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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing"

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Toolbox for advanced X-ray image processing

Toolbox for advanced X-ray image processing

引用

conference on Advances in Computational methods for X-Ray Optics II

作者： Gureyev, Timur E. Nesterets, Yakov Ternovski, Dimitri Thompson, Darren Wilkins, Stephen W. Stevenson, Andrew W. Sakellariou, Arthur Taylor, John A. CSIRO Mat Sci & Engn PB 33 Clayton Vic 3169 Australia Trident Software Pty Ltd Melbourne Vic 8006 Australia

ISBN: (纸本)9780819487513

A software system has been developed for high-performance Computed Tomography (CT) reconstruction, simulation and other X-ray image processing tasks utilizing remote computer clusters optionally equipped with multiple Graphics processing Units (GPUs). The system has a streamlined Graphical User Interface for interaction with the cluster. Apart from extensive functionality related to X-ray CT in plane-wave and cone-beam forms, the software includes multiple functions for X-ray phase retrieval and simulation of phase-contrast imaging (propagation-based, analyzer crystal based and Talbot interferometry). Other features include several methods for image deconvolution, simulation of various phase-contrast microscopy modes (Zernike, Schlieren, Nomarski, dark-field, interferometry, etc.) and a large number of conventional image processing operations (such as FFT, algebraic and geometrical transformations, pixel value manipulations, simulated image noise, various filters, etc.). The architectural design of the system is described, as well as the two-level parallelization of the most computationally-intensive modules utilizing both the multiple CPU cores and multiple GPUs available in a local PC or a remote computer cluster. Finally, some results about the current system performance are presented. This system can potentially serve as a basis for a flexible toolbox for X-ray image analysis and simulation, that can efficiently utilize modern multi-processor hardware for advanced scientific computations.

关键词： X-ray imaging Computed Tomography parallel programs Graphical processing Units computer clusters

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Automatic FFT Performance Tuning on OpenCL GPUs

Automatic FFT Performance Tuning on OpenCL GPUs

引用

International conference on parallel and distributed Systems (ICPADS)

作者： Yan Li Yunquan Zhang Haipeng Jia Guoping Long Ke Wang Laboratory of Parallel Software and Computational Science Institute of Software State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China School of Information Science and Engineering Ocean University of China Qingdao China Laboratory of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences Beijing China

Many fields of science and engineering, such as astronomy, medical imaging, seismology and spectroscopy, have been revolutionized by Fourier methods. The fast Fourier transform (FFT) is an efficient algorithm to compute the discrete Fourier transform (DFT) and its inverse. The emerging class of high performance computing architectures, such as GPU, seeks to achieve much higher performance and efficiency by exposing a hierarchy of distinct memories to programmers. However, the complexity of GPU programming poses a significant challenge for programmers. In this paper, based on the Kronecker product form multi-dimensional FFTs, we propose an automatic performance tuning framework for various OpenCL GPUs. Several key techniques of GPU programming on AMD and NVIDIA GPUs are also identified. Our OpenCL FFT library achieves up to 1.5 to 4 times, 1.5 to 40 times and 1.4 times the performance of clAmdFft 1.0 for 1D, 2D and 3D FFT respectively on an AMD GPU, and the overall performance is within 90% of CUFFT 4.0 on two NVIDIA GPUs.

关键词： Graphics processing unit Instruction sets Vectors Memory management Kernel Programming

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An ethological motion capture system

An ethological motion capture system

引用

International Symposium on Computational Intelligence and Informatics

作者： Viktor Devecseri Antal Dóka József Molnár Péter Tamás Department of Mechatronics Optics and Information Engineering Budapest University of Technology and Economics Budapest Hungary Faculty of Sciences Biological Departments / Department of Ethology Eötvös Loránd University Budapest Hungary

The motion of living beings can be recorded with motion capture systems. The recorded data can be used to animate virtual characters. There are many methods used by motion capture systems. The paper presents the development of a motion capture system for more than one performer with active optical markers. The performers wear homogenous, illuminating markers attached to each relevant joint. Movements are captured by 6 high speed cameras in order to determine the markers' position in the cameras' image. The cameras operate at 60 fps. The image processing is distributed among multiple computers. Luckily most of the image processing tasks are highly parallel, so the high parallel computational capacity of modern programmable GPUs can be exploited. The main computer calculates the markers' 3D positions after it receives the 2D data from image processing. Each marker needs to be identified, so the markers' 2D and 3D positions are tracked. A hierarchy can be defined between the points in the point cloud, which can be used to determine the bones' hierarchical transformation chain in the characters' skeleton. To achieve satisfying results precise calibration is required.

关键词： Cameras Three dimensional displays Computers Calibration Tracking image processing Laboratories

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A study of power system parallel simulation methods based on multi-core multithreaded processor platforms

A study of power system parallel simulation methods based on...

引用

International conference on Electric Information and Control Engineering

作者： Zhang, Jia-An Wang, Cheng-Shan Wu, Ai-Guo School of Electrical Engineering and Automation Tianjin University Tianjin 300072 China

ISBN: (纸本)9781424480395

High-performance processor architectures are moving toward the integration of more processing cores on a single chip. PCs and parallel computer systems will have higher computing performance. It is very meaningful for power system simulation, online stability assessment and control. But traditional serial and parallel software can not fully exploit multi-core's capability without parallelizing restructure. In this paper, parallel simulation algorithms are analyzed and software restructure strategies are studied for multi-core processor platforms. The research indicates that: (1) For PCs, implicit parallel strategy with OpenMP is easier to implement and explicit parallel strategy with MPI or Pthreads is more adaptable to large-scale system simulation. (2) For clusters and distributed systems, MPI+OpenMP hybrid programming is convenient and multilevel partitioning is potential. Both methods provide better speedup. © 2011 IEEE.

关键词： Large scale systems

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Applications and Evaluation of In-memory MapReduce

Applications and Evaluation of In-memory MapReduce

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IEEE International conference on Cloud Computing Technology and Science (CloudCom)

作者： Kim-Thomas Rehmann Michael Schoettner Institut für Informatik Hcinrich-Hcinc-Universität Düsseldorf Düsseldorf Germany Heinrich-Heine-Universitat Dusseldorf Dusseldorf Nordrhein-Westfalen DE

In-memory storage techniques provide cloud applications with cheap, fast and large-scale RAM-based storage. By replicating data and providing adequate consistency control mechanisms, in-memory storage can simplify the design and implementation of highly scalable distributed applications. We argue that in-memory storage can increase the flexibility of the MapReduce parallel programming model without requiring additional communication facilities to propagate data updates. In this paper, we present several applications for our in-memory MapReduce framework from diverse problem domains including iterative and on-line data processing.

关键词： Histograms Data models Computational modeling Load modeling distributed databases Random access memory image color analysis

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A novel receive beamforming approach of ultrasound signals based on distributed compressed sensing

A novel receive beamforming approach of ultrasound signals b...

引用

IEEE Instrumentation and Measurement Technology conference

作者： Minfen Shen Qiong Zhang Jinyao Yang Department of Electronic Science and Technology University of Science and Technology Hefei China Department of Electronic Engineering Shantou University Shantou Guangdong China Shantou Institute of Ultrasonic Instruments Company Limited Shantou Guangdong China

High efficient acquisition of the sensor array signals and accurate reconstruction of the backscatters medium are important issues in ultrasound reveive beamforming. This paper presents a novel receive beamforming approach based on distributed compressed sensing (DCS) which seeks to simultaneously measure signals that are each individually sparse in some domain(s) and also mutually correlated with much few measurements under the Nyquist rate. Instead of sampling conventional backscattering signals at the Nyquist rate, few linear projections of the returned signal with random vectors are taken as measurements. Then high resolution ultrasound image is reconstructed from the few measurements directly by a new adaptive beamforming (ABF) algorithm without the complex raw signals recovering of DCS methods. The simulated results show that the proposed algorithm can dramatically reduce the sampling frequency, achieve high resolution ultrasound image reconstruction and greatly alleviate the computational load of the processing in practice.

关键词： Ultrasonic imaging Arrays Ultrasonic variables measurement Imaging image reconstruction Array signal processing Backscatter

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Efficient Star Join for Column-oriented Data Store in the MapReduce Environment

Efficient Star Join for Column-oriented Data Store in the Ma...

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Web Information Systems and Applications conference (WISA)

作者： Haitong Zhu Minqi Zhou Fan Xia Aoying Zhou Institute of Massive Computing East China Normal University Shanghai China

Map Reduce is a parallel computing paradigm that has gained a lot of attention from both industry and academia recent years. Unlike parallel DBMSs, with Map Reduce, it is easier for non-expert to develop scalable parallel programs for analytical applications over huge data sets across clusters of commodity machines. As the nature of scan-oriented processing, the performance of Map Reduce for relation operators can be enhanced dramatically since it is inevitably accessing lots of unnecessary data tuples, especially for table join operators. In this paper, we propose an efficient star join strategy called HdBmp join for column-oriented data store by using a three-level content aware index (i.e., HdBmp Index). Armed with this index, most of the unnecessary tuples in the join processing can be filtered out, and consequently result in immense reduction in both communication cost and execution time. Our extensive experimental studies confirm the efficiency, scalability and effectiveness of our new proposed join methods.

关键词： Indexes distributed databases Memory Data models Benchmark testing Algorithm design and analysis Scalability

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Transparent adaptation of e-science applications for parallel and cycle-sharing infrastructures 11

Transparent adaptation of e-science applications for paralle...

引用

Proceedings of the 11th IFIP WG 6.1 international conference on distributed applications and interoperable systems

作者： João Morais João Nuno Silva Paulo Ferreira Luís Veiga INESC-ID Technical University of Lisbon Portugal

ISBN: (纸本)9783642213861

Grid computing is a concept usually associated with institution-driven networks assembled with a clear purpose, namely to address complex calculation problems or when heterogeneity and users' geographical dispersion is a key factor. However, regular home users willing to take advantage of distributed processing cannot regard this a viable option. Even if Grid access was open to the general public, a home user would not be able to express task decomposition without clearly understanding the program *** this work, distributed computation, and cycle-sharing in particular, are addressed in a different manner. Users share idle resources with other users provided that such resources (namely, CPU cycles) are mostly employed to execute already installed applications (e.g., popular commodity applications targeting video compression/ transcoding, image processing, ray tracing). Users need not to modify an application they already use and trust. Instead, they require only access to an available format description of the application input/output, in order to allow transparent and automatic decomposition of a job in smaller tasks that may be distributed and executed in cycle-sharing machines.

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Ultrafast image reconstruction of a dual-head PET system by use of CUDA architecture

Ultrafast image reconstruction of a dual-head PET system by ...

引用

conference on Medical Imaging 2011 - Physics of Medical Imaging

作者： Hung, Yukai Dong, Yun Chern, Felix R. Wang, Weichung Kao, Chien-Min Chen, Chin-Tu Chou, Cheng-Ying Natl Taiwan Univ Dept Bioind Mechatron Engn Taipei 10764 Taiwan

ISBN: (纸本)9780819485038

Positron emission tomography (PET) is an important imaging modality in both clinical usage and research studies. For small-animal PET imaging, it is of major interest to improve the sensitivity and resolution. We have developed a compact high-sensitivity PET system that consisted of two large-area panel PET detector heads. The highly accurate system response matrix can be computed by use of Monte Carlo simulations, and stored for iterative reconstruction methods. The detector head employs 2.1x2.1x20 mm(3) LSO/LYSO crystals of pitch size equal to 2.4 mm, and thus will produce more than 224 millions lines of response (LORs). By exploiting the symmetry property in the dual-head system, the computational demands can be dramatically reduced. Nevertheless, the tremendously large system size and repetitive reading of system response matrix from the hard drive will result in extremely long reconstruction times. The implementation of an ordered subset expectation maximization (OSEM) algorithm on a CPU system (four Athlon x64 2.0 GHz PCs) took about 2 days for 1 iteration. Consequently, it is imperative to significantly accelerate the reconstruction process to make it more useful for practical applications. Specifically, the graphic processing unit (GPU), which possesses highly parallel computational architecture of computing units can be exploited to achieve a substantial speedup. In this work, we employed the state-of-art GPU, NVIDIA Tesla C2050 based on the Fermi-generation of the compute united device architecture (CUDA) architecture, to yield a reconstruction process within a few minutes. We demonstrated that reconstruction times can be drastically reduced by using the GPU. The OSEM reconstruction algorithms were implemented employing both GPU-based and CPU-based codes, and their computational performance was quantitatively analyzed and compared.

关键词： dual-head PET image reconstruction CUDA

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High-performance polynomial GCD computations on graphics processors

High-performance polynomial GCD computations on graphics pro...

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International conference on High Performance Computing & Simulation (HPCS)

作者： Pavel Emeliyanenko Max Planck Institut für Informatik Saarbruecken Germany

We propose an algorithm to compute a greatest common divisor (GCD) of univariate polynomials with large integer coefficients on Graphics processing Units (GPUs). At the highest level, our algorithm relies on modular techniques to decompose the problem into subproblems that can be solved separately. Next, we employ resultant-based or matrix algebra methods to compute a GCD of each modular image in parallel. Our approach exhibits block structure to distribute the computation of a single modular GCD over several thread blocks, and thus to remove any hardware limitations on the maximal size of polynomials that can be handled. To "combine" all modular results, we have adopted Mixed-Radix Conversion (MRC) algorithm running on the GPU. Our approach shows a significant speed-up over host-based GCD algorithm from Maple 13.

关键词： Polynomials Graphics processing unit Instruction sets Generators Kernel Computer architecture parallel processing

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