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检索条件"任意字段=International Conference on Parallel and Distributed Processing Techniques and Applications"

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Everything Everyway All at Once -Time Traveling Debugging for Stream processing applications 40

Everything Everyway All at Once -Time Traveling Debugging fo...

引用

40th IEEE international conference on Data Engineering, ICDE 2024

作者： Räth, Timo Schlegel, Marius Sattler, Kai-Uwe TU Ilmenau Ilmenau Germany

ISBN: (纸本)9798350317152

Debugging, evaluating, and optimizing stream processing applications is challenging due to continuous streams of input data and typically distributed and parallel execution environments. To address these issues, we present an approach for explorative debugging of stream processing pipelines that allows in-depth investigation of a pipeline's execution behavior and evolution. The time traveling debugger enables traveling back in time within the pipeline's execution history and thoroughly analyzing and retracing each fine-grained step. Any changes made to the pipeline's structure or parameters are captured based on provenance information and can be reviewed, compared, and analyzed with the provenance inspector to understand the impact of each alteration on the quality of the pipeline. © 2024 IEEE.

关键词： Program debugging

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Dynamic Software Updates for Accelerating Scientific Discovery

Dynamic Software Updates for Accelerating Scientific Discove...

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9th international conference on Computational Science

作者： Kim, Dong Kwan Song, Myoungkyu Tilevich, Eli Ribbens, Calvin J. Bohner, Shawn A. Virginia Tech Dept Comp Sci CHECS Blacksburg VA 24061 USA

ISBN: (纸本)9783642019692

distributed parallel applications often run for hours or even days before arriving to a result. In the case of such long-running programs, the initial requirements could change after the program has started executing. To shorten the time it takes to arrive to a result when running a, distributed computationally-intensive application, this paper proposes leveraging the power and flexibility of dynamic software. updates. In particular, to enable flexible dynamic software updates, we introduce a novel binary rewriting approach that is more efficient than the existing techniques. While ensuring greater flexibility in enhancing a running program for new requirements, our binary rewriting technique incurs Only negligible performance overhead. We validate our approach via, a case study of dynamically changing a parallel scientific simulation.

关键词： Dynamic Software Updates Time-to-Discovery Computationally-Intensive applications JVM HotSwap Bytecode Enhancement

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parallel image-based hemodynamic simulator

Parallel image-based hemodynamic simulator

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2nd international conference on Systems and Networks Communications, ICSNC 2007

作者： Garbey, Marc Hadri, Bilel Hilford, Victoria Karmonik, Christof Department of Computer Science University of Houston Houston TX United States Methodist Hospital Research Institute Houston TX United States

ISBN: (纸本)9780769529387

With cost effective distributed memory computer systems reaching high performances, it may become feasible in the near future to provide routinely reliable blood flow simulations during angiographic procedures to enhance standard medical imaging techniques. The long term goal of our work is to produce a fast parallel image base Navier-Stokes flow solver for these kinds of clinical procedures. To achieve such performance, our method relies on the proper combination of three techniques that are the L2 penalty method to deal with complex geometry, a level set method to extract the geometry of the arteries, and a fast scalable domain decomposition solver for the parallel processing of the discrete equations. We developed a web application with a database back-end to store both the original medical images and the results of these simulations. This will assist the endovascular surgeon by providing quickly blood flow indicators such as pressure or shear stresses at the wall of the artery, in addition to existing image analysis technique aimed at improving therapy. © 2007 IEEE.

关键词： Shear stress

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distributed localization of networked cameras

Distributed localization of networked cameras

引用

5th international conference on Informational processing in Sensor Networks

作者： Funiak, Stanislav Guestrin, Carlos Paskin, Mark Sukthankar, Rahul Carnegie Mellon Univ Pittsburgh PA 15213 USA Stanford Univ Stanford CA 15213 USA Int Res Ctr Bengaluru 560054 India

ISBN: (纸本)1595933344

Camera networks are perhaps the most common type of sensor network and are deployed in a variety of real-world applications including surveillance, intelligent environments and scientific remote monitoring. A key problem in deploying a network of cameras is calibration, i.e., determining the location and orientation of each sensor so that observations in an image can be mapped to locations in the real world. This paper proposes a fully distributed approach for camera network calibration. The cameras collaborate to track an object that moves through the environment and reason probabilistically about which camera poses are consistent with the observed images. This reasoning employs sophisticated techniques for handling the difficult nonlinearities imposed by projective transformations, as well as the dense correlations that arise between distant cameras. Our method requires minimal overlap of the cameras' fields of view and makes very few assumptions about the motion of the object. In contrast to existing approaches, which are centralized, our distributed algorithm scales easily to very large camera networks. We evaluate the system on a real camera network with 25 nodes as well as simulated camera networks of up to 50 cameras and demonstrate that our approach performs well even when communication is lossy.

关键词： sensor networks graphical models

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Collision Graph based Communication Reduction techniques for Mesh Networks 14

Collision Graph based Communication Reduction Techniques for...

引用

14th international conference on Computer applications in Industry and Engineering, CAINE 2001

作者： Surma, David R. Department of Computer and Information Sciences Indiana University South Bend South BendIN46634 United States

ISBN: (纸本)9781618395344

parallel systems are increasingly being used to meet the demands of today's high technology applications. While such systems provide decreased processing time they incur a degree of communication overhead that degrades their performance. To reduce this overhead, the static communication scheduling of message transmissions is considered. The compile-time determination of when nodes should transmit their messages is what is termed static communication scheduling. In addition, the routing of the messages will be addressed. This work begins with the tasks already allocated and uses the recently developed Collision Graph model to analyze the underlying message passing that occurs in mesh networks of both two and three dimensions. Using this model, determining an optimal schedule is found to be NP-Complete. Therefore, heuristics are used in designing efficient communication reduction algorithms. Emphasis is on creating techniques that will work on current multiprocessor systems with only minor, if any, modifications to existing router hardware. Experiments show a significant improvement over baseline approaches. © 2001 by the international Society for Computers and Their applications. All rights reserved.

关键词： Graph theory

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On construction of a visualization toolkit for MPI parallel programs in cluster environments

On construction of a visualization toolkit for MPI parallel ...

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19th international conference on Advanced Information Networking and applications, AINA 2005

作者： Li, Kuan-Ching Chang, Hsun-Chang Yang, Chao-Tung Sato, Liria Matsumoto Yang, Chung-Yuan Wu, Yin-Yi Pel, Mao-Yueh Liao, Hsiang-Kai Hsieh, Min-Chieh Tsai, Chia-Wen Parallel and Distributed Processing Center CSIM Dept. Providence University Shalu Taichung 433 Taiwan MPC Laboratory CSIE Dept. Tunghai University Taichung 407 Taiwan LASE Laboratory PCS Dept. University of Sao Paulo SP 05508-900 Brazil

ISBN: (纸本)0769522491

The low cost and wide availability of PC-based clusters have made them an excellent alternative to access supercomputing. However, while network of workstations may be readily available, there is an increasing need for performance tools that support these platforms, in order to achieve even higher performance. One of possible ways to increase performance is parallel program restructuring. It is introduced in this paper a toolkit to generate graphical charts for visualization of MPI parallel programs, reflecting to its execution over time, with the use of DP*Graph representation, parallel version of timing graph. In other words, parallel programs are shown through charts its sequential codes, dependencies and communication structures in a particular cluster system platform. Still in thispaper, it is discussed the implementation of this toolkit and present some experimental results obtained. © 2005 IEEE.

关键词： parallel processing systems

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A Case of parallel EEG Data processing upon a Beowulf Cluster

A Case of Parallel EEG Data Processing upon a Beowulf Cluste...

引用

international conference on parallel and distributed Systems (ICPADS)

作者： Yufeng Yao Jinyi Chang Kaijian Xia School of Computer Science and Engineering Changshu Institute of Technology Changsha Jiangsu China

Electroencephalogram (EEG) data processing applications have become routine tasks in both bioscience and neuroscience research, which are usually highly compute and data intensive. In this paper, we present a parallel method to analyze the huge EEG data with a Beowulf cluster. Through an example of the synchronization measurement of multiple neuronal populations, the procedure of exploiting the parallelism of EEG data processing applications to achieve speed-up has been detailed. The experimental results indicate that the execution efficiency of EEG data processing can be improved dramatically using parallel and distributed computing techniques even with inexpensive computing platform.

关键词： Electroencephalography Data processing distributed computing Application software Concurrent computing Neuroscience Bioinformatics parallel processing Local area networks Message passing

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RESOURCE DISCOVERY for QUERY processing in DATA GRIDS 22

RESOURCE DISCOVERY for QUERY PROCESSING in DATA GRIDS

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22nd international conference on parallel and distributed Computing and Communication Systems, PDCCS 2009

作者： El Samad, Mahmoud Morvan, Franck Hameurlain, Abdelkader Université Paul Sabatier 118 route de Narbonne Toulouse Cedex 9F-31062 France

ISBN: (纸本)9781615675777

Today, the resource discovery is a very hot topic in large scale and unstable Virtual Organizations VOs of a data grid. This paper proposes an efficient method for resource discovery based on the use of multiple distributed Hash Tables DHTs. The considered resources are the metadata (e.g. profile of data) describing data resources. Every DHT stores these metadata for each VO where every VO is dedicated to an application domain (e.g. biology, pathology). We define two levels for metadata discovery: local discovery (i.e. intra-VO) and global discovery (i.e. inter-VO). The intra-VO discovery is a classical discovery based on DHTs. The inter-VO discovery is performed through a simple but original addressing system which allows the interconnection between all the VOs. The main advantages of our method are applying the principle of data locality during the metadata discovery phase and enabling a robust inter-VO discovery in presence of system instability. We evaluate our proposal by simulations showing its feasibility and benefits. Copyright © (2009) by the international Society for Computers and Their applications. All rights reserved.

关键词： Metadata

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Hyaline: A Transparent Distribwuted Computing Framework for CUDA 5

Hyaline: A Transparent Distribwuted Computing Framework for ...

引用

5th IEEE international conference for Convergence in Technolog, I2CT 2019

作者： Jain, Akshat Kazi, Owais Joshi, Raviraj Basantwani, Shraddha Bang, Yogita Khengare, Rahul PICT Computer Engineering Pune India IIT Computer Science Madras India

ISBN: (纸本)9781538680759

The GPU usually handles the homogenous data parallel work, by taking advantage of its massive number of cores. In most of the applications, we use CUDA programming for utilizing the power of GPU. In data intensive high computational applications like neural networks, utilizing the GPU on a single machine is time consuming. Instead if multiple GPUs are used in a network the amount of time required will be significantly reduced. Traditionally to enable a set of program to be run in a distributed environment, programmer has to accordingly design components to make his system dynamic and resilient to changes in number of systems in cluster, which is a daunting task. This work distribution can be a poor solution as it may underutilize the GPUsIn our approach, we developed a framework which transparently distributes data parallel kernels across multiple GPUs in a distributed network. The programmer is responsible for developing a single data parallel kernel in CUDA while the framework automatically distributes the workload across an arbitrary set of CUDA enabled GPUs. Depending on current workload on GPUs and the amount of data to be processed optimal distribution is done. The goal is to maximally utilize the available resources with minimal programming complexity. The systems not compatible with CUDA can also utilize our solution. We expect our framework to reduce the processing time along with simplifying the task of programmers. © 2019 IEEE.

关键词： parallel programming

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An Implementation Method of parallel Finite Element Computation Based on Overlapping Domain Decomposition

An Implementation Method of Parallel Finite Element Computat...

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2nd international conference on High Performance Computing and applications

作者： Zhang, Jianfei Zhang, Lei Jiang, Hongdao Hohai Univ Sch Civil Engn Nanjing 210098 Peoples R China China Inst Water Resources & Hydropower Res Beijing 100044 Peoples R China

ISBN: (纸本)9783642118418

An implementation method of parallel finite element computation based on overlapping domain decomposition was presented to improve the parallel computing efficiency of finite element and lower the cost and difficulty of parallel programming. By secondary processing the nodal partition obtained by using Metis, the overlapping domain decomposition of finite element mesh was gotten. Through the redundancy computation of overlapping element, finite element governing equations could be parallel formed independently. And the uniform distributed block storage could be achieved conveniently. The interface to the DMSR data format was developed to meet the need of Aztec parallel solution. And the solver called the iterative solving subroutine of Aztec directly. This implementation method reduced the change of the existed serial program to a great extent. So the main frame of finite element computation was kept. Tests show that this method can achieve high parallel computing efficiency.

关键词： parallel programming

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