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中国医疗器械杂志 2015年第1期39卷 1-4页

作者：方思敏周盛王晓春叶青盛田玲计建军王延群北京协和医学院中国医学科学院生物医学工程研究所天津市300192 天津市眼科医学设备技术工程中心天津市300384

目的基于FPGA对眼科超声诊断仪中的信号处理算法进行设计和改进。方法在Quartus ii中用Verilog HDL硬件语言实现全并行分布式动态滤波、数字正交检波、二叉树法对数压缩三大信号处理模块。结果相对原有系统,硬件开销减少,整体成像更为清... 详细信息

目的基于FPGA对眼科超声诊断仪中的信号处理算法进行设计和改进。方法在Quartus ii中用Verilog HDL硬件语言实现全并行分布式动态滤波、数字正交检波、二叉树法对数压缩三大信号处理模块。结果相对原有系统,硬件开销减少,整体成像更为清晰,眼球深部的信息更为完整,探测深度由原来的5 cm提高到6 cm。结论所设计的算法达到了设计要求,能够有效提高现有设备的成像质量,实现了系统优化。

关键词：眼科超声数字信号处理动态滤波正交检波对数压缩

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Permutation enhanced parallel reconstruction for compressive sampling

Permutation enhanced parallel reconstruction for compressive...

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IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive processing (CAMSAP)

作者： Hao Fang Serigy A. Vorobyov Hai Jiang Department of Electrical Engineering University of Washington Seattle WA USA Department of Signal Processing and Acoustics Aalto University AALTO Finland Department of Electrical and Computer Engineering University of Alberta AB Canada

In this paper, a simple but efficient permutation enhanced parallel reconstruction architecture for compressive sampling (CS) is proposed. In this architecture, a measurement matrix is constructed from a block-diagonal sensing matrix, the sparsifying basis of the target signal, and a pre-defined permutation matrix. In this way, the projection of the signal onto the sparsifying basis can be divided into several segments and all segments can be reconstructed in parallel. Thus, the computational complexity and the time for reconstruction can be reduced significantly. With a good permutation matrix, the error performance of the proposed method can be improved compared with the option without permutation. The proposed method can be used in applications where the computational complexity and time for reconstruction are crucial evaluation criteria and centralized sampling is acceptable. Simulation results show that the proposed method can achieve comparable results to the centralized reconstruction methods (i.e., standard CS and distributed CS), while requiring much less reconstruction time.

关键词： Sensors image reconstruction Sparse matrices Computational complexity Decoding Computer architecture Simulation

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Robust Weighted Supervised Sparse Coding for image Classification

Robust Weighted Supervised Sparse Coding for Image Classific...

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2015 IEEE 16th International Conference on Communication Technology(ICCT 2015)

作者： Xiang Zhang Naiyang Guan Zhigang Luo College of Computer National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Sparse coding has shown its great potential in learning image feature representation. Recent developed methods such as group sparse coding prefer discovering the group relationships among examples and have achieved the state-of-the-art results in image classification. However, they suffer from poor robustness shortcomings in practice. This paper proposes a robust weighted supervised sparse coding method(RWSSC) to address this ***, RWSSC distinguishes different classes' contributions to the sparse coding by a novel weighting strategy meanwhile removes the out liers by imposing1 l-regularization over the noisy entries. Benefitting from these strategies, RWSSC can effectively boost performance of sparse coding in image ***, we developed the block coordinate descent algorithm to optimize it, and proved its *** results of image classification on two popular datasets show that RWSSC outperforms the representative sparse coding methods in quantities.

关键词： Sparse coding Supervised learning image classification

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Robust weighted supervised sparse coding for image classification

Robust weighted supervised sparse coding for image classific...

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International Conference on Communication Technology (ICCT)

作者： Xiang Zhang Naiyang Guan Zhigang Luo College of Computer National University of Defense Technology Changsha China National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China

ISBN: (纸本)9781467370066

Sparse coding has shown its great potential in learning image feature representation. Recent developed methods such as group sparse coding prefer discovering the group relationships among examples and have achieved the state-of-the-art results in image classification. However, they suffer from poor robustness shortcomings in practice. This paper proposes a robust weighted supervised sparse coding method (RWSSC) to address this deficiency. Particularly, RWSSC distinguishes different classes' contributions to the sparse coding by a novel weighting strategy meanwhile removes the out liers by imposing l1-regularization over the noisy entries. Benefitting from these strategies, RWSSC can effectively boost performance of sparse coding in image classification. Besides, we developed the block coordinate descent algorithm to optimize it, and proved its convergence. Experimental results of image classification on two popular datasets show that RWSSC outperforms the representative sparse coding methods in quantities.

关键词： Support vector machines Robustness Classification algorithms Dictionaries Manganese

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基于MPI的大规模遥感影像金字塔并行构建方法

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地球信息科学学报 2015年第5期17卷 515-522页

作者：赫高进熊伟陈荦吴秋云景宁国防科学技术大学电子科学与工程学院长沙410073

影像金字塔是实现影像数据多分辨率组织的重要方式,是提高影像可视化性能的有效手段。传统串行金字塔构建算法,对大规模影像数据的构建性能已无法满足遥感影像快速浏览的预处理需求。故此,其成为一个亟待解决的问题,而利用多核、多节点... 详细信息

影像金字塔是实现影像数据多分辨率组织的重要方式,是提高影像可视化性能的有效手段。传统串行金字塔构建算法,对大规模影像数据的构建性能已无法满足遥感影像快速浏览的预处理需求。故此,其成为一个亟待解决的问题,而利用多核、多节点的高性能集群计算环境和并行机制是一个重要的技术途径。本文在共享外存的高性能集群环境下,提出使用消息传递接口(MPI)的金字塔并行构建算法,对构建遥感影像金字塔过程中的重采样与I/O过程进行并行处理,大大缩短了遥感影像金字塔构建时间。实验结果表明:(1)该算法比传统串行构建方法的加速效果明显,对于单波段遥感影像,其加速效果可达到GDAL的5倍以上,而对于多波段遥感影像,加速效果可达到GDAL的2倍以上;(2)遥感影像数据量越大,并行构建算法加速效果越显著,对于大规模的遥感影像,本文提出的金字塔并行构建算法的速度可达到GDAL的10倍左右。

关键词：遥感影像金字塔消息传递接口并行集群

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ObsCon: Integrated Monitoring and Control for parallel, Real-Time Applications

ObsCon: Integrated Monitoring and Control for Parallel, Real...

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IEEE International Conference on Cluster Computing

作者： Alan Nussbaum Shwetha Mathangi Chandra Choodamani Karsten Schwan College of Computing Georgia Institute of Technology Atlanta GA

A large class of emerging compute-intensive applications demand real-time or near real-time processing guarantees on streaming data. Sensor processing in particular, has stringent latency requirements for carrying out its digital processing for rapidly incoming radar data streams. The consequent demands on the cluster middleware used to run such codes include (i) efficient online observation of current application performance, coupled with (ii) highly responsive controllers able to dynamically adjust the application's input-and data-dependent runtime behavior. We present the Obs(erver)Con(troller) software for online monitoring and control, which based on specifications of acceptable application states and tunable knobs within the execution environment, ensures that application performance falls within acceptable limits. ObsCon topologies are dynamic, making possible the runtime association of ObsCon methods with arbitrary DAG-structured, distributed/parallel stream processing applications running on high end cluster machines. This paper describes the ObsCon software and its 'grey box' use with a high performance cluster code that exports to ObsCon select 'hooks' for online monitoring and control -- Adaptive Digital Beamforming for a phase-array radar system.

关键词： Monitoring Peer-to-peer computing Runtime Topology Real-time systems Middleware Radar

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New accelerated graph-based method of image segmentation applying minimum spanning tree

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IET image processing 2014年第4期8卷 239-251页

作者： Fabijanska, Anna Goclawski, Jaroslaw Lodz Univ Technol Inst Appl Comp Sci Lodz Poland

In this paper problem of graph based image segmentation is considered. In particular, attention is paid to minimal spanning tree based algorithm proposed by Felzenszwalb and Huttenlocher (FH). Although the method yields high quality results for various classes of images, its application is limited mainly to off-line processing. Its due to the very long execution time of the FH method, which in the case of high resolution images, requires processing of millions of vertices and edges contained within the resulting graph. Therefore, some improvements to the FH method are proposed in this paper. The modifications aim at the reduction of algorithm execution time and the usage of computer host memory. These goals are achieved both by reducing the size of input image graph and by applying the methods of GPU parallel computing at initial stages of the algorithm. As the reduction of graph size is obtained by processing meta-pixels representing homogenous regions, the new method is most suitable for the segmentation of images including rare, structurally complex objects distributed over nonuniform background. Results obtained by the introduced approach are compared with the results of the original FH method and other popular graph-based approaches to image segmentation. The comparison includes both the accuracy of image segmentation and the execution time. Analysis of the results clearly shows, that the proposed approach in many cases can significantly accelerate segmentation process without a noticeable loss of image segmentation quality.

关键词： graph theory image segmentation trees (mathematics) image segmentation minimum tree accelerated graph-based method FH algorithm Felzenszwalb and Huttenlocher algorithm

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EFFICIENT RENDERING OF COMPLEX SCENES ON HETEROGENEOUS parallel ARCHITECTURES

EFFICIENT RENDERING OF COMPLEX SCENES ON HETEROGENEOUS PARAL...

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作者： GOKCE YILDIRIM KALKAN Middle East Technical University

学位级别：博士

In computer graphics, generating high-quality images at high frame rates for render- ing complex scenes is a challenging task. A well-known approach to tackling this important task is to utilize parallel processing through distributing rendering and sim- ulation tasks to different processing units. In this thesis, several methods of distributed rendering architectures are investigated, and the bottlenecks in distributed rendering are analyzed. Based on this analysis, guidelines for distributed rendering in a network of computers are proposed. Moreover, in the thesis, an efficient load balancing strategy is proposed for distribut- ing the rendering of individual frames to different processing units in a network. In this distributed rendering heterogeneous system, there are computers equipped with multiple Graphical processing Units (GPUs) with different rendering performances all in the same network with a server, which collects rendering performances of the GPUs in the different image Generators (IGs) based on an effective load balancing. By means of the novel load balancing strategy, the thesis shows that such a system can increase the rendering performance of slow computers with the help of the fast ones. Lastly, this model is extended to develop an adaptive hybrid model where (i) parts of a frame or a scene can be distributed and (ii) GPU-GPU and GPU-CPU distributions can be considered. This model can adjust itself to the changing loads of the GPUs and determine an efficient load balancing strategy for distributed rendering.

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Oscillatory Neural Networks: In Problems of parallel Information processing

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2014年

作者： Margarita G. Kuzmina Eduard A. Manykin Evgeny S. Grichuk

ISBN: (数字)9783110269208

ISBN: (纸本)9783110268355

Understanding of the human brain functioning currently represents a challenging problem. In contrast to usual serial computers and complicated hierarchically organized artificial man-made systems, decentralized, parallel and distributed information processing principles are inherent to the brain. Besides adaptation and learning, which play a crucial role in brain functioning, oscillatory neural activity, synchronization and resonance accompany the brain work. Neural-like oscillatory network models, designed by the authors for image processing, allow to elucidate the capabilities of dynamical, synchronization-based types of image processing, presumably exploited by the brain. The oscillatory network models, studied by means of computer modeling and qualitative analysis, are presented and discussed in the book. Some other problems of parallel distributed information processing are also considered, such as a recall process from network memory for large-scale recurrent associative memory neural networks, performance of oscillatory networks of associative memory, dynamical oscillatory network methods of image processing with synchronization-based performance, optical parallel information processing based on the nonlinear optical phenomenon of photon echo, and modeling random electric fields of quasi-monochromatic polarized light beams using systems of superposed stochastic oscillators. This makes the book highly interesting to researchers dealing with various aspects of parallel information processing.

关键词： Human information processing. Neural networks (Neurobiology)

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Poster - 01: LabPET ii Pixelated APD-Based PET Scanner for High-Resolution Preclinical Imaging

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Medical Physics 2016年第8PART1期43卷 4935-4935页

作者： Roger Lecomte Louis Arpin Jean-François Beaudoin Mélanie Bergeron Jonathan Bouchard Haithem Bouziri Jules Cadorette Émilie Gaudin Nadia Jürgensen Konin Calliste Koua Pierre-Yves Lauzier Trépanier Jean-Daniel Leroux Francis Loignon-Houle Larissa Njejimana Maxime Paillé Caroline Paulin Catherine Pepin Jean-François Pratte Arnaud Samson Christian Thibaudeau Nicolas Viscogliosi Réjean Fontaine Université de Sherbrooke Université de Sherbrooke CIMS/CRCHUS Université de Sherbrooke Université de Sherbrooke Université de Sherbrooke CIMS/CRCHUS Université de Sherbrooke Université de Sherbrooke 3IT Université de Sherbrooke Novalgo Inc. Université de Sherbrooke Université de Sherbrooke CIMS/CRCHUS 3IT Université de Sherbrooke Université de Sherbrooke Université de Sherbrooke Université de Sherbrooke 3IT Université de Sherbrooke

Purpose: LabPET ii is a new generation APD-based PET scanner designed to achieve sub-mm spatial resolution using truly pixelated detectors and highly integrated parallel front-end processing electronics. methods: The basic element uses a 4×8 array of 1.12×1.12 mm 2 Lu 1.9 Y 0.1 SiO 5 :Ce (LYSO) scintillator pixels with one-to-one coupling to a 4×8 pixelated monolithic APD array mounted on a ceramic carrier. Four detector arrays are mounted on a daughter board carrying two flip-chip, 64-channel, mixed-signal, application-specific integrated circuits (ASIC) on the backside interfacing to two detector arrays each. Fully parallel signal processing was implemented in silico by encoding time and energy information using a dual-threshold Time-over-Threshold (ToT) scheme. The self-contained 128-channel detector module was designed as a generic component for ultra-high resolution PET imaging of small to medium-size animals. Results: Energy and timing performance were optimized by carefully setting ToT thresholds to minimize the noise/slope ratio. ToT spectra clearly show resolved 511 keV photopeak and Compton edge with ToT resolution well below 10%. After correction for nonlinear ToT response, energy resolution is typically 24±2% FWHM. Coincidence time resolution between opposing 128-channel modules is below 4 ns FWHM. Initial imaging results demonstrate that 0.8 mm hot spots of a Derenzo phantom can be resolved. Conclusion: A new generation PET scanner featuring truly pixelated detectors was developed and shown to achieve a spatial resolution approaching the physical limit of PET. Future plans are to integrate a small-bore dedicated mouse version of the scanner within a PET/CT platform.

关键词： Positron emission tomography image sensors parallel processing Detector arrays Spatial resolution Scintillation detectors Carrier generation Ceramics Flip chip Integrated circuits

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