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International Symposium on parallel and distributed processing (IPDPS)

作者： Jonathan M. R. Byrd Stephen A. Jarvis Abhir H. Bhalerao Department of Computer Science University of Warwick Coventry UK

The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov chain Monte Carlo (MCMC) simulations are widely used for approximate counting problems, Bayesian inference and as a means for estimating very high-dimensional integrals. As such MCMC has found a wide variety of applications infields including computational biology and physics, financial econometrics, machine learning and image processing. This paper presents a new method for reducing the run-time of Markov chain Monte Carlo simulations by using SMP machines to speculatively perform iterations in parallel, reducing the runtime of MCMC programs whilst producing statistically identical results to conventional sequential implementations. We calculate the theoretical reduction in runtime that may be achieved using our technique under perfect conditions, and test and compare the method on a selection of multi-core and multi-processor architectures. Experiments are presented that show reductions in runtime of 35% using two cores and 55% using four cores.

关键词： Runtime Multithreading Computer architecture Availability Computer simulation Monte Carlo methods Biological system modeling Computational modeling Bayesian methods Application software

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parallel performance of domain decomposition method on distributed computing environment

Parallel performance of domain decomposition method on distr...

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International Conference on Computer and Information Technology (ICCIT)

作者： A.M.M. Mukaddes Atsushi Uragami Department of Industrial and Production Engineering Shahjalal University of Science and Technology Sylhet Bangladesh Department of Intelligent Machinery and Systems Kyushu University Japan

distributed parallel computing, which uses general-purpose workstations connected by a network as a large parallel computing resource, is one of the most promising trends in parallel computing. Over the last two decades, the growth in the use of such parallel computing environment has ensured the interest on the parallel finite element method. In this work, parallel finite element method using domain decomposition technique has been adapted to the distributed parallel environment of networked workstations and the supercomputer. Using the developed code, several model problems are solved and the parallel performances are analyzed on the network of eight Pentium iv PC cluster and GP7000F workstations. Finally, very large size of problem over 11 million DOFs has been solved using 1024 SR8000 supercomputer.

关键词： distributed computing parallel processing Workstations Finite element methods Supercomputers Performance analysis Matrix decomposition Concurrent computing Vectors Computer networks

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Real-time implementations of Hough Transform on SIMD architecture

Real-time implementations of Hough Transform on SIMD archite...

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ACM/IEEE International Conference on distributed Smart Cameras, ICDSC

作者： Yifan He Zoran Zivkovic Richard Kleihorst Alexander Danilin Henk Corporaal NXP Semiconductors Netherlands Technische Universiteit Eindhoven Netherlands

Implementation of the Hough transform (HT) for line detection requires massive computation, large memory space and high bandwidth. Without parallel processing on a proper platform, it can be hardly implemented in real-time, especially with high accuracy on high-resolution images. This paper proposes several efficient methods for implementation of HT on SIMD (single-instruction, multiple-data) architecture. All lines in an image/frame can be detected in real time with the proposed voting method, the novel Hough space (HS) structures, and the efficient image ldquorotationrdquo mechanism. With suggested refinement and tracking approach, we can capture and follow the target lines with very high accuracy. Analysis and comparison are elaborated with real-time implementation on our wireless smart camera (WiCa) platform, which is a powerful image/video processing platform developed by NXP Semiconductors. Moreover, two different applications, lane detection and gesture control, are also developed on this platform.

关键词： Program processors Real time systems Accuracy image edge detection Computer architecture Transforms Pixel

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GPU-Accelerated KLT Tracking with Monte-Carlo-Based Feature Reselection

GPU-Accelerated KLT Tracking with Monte-Carlo-Based Feature ...

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Julius Fabian Ohmer Nicholas J. Redding DSTO Intelligence Surveillance Reconnaissance Division Edinburgh SA Australia

Many computer vision methods rely on frame registration information obtained with algorithms such as the Kanade-Lucas-Tomasi (KLT) feature tracker, which is known for its excellent performance in that area. Various research groups proposed methods to extend its performance, both in terms of execution time and stability. Recent research has shown that current graphics processing units (GPUs) have proven to be very efficient SIMD parallel processing architectures that can be used to speed up the execution time of the KLT algorithm by an order of a magnitude compared with an ordinary CPU implementation and thus making it suitable for real-time applications on commodity hardware. Previous publications demonstrated the use of the GPU for the tracking and image processing part of the KLT algorithm. One essential, but computationally demanding step of the KLT algorithm is the feature selection step. It injects fresh feature points into the existing point set and thus enables the KLT to continuously track points throughout an image sequence. Those sequences can contain rapid movements or they may be of low quality. In such situations, features diminish rapidly and the step must be performed potentially for every frame. Thus, the performance of the otherwise efficient GPU implementation declines substantially, as this step includes a sorting operation on the sparse feature map, which is difficult to implement efficiently on the GPU. We use the KLT algorithm to calculate a stable frame registration with high accuracy using the feature point set. We found that maintaining a well distributed feature set through frequent injections of points is an essential requirement. In this paper we will demonstrate an alternative feature reselection method that can be efficiently implemented on the GPU. It is a Monte-Carlo-based approximation of the original method and leads to very good tracking results with just a fraction of the computational cost.

关键词： Karhunen-Loeve transforms Computer vision Stability Graphics parallel processing Central processing Unit Hardware image processing image sequences Sorting

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distributed computing model for processing remotely sensed images based on grid computing

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INFORMATION SCIENCES 2007年第2期177卷 504-518页

作者： Shen, Zhanfeng Luo, Jiancheng Huang, Guangyu Ming, Dongping Ma, Weifeng Sheng, Hao Chinese Acad Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China China Univ Geosci Sch Earth Sci & Resources Beijing 100083 Peoples R China Zhejiang Univ Sci & Technol Sch Informat & Elect Engn Hangzhou 310023 Peoples R China

With advances in remote-sensing technology, the large volumes of data cannot be analyzed efficiently and rapidly, especially with arrival of high-resolution images. The development of image-processing technology is an urgent and complex problem for computer and geo-science experts. It involves, not only knowledge of remote sensing, but also of computing and networking. Remotely sensed images need to be processed rapidly and effectively in a distributed and parallel processing environment. Grid computing is a new form of distributed computing, providing an advanced computing and sharing model to solve large and computationally intensive problems. According to the basic principle of grid computing, we construct a distributed processing system for processing remotely sensed images. This paper focuses on the implementation of such a distributed computing and processing model based on the theory of grid computing. Firstly, problems in the field of remotely sensed image processing are analyzed. Then, the distributed (and parallel) computing model design, based on grid computing, is applied. Finally, implementation methods with middleware technology are discussed in detail. From a test analysis of our system, ***, the whole image-processing system is evaluated, and the results show the feasibility of the model design and the efficiency of the remotely sensed image distributed and parallel processing system. (C) 2006 Elsevier Inc. All rights reserved.

关键词： grid computing middleware Web services remotely sensed image processing distributed and parallel processing computing model

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Survey of parallel MATLAB techniques and applications to signal and image processing

Survey of parallel MATLAB techniques and applications to sig...

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32nd IEEE International Conference on Acoustics, Speech and Signal processing

作者： Krishnamurthy, Ashok Nehrbass, John Chaves, Juan Carlos Samsi, Siddharth Ohio Supercomp Ctr Columbus OH 43212 USA

ISBN: (纸本)1424407281

We present a survey of modem parallel MATLAB techniques. We concentrate on the most promising and well supported techniques with an emphasis in SIP applications. Some of these methods require writing explicit code to perform inter-processor communication while others hide the complexities of communication and computation by using higher level programming interfaces. We cover each approach with special emphasis given to performance and productivity issues.

关键词： distributed algorithms distributed computing array signal processing image processing

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NPU-based image compositing in a distributed visualization system

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2007年第4期13卷 798-809页

作者： Pugmire, David Monroe, Laura Davenport, Carolyn Connor DuBois, Andrew DuBois, David Poole, Stephen Los Alamos Natl Lab Los Alamos NM 87545 USA Oak Ridge Natl Lab Oak Ridge TN 37831 USA

This paper describes the first use of a Network processing Unit (NPU) to perform hardware-based image composition in a distributed rendering system. The image composition step is a notorious bottleneck in a clustered rendering system. Furthermore, image compositing algorithms do not necessarily scale as data size and number of nodes increase. Previous researchers have addressed the composition problem via software and/or custom-built hardware. We used the heterogeneous multicore computation architecture of the Intel IXP28XX NPU, a fully programmable commercial off-the-shelf (COTS) technology, to perform the image composition step. With this design, we have attained a nearly four-times performance increase over traditional software-based compositing methods, achieving sustained compositing rates of 22-28 fps on a 1, 024 x 1, 024 image. This system is fully scalable with a negligible penalty in frame rate, is entirely COTS, and is flexible with regard to operating system, rendering software, graphics cards, and node architecture. The NPU-based compositor has the additional advantage of being a modular compositing component that is eminently suitable for integration into existing distributed software visualization packages.

关键词： hardware-assisted image compositing high-performance computing image compositing Network processing Unit parallel rendering PC clusters visualization volume rendering

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Simulation-based performance analysis of a medical image-processing architecture

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11th International Workshop on Formal methods for Industrial Critical Systems (FMICS 2006)/5th International Workshop on parallel and distributed methods in Verification (PDMC

作者： Cuijpers, P. J. L. Fyukov, A. V. Tech Univ Eindhoven NL-5600 MB Eindhoven Netherlands Philips Res NL-5656 AA Eindhoven Netherlands

ISBN: (纸本)9783540709510

In this paper, we show a simulation method for performance prediction of medical image processing chains, based on ***-time calculus of [9]. In particular, we focus on estimating the latency and throughput of a given image processing chain and its distribution over hardware resources. The architectural level of abstraction of the real-time calculus approach makes our method flexible, so that different design decisions can be studied using similar models. The choice for simulation rather than the usual algebraic analysis of real-time calculus equations, gives us the possibility to include a number of performance relevant implementation details in our models for which analytical estimates are not available.

关键词： image processing

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Efficient data distribution scheme for multi-dimensional sparse arrays

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JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 2007年第1期23卷 315-327页

作者： Lin, Chun-Yuan Chung, Yeh-Ching Natl Tsing Hua Univ Inst Mol & Cellular Biol Hsinchu 300 Taiwan Natl Tsing Hua Univ Dept Comp Sci Hsinchu 300 Taiwan

Array operations are useful in a large number of important scientific codes, such as molecular dynamics, finite-element methods, climate modeling, etc. It is a challenging problem to provide an efficient data distribution for irregular problems. Multi-dimensional (AM) sparse array operations can be used in atmosphere and ocean sciences, image processing, etc., and have been an extensively investigated problem. In our previous work, a data distribution scheme, Encoding-Decoding (ED), was proposed for two-dimensional (2D) sparse arrays. In this paper, ED is extended to be useful for MD sparse arrays first. Then, the performance of ED is compared with that of Send Followed Compress (SFC) and Compress Followed Send (CFS). Both theoretical analysis and experimental tests were conducted and then shown that ED is superior to SFC and CFS for all of evaluated criteria.

关键词： data compression method data distribution scheme data layout distributed memory multicomputers sparse ratio sparse array

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A tristate approach based on weighted mean and backward iteration

A tristate approach based on weighted mean and backward iter...

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SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing

作者： Yanhua, Ma Chuanjun, Liu Haiying, Sun College of Information Science and Technology Qingdao University of Science and Technology Qingdao Shandong Province China Hisense Mobil Communications Technology Corporation Qingdao Shandong Province China

ISBN: (纸本)0769529097

A tristate approach (TA) for image denoising processing is presented;the noise is aimed at the presence of pepper-and-salt noise. The newness of this method is that it develops a new route in the field of image restoration. The tristate approach algorithm focuses on the removal and restoration of the noisy speckles and avoids blurring and averaging edges and non-noise pixels in a way different from other known algorithms. Any noisy pixel is replaced by an estimated value. This value is the weighted mean of the pixels neighboring to the noisy pixel or the four iteration pixels got before it. This paper describes, analyzes and compares several methods and results of removing noise from an image. We have performed the experiments by adding Salt-and-Pepper in an original image. © 2007 IEEE.

关键词： image processing

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