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10th International Conference and Expo on Emerging Technologies for a Smarter World (CEWIT)

作者： Chang, Cheng Xu, Wei Yan, Hanfei Li, Li Chu, Yong S. Yu, Dantong Brookhaven Natl Lab Computat Sci Ctr Upton NY 11973 USA

ISBN: (纸本)9781479925469

In scanning x-ray microscopy, Differential Phase Contrast (DPC) imaging is a technique to image the phase contrast information. It is based on the concept that locally a sample can be considered as a prism, which deflects the incident x-ray beam slightly in angle. Many efforts have been made in DPC imaging and a number of representative cases at a moderate spatial resolution have demonstrated the success of the method. However, the inherent limitations of those methods prevent DPC imaging from ultra-high spatial resolution imaging applications. A highly robust approach to DPC imaging based on Fourier-shift fitting was proposed recently. This method is effective in reconstructing the buried nanoscale interfacial structures. Because of the non-linear fitting and Fourier transformation operations involved in the algorithm, the computation is intensive at each scanning point. One challenge in this method is to make it fast enough to keep up with pixel-wise scanning, so that real-time data processing can be achieved. Here we provided three implementations in Matlab, Python and C++ and compared their speed performance. Experiments show that the C++ version is about one order of magnitude faster than the Matlab version and nearly two orders of magnitude faster than the Python version. In addition, we designed a parallel algorithm to divide the task into a number of independently running routines executing on a batch-queue based multi-core servers cluster and achieved almost another two orders of magnitude improvement.

关键词： Acceleration Non-linear fitting Fourier transform DPC Multi-core CPUs

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Multiview image compression and transmission techniques in Wireless Multimedia Sensor Networks: A survey

Multiview image compression and transmission techniques in W...

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ACM/IEEE International Conference on distributed Smart Cameras, ICDSC

作者： Xiaoqin Wang Y. Ahmet Şekercioğlu Tom Drummond Department of Electrical and Computer System Engineering Monash University Melbourne Australia

We present a survey of recent research works on multiview image compression and transmission techniques developed for Wireless Multimedia Sensor Networks (WMSNs). We classify them into two categories with respect to the coding methods adopted: (i) in-network processing with joint coding schemes, and (ii) distributed source coding schemes. The survey also includes a comprehensive evaluation of the limitations of each approach. Based on the review results, we discuss future research directions, and identify the ways of more efficient transmission of the spatially correlated and redundant data in WMSNs.

关键词： Cameras Correlation image coding Decoding Joints Visualization Encoding

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A Study of the Behavior of Synchronization methods in Commonly Used Languages and Systems

A Study of the Behavior of Synchronization Methods in Common...

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International Symposium on parallel and distributed processing (IPDPS)

作者： Daniel Cederman Bapi Chatterjee Nhan Nguyen Yiannis Nikolakopoulos Marina Papatriantafilou Philippas Tsigas Computer Science and Engineering Chalmers University of Technology Sweden

ISBN: (纸本)9781467360661

Synchronization is a central issue in concurrency and plays an important role in the behavior and performance of modern programmes. Programming languages and hardware designers are trying to provide synchronization constructs and primitives that can handle concurrency and synchronization issues efficiently. Programmers have to find a way to select the most appropriate constructs and primitives in order to gain the desired behavior and performance under concurrency. Several parameters and factors affect the choice, through complex interactions among (i) the language and the language constructs that it supports, (ii) the system architecture, (iii) possible run-time environments, virtual machine options and memory management support and (iv) applications. We present a systematic study of synchronization strategies, focusing on concurrent data structures. We have chosen concurrent data structures with different number of contention spots. We consider both coarse-grain and fine-grain locking strategies, as well as lock-free methods. We have investigated synchronization-aware implementations in C++, C# (.NET and Mono) and Java. Considering the machine architectures, we have studied the behavior of the implementations on both Intel's Nehalem and AMD's Bulldozer. The properties that we study are throughput and fairness under different workloads and multiprogramming execution environments. For NUMA architectures fairness is becoming as important as the typically considered throughput property. To the best of our knowledge this is the first systematic and comprehensive study of synchronization-aware implementations. This paper takes steps towards capturing a number of guiding principles and concerns for the selection of the programming environment and synchronization methods in connection to the application and the system characteristics.

关键词： Synchronization Instruction sets Data structures Throughput Memory management Java Programming

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A Laplace transform method for the image in-painting

A Laplace transform method for the image in-painting

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The 12th International Symposium on distributed Computing and Applications to Business,Engineering and Science(DCABES 2013)(第十二届分布式计算及其应用国际学术研讨会)

作者： N.Kokulan C.-H.Lai School of Computing and Mathematical Sciences University of Greenwich London UK

There are many image processing techniques based on partial differential equations that perform well,but they consume much computational ***'s vital that rapid and efficient ways of solving these equations are *** of the Laplace transforms permits solution to the time dependent problems in a parallel *** solution procedure requires numerical computation of an inverse Laplace transform of which the Stehfest method was examined in the *** investigated the performance and efficiency of using the Laplace transform technique for the solution of a mathematical model related to image in-painting and compared the results with temporal integration.

关键词： CDD in-painting temporal parallel methods time dependent problems

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GPU-Accelerated Protein Family Identification for Metagenomics

GPU-Accelerated Protein Family Identification for Metagenomi...

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Changjun Wu Ananth Kalyanaraman Xerox Innovation Group Xerox Research Center Webster NY USA

ISBN: (纸本)9781479913725

The clustering of putative protein/Open Reading Frame (ORF) sequences available from large-scale metagenomics survey projects is a core analytical function that has led to the identification and characterization of novel protein families of environmental microbial communities. The implementation of this function, however, is currently challenged not only by data size but also by data complexity. In this paper, we present a CPU-GPU implementation of a randomized graph clustering heuristic called Shingling, which was originally developed by Gibson et al. Our implementation uses the CPU and GPU for different stages of computation, using GPUs for the most time-consuming steps. Experimental results of a 2M ocean metagenomics data set obtained from the Sorcerer ii Global Ocean Sampling project show that our new implementation is able to achieve a ~7X speedup over our serial implementation without using asynchronous CPU-GPU communication, with the GPU part alone contributing to over ~374X speedup in the accelerated part. Qualitative evaluation of the 2M data set shows that our method is able to improve sensitivity of clustering over existing methods, and is more successful in recruiting more sequences into the clustering without impacting the overall specificity. As a demonstration of a large scale run, we were able to cluster a real world homology graph, containing 11M vertices and 640M edges, and constructed from sequences of an ongoing Pacific Ocean metagenomics survey project, in about 94 minutes.

关键词： Graphics processing units Instruction sets Proteins Clustering algorithms Oceans Random access memory Algorithm design and analysis

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Scheduling Tightly-Coupled Applications on Heterogeneous Desktop Grids

Scheduling Tightly-Coupled Applications on Heterogeneous Des...

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IEEE International Symposium on parallel and distributed processing Workshops and Phd Forum (IPDPSW)

作者： Henri Casanova Fanny Dufossé Yves Robert Frédéric Vivien Univ. of Hawai`i at Manoa Honolulu USA Laboratoire I3S Polytech'Nice France ENS Lyon & INRIA France

ISBN: (纸本)9781479913725

Platforms that comprise volatile processors, such as desktop grids, have been traditionally used for executing independent-task applications. In this work we study the scheduling of tightly-coupled iterative master-worker applications onto volatile processors. The main challenge is that workers must be simultaneously available for the application to make progress. We consider three additional complications: (i) one should take into account that workers can become temporarily reclaimed and, for data-intensive applications; (ii) one should account for the limited bandwidth between the master and the workers; and (iii) workers are strongly heterogeneous, with different computing speeds and availability probability distributions. In this context, our first contribution is a theoretical study of the scheduling problem in its off-line version, i.e., when processor availability is known in advance. Even in this case the problem is NP-hard. Our second contribution is an analytical approximation of the expectation of the time needed by a set of workers to complete a set of tasks and of the probability of success of this computation. This approximation relies on a Markovian assumption for the temporal availability of processors. Our third contribution is a set of heuristics, some of which use the above approximation to favor reliable processors in a sensible manner. We evaluate these heuristics in simulation. We identify some heuristics that significantly outperform their competitors and derive heuristic design guidelines.

关键词： Program processors Processor scheduling Availability Computational modeling Bandwidth Scheduling Approximation methods

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Multi-label Classification with Clustering for image and Text Categorization

Multi-label Classification with Clustering for Image and Tex...

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International Congress on image and Signal processing

作者： Gulisong Nasierding Atul Sajjanhar School of Computer Science and Technology Xinjiang Normal University Parallel and Distributed Computing Lab School of Information Technology Deakin University

ISBN: (纸本)9781479927654

This paper explores effective multi-label classification methods for multi-semantic image and text categorization. We perform an experimental study of clustering based multi-label classification (CBMLC) for the target problem. Experimental evaluation is conducted for identifying the impact of different clustering algorithms and base classifiers on the predictive performance and efficiency of CBMLC. In the experimental setting, three widely used clustering algorithms and six popular multi-label classification algorithms are used and evaluated on multi-label image and text datasets. A multi-label classification evaluation metrics, micro F1-measure, is used for presenting predictive performances of the classifications. Experimental evaluation results reveal that clustering based multi-label learning algorithms are more effective compared to their non-clustering counterparts.

关键词： Multi-label classification Clustering image and text categorization

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Efficient hardware calculation of running statistics

Efficient hardware calculation of running statistics

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International Conference on image and Vision Computing New Zealand, IVCNZ

作者： Donald G. Bailey Michael J. Klaiber School of Engineering and Advanced Technology Massey University Palmerston North Institute for Parallel and Distributed Systems University of Stuttgart

Calculation of mean, variance and standard deviation are often required for segmentation or feature extraction. In image processing, often an integer approximation is adequate. Conventional methods require division and square root operations, which are expensive to realize in hardware in terms of both the amount of required resources and latency. A new class of iterative algorithms is developed based on integer arithmetic. An implementation of the algorithms as a hardware architecture for a Field-Programmable Gate Array (FPGA) is compared with architectures using the conventional approach, which shows a significantly reduced latency while using less hardware resources.

关键词： Hardware Computer architecture Standards Approximation methods Nickel Accuracy Feature extraction

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A parallel solution for high resolution histological image analysis

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COMPUTER methods AND PROGRAMS IN BIOMEDICINE 2012年第1期108卷 388-401页

作者： Bueno, G. Gonzalez, R. Deniz, O. Garcia-Rojo, M. Gonzalez-Garcia, J. Fernandez-Carrobles, M. M. Vallez, N. Salido, J. Univ Castilla La Mancha VISILAB ETS Ingenieros Ind E-13071 Ciudad Real Spain Hosp Gen Univ Ciudad Real Dpt Anat Patol Ciudad Real Spain

This paper describes a general methodology for developing parallel image processing algorithms based on message passing for high resolution images (on the order of several Gigabytes). These algorithms have been applied to histological images and must be executed on massively parallel processing architectures. Advances in new technologies for complete slide digitalization in pathology have been combined with developments in biomedical informatics. However, the efficient use of these digital slide systems is still a challenge. The image processing that these slides are subject to is still limited both in terms of data processed and processing methods. The work presented here focuses on the need to design and develop parallel image processing tools capable of obtaining and analyzing the entire gamut of information included in digital slides. Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images. Code portability, reusability and scalability have been tested by using the following parallel computing architectures: distributed memory with massive parallel processors and two networks, INFINIBAND and Myrinet, composed of 17 and 1024 nodes respectively. The parallel framework proposed is flexible, high performance solution and it shows that the efficient processing of digital microscopic images is possible and may offer important benefits to pathology laboratories. (c) 2012 Elsevier Ireland Ltd. All rights reserved.

关键词： Low and high-level parallel image processing High resolution histological image processing MPI Microscopy Whole slide imaging

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Do you see what i see?

Do you see what i see?

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Applied imagery Pattern Recognition Workshop (AIPR)

作者： P.S. Cerkez DCS Corporation MD USA

Semagrams are a subset of steganography. When a message is transmitted in a non-textual format, (i.e., in the visual content of an image), it is referred to as a semagram. While semagrams are relatively easy to create (as shown in published papers covering hiding techniques), detecting a hidden message in or embedded as an image-based semagram is a greater magnitude of difficultly than typical digital steganography. US Patents issued based on semagram technology show that this feature has been exploited in the copyright/watermarking world to increase protection. In a semagram, the image is the message and they work well for simple messages and dead drops. Attacks on semagrams are primarily visual examinations of artifacts. In the counter-espionage world, the rule of the thumb is that there is always a message hidden in an image or graphic, it is simply up to the steganalyst to find it. In short, detecting semagrams is a matter of recognizing patterns of patterns that represent a hidden message within an image. This presentation provides a brief summary of the technology underlying semagrams, present a short non-technical discussion of the technology used in the attack on semagrams, followed by a discussion on current work and planned future implementations of the proven semagram detection ANN. It will focus on extending the ANN to other domains (e.g., non-visual spectrums, multi/cross spectrum correlation, scene identification, image classification) and efforts to improve the processing speed and throughput via parallel/distributed methods.

关键词： Training Testing image coding Artificial neural networks Context Pattern recognition

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