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International Symposium on Logistics and Industrial Informatics, LINDI

作者： Attila Reményi Sándor Szénási István Bándi Zoltán Vámossy Gábor Valcz Pál Bogdanov Szabolcs Sergyán Miklos Kozlovszky John von Neumann Faculty of Informatics Óbuda University Budapest Hungary 2nd Department of Internal Medicine Semmelweiss University Budapest Hungary Laboratory of Parallel and Distributed Computing MTA SZTAKI Budapest Hungary

The main aim of this work is to show, how GPGPUs can facilitate certain type of image processing methods. The software used in this paper is used to detect special tissue part, the nuclei on (HE - hematoxilin eosin) stained colon tissue sample images. Since pathologists are working with large number of high resolution images - thus require significant storage space -, one feasible way to achieve reasonable processing time is the usage of GPGPUs. The CUDA software development kit was used to develop processing algorithms to NVIDIA type GPUs. Our work focuses on how to achieve better performance with coalesced global memory access when working with three-channel RGB tissue images, and how to use the on-die shared memory efficiently.

关键词： Graphics processing unit Instruction sets image processing Memory management Optimization Kernel Colon

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Informatics Engineering and Information Science, Part ii 2011

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丛书名： Communications in Computer and Information Science

2011年

作者： Azizah Abd Manaf Akram Zeki Mazdak Zamani Suriayati Chuprat Eyas El-Qawasmeh

ISBN: (数字)9783642254536

ISBN: (纸本)9783642254529

This 4-Volume-Set, CCIS 0251 - CCIS 0254, constitutes the refereed proceedings of the International Conference on Informatics Engineering and Information Science, ICIEIS 2011, held in Kuala Lumpur, Malaysia, in November 2011. The 210 revised full papers presented together with invited papers in the 4 volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on e-learning, information security, software engineering, image processing, algorithms, artificial intelligence and soft computing, e-commerce, data mining, neural networks, social networks, grid computing, biometric technologies, networks, distributed and parallel computing, wireless networks, information and data management, web applications and software systems, multimedia, ad hoc networks, mobile computing, as well as miscellaneous topics in digital information and communications.

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An ethological motion capture system

An ethological motion capture system

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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 parallel resampling scheme and its application to distributed particle filtering in wireless networks

A parallel resampling scheme and its application to distribu...

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

作者： Katrin Achutegui Joaquín Míguez Department of Signal Theory and Communications Universidad Carlos III de Madrid Leganes Spain

We address the design of a particle filter (PF) that can be implemented in a distributed manner over a network of wireless sensor nodes, each of them collecting their own local data. This is a problem that has received considerable attention lately and several methods based on consensus, the transmission of likelihood information, the truncation and/or the quantization of data have been proposed. However, all existing schemes suffer from limitations related either to the amount of required communications among the nodes or the accuracy of the filter outputs. In this work we propose a novel distributed PF that is built around the distributed resampling with non-proportional allocation (DRNA) algorithm. This scheme guarantees the properness of the particle approximations produced by the filter and has been shown to be both efficient and accurate when compared with centralized PFs. The standard DRNA technique, however, places stringent demands on the communications among nodes that turn out impractical for a typical wireless sensor network (WSN). In this paper we investigate how to reduce this communication load by using (i) a random model for the spread of data over the WSN and (ii) methods that enable the out-of-sequence processing of sensor observations. A simple numerical illustration of the performance of the new algorithm compared with a centralized PF is provided.

关键词： Wireless sensor networks Artificial neural networks Approximation algorithms Signal processing Markov processes Vectors Approximation methods

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Architecture-Aware Mapping and Optimization on a 1600-Core GPU

Architecture-Aware Mapping and Optimization on a 1600-Core G...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Mayank Daga Thomas Scogland Wu-chun Feng Department of Computer Science Virginia Tech USA USA

The graphics processing unit (GPU) continues to make in-roads as a computational accelerator for high-performance computing (HPC). However, despite its increasing popularity, mapping and optimizing GPU code remains a difficult task, it is a multi-dimensional problem that requires deep technical knowledge of GPU architecture. Although substantial literature exists on how to map and optimize GPU performance on the more mature NVIDIA CUDA architecture, the converse is true for OpenCL on an AMD GPU, such as the 1600-core AMD Radeon HD 5870 GPU. Consequently, we present and evaluate architecture-aware mapping and optimizations for the AMD GPU. The most prominent of which include (i) explicit use of registers, (ii) use of vector types, (iii) removal of branches, and (iv) use of image memory for global data. We demonstrate the efficacy of our AMD GPU mapping and optimizations by applying each in isolation as well as in concert to a large-scale, molecular modeling application called GEM. Via these AMD-specific GPU optimizations, our optimized OpenCL implementation on an AMD Radeon HD 5870 delivers more than a four-fold improvement in performance over the basic OpenCL implementation. In addition, it outperforms our optimized CUDA version on an NVIDIA GTX280 by 12%. Overall, we achieve a speedup of 371-fold over a serial but hand-tuned SSE version of our molecular modeling application, and in turn, a 46-fold speedup over an ideal scaling on an 8-core CPU.

关键词： Graphics processing unit Optimization Kernel Instruction sets Computer architecture Vectors Registers

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High Performance Scalable and Expressive Modeling Environment to Study Mobile Malware in Large Dynamic Networks

High Performance Scalable and Expressive Modeling Environmen...

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International Symposium on parallel and distributed processing (IPDPS)

作者： Karthik Channakeshava Keith Bisset V.S. Anil Kumar Madhav Marathe Shrirang Yardi Virginia Bioinformatics Institute Virginia Polytechnic Institute and State University Blacksburg VA USA Virginia Polytechnic Institute and State University Blacksburg VA US NVIDIA Corporation Santa Clara CA USA

Large scale realistic simulations of malware on mobile wireless networks have recently become an increasingly important application of high-performance computing. We propose EpiCure - an individual-based, scalable high performance computing oriented modeling environment to study malware propagation over realistic mobile networks. It is designed specifically to work on commodity cluster architectures. EpiCure runs extremely fast for realistic instances that involve: (i) large time-varying networks consisting of millions of heterogeneous individuals with time varying interaction neighborhoods, (ii) dynamic interactions between disease propagation, device behavior, and the exogenous interventions, and (iii) large number of replicated runs necessary for statistically sound estimates about the stochastic epidemic evolution. We find that EpiCure runs several orders of magnitude faster than another comparable simulation tool while delivering similar results. Beyond simple compute speed, EpiCure has been designed so that analysts can easily represent a range of interventions leading to improved human productivity and ease of use. This is an increasingly important metric in high performance computing. We illustrate EpiCure using three case studies that bring out the novel features of EpiCure.

关键词： Malware Computational modeling Wireless communication Approximation methods Ad hoc networks Software Mobile communication

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Acceleration of Two Point Correlation Function Calculation for Pathology image Segmentation

Acceleration of Two Point Correlation Function Calculation f...

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IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB)

作者： Lee A.D. Cooper Joel H. Saltz Umit Catalyurek Kun Huang Center of Comprehensive Informatics Emory University Atlanta GA USA Department of Biomedical Informatics Ohio State University Columbus OH USA

The segmentation of tissue regions in high-resolution microscopy is a challenging problem due to both the size and appearance of digitized pathology sections. The two point correlation function (TPCF) has proved to be an effective feature to address the textural appearance of tissues. However the calculation of the TPCF functions is computationally burdensome and often intractable in the gigapixel images produced by slide scanning devices for pathology application. In this paper we present several approaches for accelerating deterministic calculation of point correlation functions using theory to reduce computation, parallelization on distributed systems, and parallelization on graphics processors. Previously we show that the correlation updating method of calculation offers an 8-35x speedup over frequency domain methods and decouples efficient computation from the select scales of Fourier methods. In this paper, using distributed computation on 64 compute nodes provides a further 42x speedup. Finally, parallelization on graphics processors (GPU) results in an additional 11-16x speedup using an implementation capable of running on a single desktop machine.

关键词： Correlation Graphics processing unit parallel processing Instruction sets image segmentation Interpolation

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Biomedical image processing with GPGPU using CUDA

Biomedical image processing with GPGPU using CUDA

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Proceedings of the International Convention MIPRO

作者： A. R. Firstauthor I. B. Secondauthor G. V. Thirdauthor P. B. Fourthauthor M. K. Fifthauthor Óbuda University/John von Neumann Faculty of Informatics Budapest Hungary Semmelweiss University/Znd Department of Internal Medicine Budapest Hungary MTA SZTAKI/Laboratory of Parallel and Distributed Computing Budapest Hungary

The main aim of this work is to show, how the GPGPUs can be used to speed up certain image processing methods. The algorithm explained in this paper is used to detect nuclei on (HE - hematoxilin eosin) stained colon tissue sample images, and includes a Gauss blurring, an RGB-HSV color space conversion, a fixed binarization, an ultimate erode procedure and a local maximum search. Since the images retrieved from the digital slides require significant storage space (up to few hundred megapixels), the usage of GPGPUs to speed up image processing operations is necessary in the interest of achieving reasonable processing time. The CUDA software development kit was used to develop algorithms to GPUs made by NVIDIA. This work focuses on how to achieve coalesced global memory access when working with three-channel RGB images, and how to use the on-die shared memory efficiently. The exact test algorithm also included a linear connected component labeling, which was running on the CPU, and with iterative optimization of the GPU code, we managed to achieve significant speed up in well defined test environment.

关键词： Graphics processing unit Instruction sets image processing Kernel Optimization Memory management Pixel

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First On-Site Data Analysis System for Subaru/Suprime-Cam

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PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF JAPAN 2011年第sp2期63卷 S585-S603页

作者： Furusawa, Hisanori Okura, Yuki Mineo, Sogo Takata, Tadafumi Nakata, Fumiaki Tanaka, Manobu Katayama, Nobuhiko Itoh, Ryosuke Yasuda, Naoki Miyazaki, Satoshi Komiyama, Yutaka Utsumi, Yousuke Uchida, Tomohisa Aihara, Hiroaki Natl Astron Observ Japan Tokyo 1818858 Japan Univ Tokyo Sch Sci Dept Phys Bunkyo Ku Tokyo 1330033 Japan Natl Astron Observ Japan Subaru Telescope Hilo HI 96720 USA High Energy Accelerator Res Org KEK Inst Particle & Nucl Studies Ibaraki 3050801 Japan Univ Tokyo Univ IPMU Inst Phys & Math Kashiwa Chiba 2778583 Japan

We developed an automated on-site quick analysis system for mosaic CCD data of Suprime-Cam, which is a wide-field camera mounted at the prime focus of the Subaru Telescope, Mauna Kea, Hawaii. The first version of the data-analysis system was constructed;and started to operate in general observations. This system is a new function of observing support at the Subaru Telescope to provide the Subaru user community with an automated on-site data evaluation, aiming at improvements of observers' productivity, especially in large imaging surveys. The new system assists the data evaluation tasks in observations by the continuous monitoring of the characteristics of every data frame during observations. The evaluation results and data frames processed by this system are also useful for reducing the data-processing time in a full analysis after an observation. The primary analysis functions implemented in the data-analysis system are composed of automated realtime analysis for data evaluation and on-demand analysis, which is executed upon request, including mosaicing analysis and flat making analysis. In data evaluation, which is controlled by the organizing software, the database keeps track of the analysis histories, as well as the evaluated values of data frames, including seeing and sky background levels;it also helps in the selection of frames for mosaicing and flat making analysis. We examined the system performance and confirmed an improvement in the data-processing time by a factor of 9 with the aid of distributed parallel data processing and on-memory data processing, which makes the automated data evaluation effective.

关键词： Astronomical data bases: miscellaneous methods: data analysis Techniques: image processing

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Stereo Reconstruction of Building Interiors with a Vertical Structure Prior

Stereo Reconstruction of Building Interiors with a Vertical ...

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International Conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： Bernhard Zeisl Christopher Zach Marc Pollefeys Computer Vision and Geometry Group ETH Zürich Switzerland

image-based computation of a 3D map for an indoor environment is a very challenging task, but also a useful step for vision-based navigation and path planning for autonomous systems, and for efficient visualization of interior spaces. Since computational stereo is a highly ill-posed problem for the typically weakly textured, specular, and even sometimes transparent indoor environments, one has to incorporate very strong prior assumptions on the observed geometry. A natural assumption for building interiors is that open space is bounded (i) by parallel ground and ceiling planes, and (ii) by vertical (not necessarily orthogonal) wall elements. We employ this assumption as a strong prior in dense depth estimation from stereo images. The additional assumption of smooth vertical elements allows our approach to fill in plausible extensions of e.g. walls in case of (non-vertical) occlusions. It is also possible to explicitly detect non-vertical regions in the images, and to revert to more general stereo methods only in those areas. We demonstrate our method on several challenging stereo images of office environments.

关键词： Three dimensional displays Cameras Indoor environments Hafnium Dynamic programming Computational modeling image reconstruction

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