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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing"

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Performance problems online detection in cloud computing systems via analyzing request execution paths

Performance problems online detection in cloud computing sys...

引用

Workshop on Proactive Failure Avoidance, Recovery, and Maintenance

作者： Mi, Haibo Wang, Huaimin Yin, Gang Cai, Hua Zhou, Qi Sun, Tingtao National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha China Computing Platform Alibaba Cloud Computing Company Hangzhou China

ISBN: (纸本)9781457703751

It is quite a headache for developers to online detect performance problems in large-scale cloud computing systems. The behavior and the hidden connections among the huge amount of runtime request execution paths in cloud computing systems usually contain useful information for performance problem detection. In this paper, we propose an approach to rapidly diagnose the source of performance degradation in large-scale non-stop cloud computing systems. The approach first groups the user requests into categories with a fast clustering algorithm;then applies the principal components analysis to extract the primary methods;finally compares the normal and abnormal behaviors of the primary methods to localize the main cause of performance problems. We conduct extensive experiments over a real-world enterprise system providing services for the public. The results show that our approach can locate the prime causes of performance problems accurately and efficiently.1 © 2011 IEEE.

关键词： Cloud computing

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Wi-FLIP: A wireless smart camera based on a focal-plane low-power image processor

Wi-FLIP: A wireless smart camera based on a focal-plane low-...

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ACM/IEEE International conference on distributed Smart Cameras, ICDSC

作者： Jorge Fernández-Berni Ricardo Carmona-Galán Gustavo Liñán-Cembrano Ákos Zarándy Ángel Rodríguez-Vázquez Institute of Microelectronics of Seville (IMSE-CNM) Sevilla Spain Computer and Automation Research Institute (MTA-SZTAKI) Budapest Hungary

This paper presents Wi-FLIP, a vision-enabled WSN node resulting from the integration of FLIP-Q, a prototype vision chip, and Imotel, a commercial WSN platform. In Wi-FLIP, image processing is not only constrained to the digital domain like in conventional architectures. Instead, its image sensor - the FLIP-Q prototype - incorporates pixel-level processing elements (PEs) implemented by analog circuitry. These PEs are interconnected, rendering a massively parallel SIMD-based focal-plane array. Low-level image processing tasks fit very well into this processing scheme. They feature a heavy computational load composed of pixel-wise repetitive operations which can be realized in parallel with moderate accuracy. In such circumstances, analog circuitry, not very precise but faster and more area- and power-efficient than its digital counterpart, has been extensively reported to achieve better performance. The Wi-FLIP's image sensor does not therefore output raw but pre-processed images that make the subsequent digital processing much lighter. The energy cost of such pre-processing is really low - 5.6mW for the worst-case scenario. As a result, for the configuration where the Imote2's processor works at minimum clock frequency, the maximum power consumed by our prototype represents only the 5.2% of the whole system power consumption. This percentage gets even lower as the clock frequency increases. We report experimental results for different algorithms, image resolutions and clock frequencies. The main drawback of this first version of Wi-FLIP is the low frame rate reachable due to the non-standard GPIO-based FLIPQ-to-Imote2 interface.

关键词： Clocks Wireless sensor networks Power demand image resolution Prototypes Arrays

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More Efficient Executions of Monte Carlo Fusion Codes by Means of Montera: The ISDEP Use Case

More Efficient Executions of Monte Carlo Fusion Codes by Mea...

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Euromicro conference on parallel, distributed and Network-Based processing

作者： M. Rodríguez-Pascual A.J. Rubio-Montero R. Mayo A. Bustos F. Castejón I.M. Llorente CIEMAT Madrid Madrid Spain Laboratorio Nacional de Fusion Asociación EURATOM/CIEMAT Madrid Madrid Spain *** Madrid Madrid Spain

ISDEP (Integrator of Stochastic Differential Equations for Plasmas) is a Monte Carlo code that solves the plasma dynamics in a fusion device and perfectly scales on distributed computing platforms. Montera is a recent framework developed for achieving Grid efficient executions of Monte Carlo applications, as ISDEP is. In this work, the improvement of performing the calculations of ISDEP with Montera, which rise up to 34.9%, is shown as well as an analysis on the implications it could have, which aim to show to the fusion research community the benefits of using Montera.

关键词： Plasmas Monte Carlo methods Dynamic scheduling Trajectory Mathematical model Equations Heuristic algorithms

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Ultra-high speed real-time 4D display system installed in ultra-high speed parallel OCT system at a volume rate of 12 volumes/sec

Ultra-high speed real-time 4D display system installed in ul...

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conference on Optical Coherence Tomography and Coherence Domain Optical methods in Biomedicine XV

作者： Ohbayashi, K. Choi, D. Hiro-oka, H. Kubota, A. Ohno, T. Ikeda, R. Shimizu, K. Kitasato Univ Grad Sch Med Sci Sagamihara Si 2520373 Japan

ISBN: (纸本)9780819484260

Optical coherence tomography (OCT) has become a promising diagnostic method in many medical fields. Non-invasive real-time optical biopsy of internal organs is one of the most attractive applications of OCT enabling in-situ diagnostic of cancer in its early stage, i.e. optical biopsy. For the application, faster OCT methods are required to reduce the inspection time and motion artifacts in images. A criterion to satisfy the purpose is an endoscopic-OCT method capable to display volumetric tomography continuously in real-time at a rate of video movie like conventional endoscopes. In our previous work, we demonstrated ultra-high speed OCT at an A-scan rate of 60 MHz. However, movies were rendered after the data acquisition. In this work, we have developed an ultra-fast data processing system, installed it in the ultra-high speed OCT system, and enabled real time display of various 3D tomography images without limitation of diagnostic time, i.e. 4D OCT imaging, at an A-scan rate, B-scan rate and volume rate of 10 MHz, 4 kHz and 12 volumes/sec, respectively. Various image presentations in real-time are demonstrated such as continuous rendered 3D imaging and continuous 2D-slice scanning 3D imaging.

关键词： Optical coherence tomography OCT ultra-high speed OCT endoscopic OCT optical biopsy

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A systemc TLM framework for distributed simulation of complex systems with unpredictable communication

A systemc TLM framework for distributed simulation of comple...

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conference on Design and Architectures for Signal and image processing

作者： Julien Peeters Nicolas Ventroux Tanguy Sassolas Lionel Lacassagne LIST Embedded Computing Laboratory CEA Gif-sur-Yvette France

Increasingly complex systems need parallelized simulation engines. In the context of SystemC simulation, existing proposals require predicting communication in the simulated system. However, this is often unpredictable. In order to deal with unpredictable systems, this paper presents a parallelization approach using asynchronous communication without modification of the SystemC simulation engine. Simulated system model is cut up and distributed across separate simulation engines, each part being evaluated in parallel of others. Functional consistency is preserved thanks to the simulated system write exclusive memory access policy while temporal consistency is guaranteed using explicit synchronization. Experimental results show up a speed-up up to 13× on 16 processors.

关键词： Synchronization Load modeling Adaptation models Hardware Context Engines Program processors

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parallel Automatic Registration of Large Scale Microscopic images on Multiprocessor CPUs and GPUs

Parallel Automatic Registration of Large Scale Microscopic I...

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

作者： Lee Cooper Kun Huang Manuel Ujaldon Center of Comprehensive Informatics Emory University Atlanta GA USA Biomedical Informatics Department Ohio State Uinversity Columbus OH USA Computer Architecture Department University of Malaga Malaga Spain

During the present decade, emerging architectures like multicore CPUs and graphics processing units (GPUs) have steadily gained popularity for their ability to deploy high computational power at a low cost. In this paper, we combine parallelization techniques on a cooperative cluster of multicore CPUs and multisocket GPUs to apply their joint computational power to an automatic image registration algorithm intended for the analysis of high-resolution microscope images. Registration methods pose a computational challenge within the biomedical field due to the large size of microscope image data sets, which typically extend to the Terabyte scale. We analyze this application to identify those parts which are more favorable to the CPU and GPU execution models and decompose the process accordingly. Performance results are presented for two sets of images: mouse placenta (16K × 16K pixels) and mouse mammary tumor (23K × 62K pixels). Execution times are shown on different multi-node, multi-socket and multi-core configurations to provide performance insights about the most effective approach.

关键词： Graphics processing unit Microscopy Multicore processing Sockets Random access memory parallel processing Hardware

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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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Demonstration of a low power image processing system using a SCAMP3 vision chip

Demonstration of a low power image processing system using a...

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ACM/IEEE International conference on distributed Smart Cameras, ICDSC

作者： Stephen J. Carey David R. W. Barr Piotr Dudek School of Electrical and Electronics Engineering University of Manchester UK

A low power vision system has been developed incorporating the SCAMP3 pixel-parallel processor array vision chip. A test algorithm to detect loitering targets has shown an average power consumption of

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Fast double-parallel image processing based on FPGA

Fast double-parallel image processing based on FPGA

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IEEE International conference on Vehicular Electronics and Safety (ICVES)

作者： Ye Li Qingming Yao Bin Tian Wencong Xu State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China School of Mechanical Electrical and Information Engineering Shandong University Weihai China

Due to FPGA's flexibility and parallelism, it is popular for accelerating image processing. In this paper, a double-parallel architecture based on FPGA has been exploited to speed up median filter and edge detection tasks, which are essential steps during image processing. The double-parallel scheme includes an image-level parallel and an operation-level parallel. The image-level parallel is a high-level parallel which divides one image into different parts and processes them concurrently. The operation-level parallel, which is embedded in each image-level parallel thread, fully explores every parallel part inside the concrete algorithms. The corresponding design is based on a DE2 Development Board which contains a CYCLONE II FPGA device. Meanwhile, the same task has also been implemented on PC and DSP for performance comparison. Despite the fact that operating frequencies of used PC and DSP are much higher than FPGA's, FPGA costs less time per computed image than both of them. By taking advantage of the double-parallel technique, the speed/frequency ratio of FPGA is 202 times faster than PC and 147 times faster than DSP. Finally, a detailed discussion about different platforms is conducted, which analyzes advantages and disadvantages of used computing platforms. This paper reveals that the proposed double-parallel scheme can dramatically speed up image processing methods even on a low-cost FPGA platform with low frequency and limited resources, which is very meaningful for practical applications.

关键词： image edge detection Field programmable gate arrays Digital signal processing Hardware Kernel Detectors

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Ball Detection with the Aim of Corner Event Detection in Soccer Video

Ball Detection with the Aim of Corner Event Detection in Soc...

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IEEE International Symposium on parallel and distributed processing with Applications Workshops (ISPAW)

作者： J. Hossein-Khani H. Soltanian-Zadeh M. Kamarei O. Staadt CIPCE Department of Electrical and Computer Engineering University of Tehran Tehran Iran Faculty of Computer Science University of Rostock Rostock Germany

In the present work, automatic corner detection in soccer games based on image features (e.g., object-based features) has been studied. For this purpose, a framework has been proposed that consists of five steps. This paper mainly focuses on the first three steps and specially ball detection step. Ball position on the field plays an important role in determining which event has occurred in the game. Therefore, it is necessary to detect exact position of the ball in the playfield and then track it. Ball trajectory that can be obtained via tracking is useful for identifying and detecting main events of soccer games. In these three steps, the most important processing that has been applied to the images is based on image segmentation to detect playfield, field lines, and ball. Cleaning morphological method is applied to detect the ball. This method is real-time and automatic, it yields superior results in comparison with other common methods such as Template Matching and Circular Hough Transform (CHT). By applying the proposed method, only one candidate for the ball position is obtained and non-ball candidates are removed, hence, it is more reliable than other methods. The results of the proposed method are compared with those of CHT. They illustrate that the proposed method is fast, effective, and reliable.

关键词： image color analysis Streaming media Feature extraction Shape Games Tracking Pixel

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