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Real-Time Patient Table Removal in CT Images 1

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5th international conference on Health Information Science (HIS)

作者： Chen, Luming Wu, Shibin Zhang, Zhicheng Yu, Shaode Xie, Yaoqin Zhang, Hefang Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China XiAn Technol Univ Coll Elect & Informat Engn Xian 710021 Peoples R China Univ Chinese Acad Sci Shenzhen Coll Adv Technol Shenzhen 518055 Peoples R China

ISBN: (数字)9783319483351

ISBN: (纸本)9783319483351;9783319483344

As a routine tool for screening and examination, CT plays an important role in disease detection and diagnosis. Real-time table removal in CT images becomes a fundamental task to improve readability, interpretation and treatment planning. Meanwhile, it makes data management simple and benefits information sharing and communication in picture archiving and communication system. In this paper, we proposed an automated framework which utilized parallel programming to address this problem. Eight full-body CT images were collected and analyzed. Experimental results have shown that with parallel programming, the proposed framework can accelerate the patient table removal task up to three times faster when it was running on a personal computer with four-core central processing unit. Moreover, the segmentation accuracy reaches 99% of Dice coefficient. the idea behind this approach refreshes many algorithms for real-time medical image processing without extra hardware spending.

关键词： Real-time parallel programming Image segmentation Health information science

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12th international conference on Beyond Databases, architectures and Structures, BDAS 2016

12th International Conference on Beyond Databases, Architect...

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12th international conference on Beyond Databases, architectures and Structures, BDAS 2016

ISBN: (纸本)9783319340982

the proceedings contain 57 papers. the special focus in this conference is on Artifical Intelligence, Data Mining, Knowledge Discovery, algorithms for Efficient Data processing and Data Warehousing. the topics include: Interactive visualization of big data;reduction of readmissions to hospitals based on actionable knowledge discovery and personalization;performing and visualizing temporal analysis of large text data issued for open sources;influence of outliers introduction on predictive models quality;methods for selecting nodes for maximal spread of influence in recommendation services;memetic neuro-fuzzy system with differential optimisation;new rough-neuro-fuzzy approach for regression task in incomplete data;improvement of precision of neuro-fuzzy system by increase of activation of rules;rough sets in multicriteria classification of national heritage monuments;inference rules for fuzzy functional dependencies in possibilistic databases;the evaluation of map-reduce join algorithms;the design of the efficient theta-join in map-reduce environment;non-recursive approach for sort-merge join operation;estimating costs of materialization methods for SQL;performance aspect of the in-memory databases accessed via JDBC;comparison of the behaviour of local databases and databases located in the cloud;scalable distributed two-layer datastore providing data anonymity;coordination of parallel tasks in access to resource groups by adaptive conflictless scheduling;conflictless task scheduling using association rules;distributed computing in monotone topological spaces;new similarity measure for spatio-temporal OLAP queries;enhancing concept extraction from polish texts with rule management and a diversified classification committee for recognition of innovative internet domains.

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Modeling, Programming and Performance Analysis of Automotive Environment Map Representations on Embedded GPUs 18

Modeling, Programming and Performance Analysis of Automotive...

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18th IEEE international High Level Design Validation and Test Workshop (HLDVT)

作者： Fickenscher, Jorg Reiche, Oliver Schlumberger, Jens Hannig, Frank Teich, Juergen Friedrich Alexander Univ Erlangen Nurnberg FAU Dept Comp Sci Hardware Software Codesign Erlangen Germany

ISBN: (纸本)9781509042708

Future Advanced Driver Assistance Systems (ADAS) require the continuous computation of detailed maps of the vehicle's environment. Due to the high demand of accuracy and the enormous amount of data to be fused and processed, common architectures used today, like single-core processors in automotive Electronic Control Units (ECUs), do not provide enough computing power. Here, emerging embedded multi-core architectures are appealing such as embedded Graphics processing Units (GPUs). In this paper, we (a) identify and analyze common subalgorithms of ADAS algorithms for computing environment maps, such as interval maps, for suitability to be parallelized and run on embedded GPUs. From this analysis, (b) performance models are derived on achievable speedups with respect to sequential single-core CPU implementations. (c) As a third contribution of this paper, these performance models are validated by presenting and comparing a novel parallelized interval map GPU implementation against a parallel occupancy grid map implementation. For both types of environment maps, implementations on an Nvidia Tegra K1 prototype are compared to verify the correctness of the introduced performance models. Finally, the achievable speedups with respect to a single-core CPU solution are reported. these range from 3x to 2 7 5x for interval and grid map computations.

关键词： Graphics processing unit

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10th international Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, MEMICS 2015

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10th international Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, MEMICS 2015

ISBN: (纸本)9783319298160

the proceedings contain 13 papers. the special focus in this conference is on Mathematical and Engineering Methods in Computer Science. the topics include: Programming support for future parallel architectures;flexible interpolation for efficient model checking;understanding transparent and complicated users as instances of preference learning for recommender systems;span-program-based quantum algorithms for graph bipartiteness and connectivity;fitting aggregation operators;practical exhaustive generation of small multiway cuts in sparse graphs;self-adaptive architecture for multi-sensor embedded vision system;exceptional configurations of quantum walks with grover’s coin;performance analysis of distributed stream processing applications through colored petri nets;GPU-accelerated real-time mesh simplification using parallel half edge collapses;classifier ensemble by semi-supervised learning;the challenge of increasing safe response of antivirus software users and weak memory models as LLVM-to-LLVM transformations.

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Performance of a Real-time Multipurpose 2-Dimensional Clustering Algorithm Developed for the ATLAS Experiment 5

Performance of a Real-time Multipurpose 2-Dimensional Cluste...

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5th international conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Gkaitatzis, Stamatios Aristotle Univ Thessaloniki Thessaloniki 54124 Greece

ISBN: (纸本)9781467396806

In this paper the performance of the 2D pixel clustering algorithm developed for the Input Mezzanine card of the ATLAS Fast TracKer system is presented. Fast TracKer is an approved ATLAS upgrade that has the goal to provide a complete list of tracks to the ATLAS High Level Trigger for each level-1 accepted event, at up to 100 kHz event rate with a very small latency, in the order of 100 mu s. the Input Mezzanine card is the input stage of the Fast TracKer system. Its role is to receive data from the silicon detector and perform real time clustering, thus to reduce the amount of data propagated to the subsequent processing levels with minimal information loss. We focus on the most challenging component on the Input Mezzanine card, the 2D clustering algorithm executed on the pixel data. We compare two different implementations of the algorithm. the first is one called the ideal one which searches clusters of pixels in the whole silicon module at once and calculates the cluster centroids exploiting the whole available information, included the precise sharing of charge produced by the particle between contiguous pixels of the cluster. the second one uses a sliding window technique to identify clusters of contiguous pixels, one at a time. In addition, a simplified centre of mass is calculated as the center of a bounding box which contains the cluster. the size of the window sets a limit to the maximum cluster that can be found, so clusters can be split if their sizes exceeds the window one. We show that the simplified implementation saves a large amount of hardware resources and has the equivalent performance for the use in the Fast TracKer processor. Finally, we describe an event display that is a powerful diagnostic/monitoring tool used to understand in detail the performance of the algorithm, also used during the data taking.

关键词： Clustering Image processing parallel processing Trigger circuits Field programmable gate arrays Pixel detectors

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Performance analysis of Δ-stepping algorithm on CPU and GPU 47

Performance analysis of Δ-stepping algorithm on CPU and GPU

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47th international Youth School-conference "Modern Problems in Mathematics and its Applications", MPMA 2016

作者： Lesnikov, Dmitry Chernoskutov, Mikhail Ural Federal University Yekaterinburg Russia Krasovskii Institute of Mathematics and Mechanics Yekaterinburg Russia

Δ-stepping is an algorithm for solving single source shortest path problem. It is very efficient on a large class of graphs, providing nearly linear time complexity in sequential implementation, and can be parallelized. However, this algorithm requires some tuning and has unpredictable performance behaviour on systems with different parallel architectures. In this paper we describe details of implementation of this algorithm on CPU and GPU. Performing numerous tests we studied scalability of algorithms on CPU and GPU and compared performance for different Δ parameter. We show that performance results for CPU and GPU varies for different delta. Also, we noticed that GPU performance are stable for some different delta values. Our result shows how to choose Δ for achieving best performance for tested graphs. Copyright © by the paper's authors.

关键词： Graphics processing unit

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Towards a Smart Selection of Resources for Low-energy Multimedia processing

Towards a Smart Selection of Resources for Low-energy Multim...

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2nd international conference on Cloud Computing Technologies and Applications (CloudTech)

作者： Mahmoudi, Sidi Ahmed Univ Mons Fac Engn Comp Sci Dept 20 Pl Parc Mons Belgium

ISBN: (纸本)9781467388948

Today, one can find images and videos everywhere, they can come from cameras, mobile phones or from other devices. these images and videos are used to illustrate different objects in a large number of situations (airports, hospitals, public areas, sport events, etc.). this makes the task of processing images and videos a necessary tool that can be used for various domains related to computer vision. the performance of these algorithms have been so reduced due to their high intensive computation and energy consumption. In this work, we propose a new framework that allows users to select in a smart and efficient way the computing units (CPU or/and GPU) in case of processing single image, multiple images, multiple videos or single video in real time. this framework enables to affect the CPU or/and GPU units for calculation depending on the type of media to process and the algorithm complexity. the framework provides several image and video functions on GPU, such as silhouette extraction, points of interest extraction, edges detection, sparse and dense optical flow estimation. these functions are exploited in different applications such as vertebra segmentation in X-ray and MR images, gaze estimation, event detection and localization in real time. Experimental results have been obtained by applying the framework for different use case applications showing a speedup ranging from 5 to 116 x, by comparison with sequential CPU implementations. In addition to these performance, the parallel and heterogeneous implementation offered lower power consumption as a result for the fast treatment.

关键词： GPU Heterogeneous architectures Image and video processing Medical imaging Motion tracking

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the Performance Evaluation of the Java Implementation of Graph500 11th

The Performance Evaluation of the Java Implementation of Gra...

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11th international conference on parallel processing and Applied Mathematics (PPAM)

作者： Ryczkowska, Magdalena Nowicki, Marek Bala, Piotr Nicolaus Copernicus Univ Fac Math & Comp Sci Chopina 12-18 PL-87100 Torun Poland Univ Warsaw Interdisciplinary Ctr Math & Computat Modeling Pawinskiego 5a PL-02106 Warsaw Poland

ISBN: (纸本)9783319321523;9783319321516

Graph-based computations are used in many applications. Increasing size of analyzed data and its complexity make graph analysis a challenging task. In this paper we present performance evaluation of Java implementation of Graph500 benchmark. It has been developed with the help of the PCJ (parallel Computations in Java) library for parallel and distributed computations in Java. PCJ is based on a PGAS (Partitioned Global Address Space) programming paradigm, where all communication details such as threads or network programming are hidden. In this paper, we present Java implementation details of first and second kernel from Graph500 benchmark. the results are compared with the existing MPI implementations of Graph500 benchmark, showing good scalability of PCJ library.

关键词： High performance computing Graph processing PGAS parallel and distributed computation Performance evaluation parallel graph algorithms Java

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A Comparison of Accelerator architectures for Radio-Astronomical Signal-processing algorithms

A Comparison of Accelerator Architectures for Radio-Astronom...

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international conference on parallel processing (ICPP)

作者： John W. Romein ASTRON (Netherlands Institute for Radio Astronomy) Postbus 2 Dwingeloo The Netherlands

ISBN: (纸本)9781509028245

In this paper, we compare a wide range of accelerator architectures (GPUs from AMD and NVIDIA, the Xeon Phi, and a DSP), by means of a signal-processing pipeline that processes radio-telescope data. We discuss the mapping of the algorithms from this pipeline to the accelerators, and analyze performance. We also analyze energy efficiency, using custom-built, microcontroller-based power sensors that measure the instantaneous power consumption of the accelerators, at millisecond time scale. We show that the GPUs are the fastest and most energy efficient accelerators, and that the differences in performance and energy efficiency are large.

关键词： Receivers Pipelines Kernel Digital signal processing Finite impulse response filters Computer architecture Instruction sets

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Performance Analysis of Optical Balanced Coherent Detection Based on an Acousto-Optic Deflection System 5th

Performance Analysis of Optical Balanced Coherent Detection ...

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5th international conference on Electronics, Communications and Networks (CECNet)

作者： Jiang, Hong-Yan He, Ning Liao, Xin Guilin Univ Elect Technol Sch Informat & Commun Guilin Peoples R China

ISBN: (纸本)9789811007408;9789811007385

Based on the principle of acousto-optic (AO) diffraction, the mechanism of acousto-optic deflection for frequency measurement and the noise characteristics of balanced detection in a coherent system are analyzed theoretically. For signal to noise ratio (SNR) improvement and multiple simultaneous signals parallel processing in acousto-optic signals processing environment, a test platform for frequency measurement is established to discuss the method of SNR improvement while the ability of signals detection and frequency resolution are tested. In the operational bandwidth, the system using acousto-optic effect and balanced coherent detection can improve the output SNR to some extent. Experiments have shown that a balanced coherent configuration has 5 dB improvements in output SNR over a single-detector coherent configuration, and frequency resolution of the system is less than 0.1 MHz.

关键词： Acousto-optic deflection Optical coherence Balanced detection Multiple signals processing Frequency resolution

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