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Recognition of circular patterns on GPUs: Performance analysis and contributions

JOURNAL OF parallel AND distributed COMPUTING 2008年第10期68卷 1329-1338页

作者： Ruiz, Antonio Guil, Nicolas Ujaldon, Manuel Univ Malaga ETSI Informat Comp Architecture Dept E-29071 Malaga Spain

We develop a novel approach for computing the circle Hough transform entirely on graphics hardware (GPU). A primary role is assigned to vertex processors and the rasterizer, overshadowing the traditional foreground of pixel processors and enhancing parallel processing. Resources like the vertex cache or blending units are studied too, with our set of optimizations leading to extraordinary peak gain factors exceeding 358x over a typical CPU execution. Software optimizations, like the use of precomputed tables or gradient information and hardware improvements, like hyperthreading and multicores are explored on CPUs as well. Overall, the GPU exhibits better scalability and much greater parallel performance to become a solid alternative for computing the classical circle Hough transform versus those optimal methods run on emerging multicore architectures. (c) 2008 Elsevier Inc. All rights reserved.

关键词： image processing Hough transform Graphics processors parallel programming on shaders GPU rasterizer Multicore architectures High performance computing

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Efficient parallel implementation of iterative reconstruction algorithms for electron tomography

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JOURNAL OF parallel AND distributed COMPUTING 2008年第5期68卷 626-640页

作者： Fernandez, Jose-Jesus Gordon, Dan Gordon, Rachel Univ Almeria Dept Comp Architecture & Elect Almeria 04120 Spain Univ Haifa Dept Comp Sci IL-31999 Haifa Israel Technion Israel Inst Technol Dept Aerosp Engn Haifa Israel

Electron tomography (ET) combines electron microscopy and the principles of tomographic imaging in order to reconstruct the three-dimensional structure of complex biological specimens at molecular resolution. Weighted back-projection (WBP) has long been the method of choice since the reconstructions are very fast. it is well known that iterative methods produce better images, but at a very costly time penalty. In this work. it is shown that efficient parallel implementations of iterative methods. based primarily on data decomposition, can speed up such methods to an extent that they become viable alternatives to WBP. Precomputation of the coefficient matrix has also turned out to be important to substantially improve the performance regardless of the number of processors used. Matrix precomputation has made it possible to speed up the block-iterative component averaging (BICAV) algorithm, which has been studied before in the context of computerized tomography (CT) and ET. by a factor of more than 3.7. Component-averaged row projections (CARP) is a recently introduced block-parallel algorithm, which was shown to be a robust method for solving sparse systems arising from partial differential equations. It is shown that this algorithm is also suitable for single-axis ET. and is advantageous over BICAV both in terms of runtime and image quality. The experiments were carried out on several datasets of ET of various sizes, using the blob model for representing the reconstructed object. (C) 2007 Elsevier Inc. All rights reserved.

关键词： BICAV CARP CAV component-averaging electron microscopy electron tomography image reconstruction parallel processing WBP weighted back-projection

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Performance requirements of the Mojette transform for internet distributed databases and image processing

Performance requirements of the Mojette transform for intern...

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11th International Conference on Optimization of Electrical and Electronic Equipment

作者： Serfozo, P. Vasarhelyi, J. Szoboszlai, P. Turan, J. Univ Miskolc Dept Automat Miskolc Hungary Ericsson Hungary Budapest Hungary Tech Univ Kosice Dept Elect & Multimedia Commun \ Kosice Slovakia

ISBN: (纸本)1424415446

In the last ten years there were intensive researches to find new methods for handling internet distributed databases and image processing. One of these methods is the Mojette transform (MOT). This transform is an exact discrete Radon transform defined for a set of specific projections. The MOT is used mainly in image processing applications. There were several implementation using personal computers [8] and [9], but these application were implemented only for locally stored images. There are some applications where real time computing is a must, but the implementations before referred can not accomplish this requirement. The Mojette transforms implemented under different operating systems and for different processors presented below helps the performance analyses of the MOT and also let to conclude the need for reconfigurable hardware implementation. There is also analyzed the implementation of Mojette transform and Inverse Mojette transform (IMOT) the implementation in Field Programmable Gate Arrays using reconfigurable platform. The paper tries to conclude the necessity for hardware implementation for real time processing. The paper outline the development work in order to create an embedded reconfigurable hardware based on FPGA board.

关键词： image processing

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Estimation in Gaussian graphical models using tractable subgraphs: A walk-sum analysis

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IEEE TRANSACTIONS ON SIGNAL processing 2008年第5期56卷 1916-1930页

作者： Chandrasekaran, Venkat Johnson, Jason K. Willsky, Alan S. MIT Informat & Decis Syst Lab Dept Elect Engn & Comp Engn Cambridge MA 02139 USA

Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, and distributed sensor networks. In this paper, we present a general class of algorithms for estimation in Gaussian graphical models with arbitrary structure. These algorithms involve a sequence of inference problems on tractable subgraphs over subsets of variables. This framework includes parallel iterations such as embedded trees, serial iterations such as block Gauss-Seidel, and hybrid versions of these iterations. We also discuss a method that uses local memory at each node to overcome temporary communication failures that may arise in distributed sensor network applications. We analyze these algorithms based on the recently developed walk-sum interpretation of Gaussian inference. We describe the walks "computed" by the algorithms using walk-sum diagrams, and show that for iterations based on a very large and flexible set of sequences of subgraphs, convergence is guaranteed in walk-summable models. Consequently, we are free to choose spanning trees and subsets of variables adaptively at each iteration. This leads to efficient methods for optimizing the next iteration step to achieve maximum reduction in error. Simulation results demonstrate that these nonstationary algorithms provide a significant speedup in convergence over traditional one-tree and two-tree iterations.

关键词： distributed estimation Gauss-Markov random fields graphical models maximum walk-sum block maximum walk-sum tree subgraph preconditioners walk-sum diagrams walk-sums

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parallel memory architecture for elliptic curve cryptography over GF_(p) aimed at efficient FPGA implementation

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JOURNAL OF SIGNAL processing SYSTEMS FOR SIGNAL image AND VIDEO TECHNOLOGY 2008年第1期51卷 39-55页

作者： Laue, Ralf Huss, Sorin A. Tech Univ Darmstadt Dept Comp Sci Integrated Circuits & Syst Lab Darmstadt Germany

parallelization of operations is of utmost importance for efficient implementation of Public Key Cryptography algorithms. Starting with a classification of parallelization methods at different abstraction levels of public key algorithms, we propose a novel memory architecture for elliptic curve implementations with multiple modular multiplier units. This architecture is well-suited for different point addition and doubling algorithms over GF(p) to be implemented on FPGAs. It allows the execution time to scale with the number of modular multipliers and exhibits nearly no overhead compared to the mere runtime of the multipliers. The advantages of this distributed memory architecture are demonstrated by means of two different point addition and doubling algorithms.

关键词： elliptic curve cryptography parallelization memory architecture FPGA

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Identifying, tabulating, and analyzing contacts between branched neuron morphologies

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IBM JOURNAL OF RESEARCH AND DEVELOPMENT 2008年第1-2期52卷 43-55页

作者： Kozloski, J. Sfyrakis, K. Hill, S. Schuermann, F. Peck, C. Markram, H. IBM Corp Div Res Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA Ecole Polytech Fed Lausanne Blue Brain Lab Brain Mind Inst Fac Sci Vie CH-1015 Lausanne Switzerland IBM Corp Div Res Thomas J Watson Res Ctr CH-1015 Lausanne Switzerland

Simulating neural tissue requires the construction of models of the anatomical structure and physiological function of neural microcircuitry. The Blue Brain Project is simulating the microcircuitry of a neocortical column with very high structural and physiological precision. This paper describes how we model anatomical structure by identifying, tabulating, and analyzing contacts between 104 neurons in a morphologically precise model of a column. A contact occurs when one element touches another, providing the opportunity for the subsequent creation of a simulated synapse. The architecture of our application divides the problem of detecting and analyzing contacts among thousands of processors on the IBM Blue Gene/L (TM) supercomputer. Data required for contact tabulation is encoded with geometrical data for contact detection and is exchanged among processors. Each processor selects a subset of neurons and then iteratively 1) divides the number of points that represents each neuron among column subvolumes, 2) detects contacts in a subvolume, 3) tabulates arbitrary categories of local contacts, 4) aggregates and analyzes global contacts, and 5) revises the contents of a column to achieve a statistical objective. Computing, analyzing, and optimizing local data in parallel across distributed global data objects involve problems common to other domains (such as three-dimensional image processing and registration). Thus, we discuss the generic nature of the application architecture.

关键词： NEURONS image processing IMAGING systems SIMULATION methods OPTICAL data processing COMPUTER graphics MOLECULAR biology MORPHOGENESIS

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Massively parallel electrical conductivity imaging of the subsurface: Applications to hydrocarbon exploration

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Journal of Physics: Conference Series 2009年第1期180卷

作者： Gregory A Newman Michael Commer Lawrence Berkeley National Laboratory MS-90-1116 Berkeley CA 94720 USA

Three-dimensional (3D) geophysical imaging is now receiving considerable attention for electrical conductivity mapping of potential offshore oil and gas reservoirs. The imaging technology employs controlled source electromagnetic (CSEM) and magnetotelluric (MT) fields and treats geological media exhibiting transverse anisotropy. Moreover when combined with established seismic methods, direct imaging of reservoir fluids is possible. Because of the size of the 3D conductivity imaging problem, strategies are required exploiting computational parallelism and optimal meshing. The algorithm thus developed has been shown to scale to tens of thousands of processors. In one imaging experiment, 32,768 tasks/processors on the IBM Watson Research Blue Gene/L supercomputer were successfully utilized. Over a 24 hour period we were able to image a large scale field data set that previously required over four months of processing time on distributed clusters based on Intel or AMD processors utilizing 1024 tasks on an InfiniBand fabric. Electrical conductivity imaging using massively parallel computational resources produces results that cannot be obtained otherwise and are consistent with timeframes required for practical exploration problems.

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Clusters versus FPGAs for Spectral Mixture Analysis-Based Lossy Hyperspectral Data Compression

Clusters versus FPGAs for Spectral Mixture Analysis-Based Lo...

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Conference on Satellite Data Compression, Communications and Archiving iv

作者： Plaza, Antonio J. Univ Extremadura Dept Technol Comp & Commun E-10071 Caceres Spain

ISBN: (纸本)9780819473042

The increasing number of airborne and satellite platforms that incorporate hyperspectral imaging spectrometers has soon created the need for efficient storage, transmission and data compression methodologies. In particular, hyperspectral data compression is expected to play a crucial role in many remote sensing applications. Many efforts have been devoted to designing and developing lossless and lossy algorithms for hyperspectral imagery. However, most available lossy compression approaches have largely overlooked the impact of mixed pixels and subpixel targets, which can be accurately modeled and uncovered by resorting to the wealth of spectral information provided by hyperspectral image data. In this paper, we develop a simple lossy compression technique which relies on the concept of spectral unmixing, one of the most popular approaches to deal with mixed pixels and subpixel targets in hyperspectral analysis. The proposed method uses a two-stage approach in which the purest spectral signatures (also called endmembers) are first extracted from the input data, and then used to express mixed pixels as linear combinations of endmembers. Analytical and experimental results are presented in the context of a real application, using hyperspectral data collected by NASA's Jet Propulsion Laboratory over the World Trade Center area in New York City, right after the terrorist attacks of September 11th. These data are used in this work to evaluate the impact of compression using different methods on spectral signature quality for accurate detection of hot spot fires. Two parallel implementations are developed for the proposed lossy compression algorithm: a multiprocessor implementation tested on Thunderhead, a massively parallel Beowulf cluster at NASA's Goddard Space Flight Center, and a hardware implementation developed on a Xilinx Virtex-II FPGA device. Combined, these parts offer a thoughtful perspective on the potential and emerging challenges of incorporating parallel d

关键词： Hyperspectral imaging data compression parallel implementations clusters of computers field programmable gate arrays (FPGAs)

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A neocortex model implementation on reconfigurable logic with streaming memory

A neocortex model implementation on reconfigurable logic wit...

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International Symposium on parallel and distributed processing (IPDPS)

作者： Christopher N. Vutsinas Tarek M. Taha Kenneth L. Rice Department of Electrical and Computer Engineering Clemson University Clemson SC USA

In this paper we study the acceleration of a new class of cognitive processing applications based on the structure of the neocortex. Our focus is on a model of the visual cortex used for image recognition developed by George and Hawkins. We propose techniques to accelerate the algorithm using reconfigurable logic, specifically a streaming memory architecture utilizing available off-chip memory. We discuss the design of a streaming memory access unit enabling a large number of processing elements to be placed on a single FPGA thus increasing throughput. We present an implementation of our approach on a Cray XD1 and discuss possible extension to further increase throughput. Our results indicate that using a two FPGA design with streaming memory gives a speedup of 71.9 times over a purely software implementation.

关键词： Reconfigurable logic Application software Brain modeling Field programmable gate arrays Concurrent computing Bayesian methods Computer architecture Acceleration image recognition Streaming media

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Sampling strategies for super-resolution in multi-slice MRI

Sampling strategies for super-resolution in multi-slice MRI

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IEEE International Conference on image processing

作者： Richard Z. Shilling Senthil Ramamurthy Marijn E. Brummer Emory University Atlanta GA USA Georgia Institute of Technology Atlanta GA USA Children''s Healthcare of Atlanta Atlanta GA USA

A comparison study is presented of two methods for MRI reconstruction using super-resolution techniques which combine multiple multi-slice stacks into a single high- resolution 3-D image volume. Sampling configurations are compared involving stacks with parallel orientations at different sub-pixel offset locations, and stacks with regularly distributed slice orientations. Results from experiments with simulated and real MRI data suggest that different stack orientations perform better than parallel stacks.

关键词： Sampling methods Magnetic resonance imaging image reconstruction Spatial resolution image sampling Signal resolution Frequency image resolution Maximum likelihood estimation Strontium

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