasing number of processor cores.

关键词： Three-dimensional displays Face Instruction sets Interpolation Equations parallel algorithms Cameras

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Modelling and simulation of complex fluid and mechanical aircraft systems

Modelling and simulation of complex fluid and mechanical air...

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1998 World Aviation conference

作者： Krus, Petter Linköping University Sweden

Modelling and simulation is of crucial importance for the understanding of system dynamics. In aircraft, simulation has been strong in the area of flight control. Modelling and simulation of the hydraulic systems has also a long tradition. The rapid increase in computational power has now come to a point where complete modelling and simulation of all the sub systems in an aircraft is not far away. This means new challenges in dealing with very complex multi domain systems. Of all the systems in an aircraft fluid power systems is one of the most difficult to handle from a numerical point of view. They are characterised by difficulties such as discontinuities, very strong non-linearities, stiff differential equations and a high degree of complexity. A considerable effort has therefore been made to develop methods suitable for simulation of such systems. This means that it is possible to simulate fluid power systems much more efficiently than before, and that a lot of systems can even be simulated in real time. The distributed modelling technique used, also makes it possible to partition the system for parallel processing. This means that it is possible to simulate much larger systems within reasonable time. It also is a valid paradigm for multi domain system. The rapid development in simulation methods and the general increase in hardware performance imply that simulations can be run thousands of times faster than just a few years ago. As a consequence, there is no longer such need to use very economic, more or less analytical methods. This means that design methods based on different kinds of numerical optimisation for system design, are becoming much more important. Copyright © 1998 by SAE International and the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Numerical methods

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Fine-grained parallel implementation of edge-directed image Interpolation on GPU

Fine-grained parallel implementation of edge-directed Image ...

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International conference on parallel and distributed Systems (ICPADS)

作者： Wenze Li Jiaji Wu Jiao Shi Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University Xi'an P.R. China

ISBN: (纸本)9781479976164

Edge-directed interpolation is widely used to enhance visual performance of remote sensing image. Compared with traditional bi-cubic interpolation and bilinear interpolation, a great number of matrix operations will appear as it is getting better visual performance. CUDA (Compute Unified Device Architecture) offers tremendous performance in many high-performance computing areas. Edge-directed interpolation can be mapped to this architecture (CUDA) readily. However, parallel schemes based on CUDA are generally decomposed into coarse-grained tasks, which is suitable for thread blocks. In this paper, a parallel approach of fine-grained edge-directed interpolation is proposed. Based on CUDA, the process of parallel interpolation for one missing pixel is assigned to 4*4 threads for the reason that majority of matrix operations are related to 4*4 matrix. This task division strategy minimizes resource pressure of thread-blocks. Our calculating scheme is expressed in terms of increasing parallelism that is efficiently implemented on the GPU. By employing one NVIDIA GTX480 GPU and one NVIDIA GTX590 GPU in the case with asynchronous I/O transfer, our GPU optimization efforts on fine-grained edge-directed interpolation scheme finally achieve a speedup of 69.8x with respect to its CPU counterpart C code running on one CPU core of Intel core(TM) i7-920.

关键词： Interpolation Graphics processing units Instruction sets image edge detection Matrix decomposition Algorithm design and analysis Visualization

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Conch: A Cyclic MapReduce Model for Iterative Applications

Conch: A Cyclic MapReduce Model for Iterative Applications

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Euromicro conference on parallel, distributed and Network-Based processing

作者： Ran Zheng Genmao Yu Hai Jin Xuanhua Shi Qin Zhang Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

MapReduce programming model is a popular model to simplify but speed up data parallel applications. However, it is not efficient for iterative applications because of its repeated data transmission with HDFS (Hadoop distributed File System). Conch, a cyclic MapReduce model, is designed for efficient processing of iterative applications. In order to minimize network overhead, shared data is cached locally and a "map-shuffle" phase is presented with a combined transmission mechanism. Meanwhile, a prediction scheduler for iterative applications is brought out to achieve better data locality in terms of runtime information. The experiments show that Conch can support iterative applications transparently and efficiently. Compared with Hadoop and HaLoop in single-job environment, Conch can achieve 13%-17% improvements on K-Means and fuzzy C-Means. Especially in multi-job environment, 63.6% and 28.6% improvements can be obtained compared with Hadoop and HaLoop.

关键词： Delays Iterative methods Computational modeling Prediction algorithms Heart beat Data transfer Data models

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Comparison of Approaches of distributed Satellite image Edge Detection on Hadoop

Comparison of Approaches of Distributed Satellite Image Edge...

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International conference on Inventive Communication and Computational Technologies (ICICCT)

作者： Tapan Sharma Vinod Shokeen Sunil Mathur ASET Amity University Noida Uttar Pradesh India MAIT GGS Indraprastha University Delhi India

In the world of bigdata, Hadoop has become the major platform for storage and processing. Due to advancement in technology in the area of remote sensing, tremendous growth in data has been witnessed. In this paper, we have conducted experiments and compared two methods in which edge detection of satellite images is performed on Hadoop. Since, edge detection is one of the prime steps in the field of image processing and is being used for object detection in the image, we have targeted this basic algorithm of image processing for our experiments. In earlier research for edge detection on Hadoop, SequenceFiles were used to store and process images. In our experiments, we have leveraged distributed processing of Hadoop by logically splitting the file on HDFS and performing edge detection in distributed manner. The experiments were performed on Amazon AWS Elastic MapReduce (EMR) cluster using different satellite images varying from 10MB-200MB. The paper describes the comparison of the two approaches.

关键词： image edge detection Satellites Task analysis distributed processing conferences Clustering algorithms

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Derivation languages of splicing P systems 12th

Derivation languages of splicing P systems

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12th International conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

作者： Mahalingam, Kalpana Paul, Prithwineel Song, Bosheng Pan, Linqiang Subramanian, K.G. Department of Mathematics Indian Institute of Technology Madras Chennai600036 India Key Laboratory of Image Information Processing Intelligent Control of Education Ministry of China School of Automation Huazhong University of Science and Technology WuhanHubei430074 China School of Electric and Information Engineering Zhengzhou University of Light Industry ZhengzhouHenan450002 China Faculty of Science Liverpool Hope University LiverpoolL16 9JD United Kingdom

ISBN: (纸本)9789811071782

Labelled splicing P systems are distributed parallel computing models, where sets of strings that evolve by splicing rules are labelled. In this work, we consider labelled splicing systems with the following modifications: (i) The strings in the membranes are present in arbitrary number of copies;(ii) the rules in the regions are finite in number. Results on the language family generated by the labelled splicing system in comparison with the language families of the Chomsky hierarchy, including recursively enumerable languages, are obtained, by involving only either one or two membranes in the P systems considered. © Springer Nature Singapore Pte Ltd 2017.

关键词： distributed computer systems

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image Recognition with MapReduce Based Convolutional Neural Networks

Image Recognition with MapReduce Based Convolutional Neural ...

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IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication conference (UEMCON)

作者： Jackie Leung Min Chen State University of New York New Paltz NY USA

ISBN: (纸本)9781728138862

Convolutional neural networks (CNNs) have gained global recognition in advancing the field of artificial intelligence and have had great successes in a wide array of applications including computer vision, speech and natural language processing. However, due to the rise of big data and increased complexity of tasks, the efficiency of training CNNs have been severely impacted. To achieve state-of-art results, CNNs require tens to hundreds of millions of parameters that need to be fine-tuned, resulting in extensive training time and high computational cost. To overcome these obstacles, this work takes advantage of distributed frameworks and cloud computing to develop a parallel CNN algorithm. Close examination of the implementation of MapReduce based CNNs as well as how the proposed algorithm accelerates learning are discussed and demonstrated through experiments. Results reveal high accuracy in classification and improvements in speedup, scaleup and sizeup compared to the standard algorithm.

关键词： cloud computing computer vision convolutional neural nets data handling image recognition learning (artificial intelligence) natural language processing parallel processing image recognition Cloud Computing data processing images computer vision Natural Language processing parallel processing (COMPUTERS) Neural network big data

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