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检索条件"任意字段=2nd International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering"

共 1401 条记录，以下是141-150 订阅

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Fast 3D Structure Localization in Medical Volumes using CUDA-enabled GPUs

Fast 3D Structure Localization in Medical Volumes using CUDA...

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2nd IEEE international conference on parallel, distributed and grid computing (PDGC)

作者： Vaswani, Sharan Thota, Rahul Vydyanathan, Nagavijayalakshmi Kale, Amit Siemens Corp Res & Technol Bangalore Karnataka India

ISBN: (纸本)9781467329255;9781467329224

Effective and fast localization of anatomical structures is a crucial first step towards automated analysis of medical volumes. In this paper, we propose an iterative approach for structure localization in medical volumes based on the adaptive bandwidth mean-shift algorithm for object detection (ABMSOD). We extend and tune the ABMSOD algorithm, originally used to detect 2D objects in non-medical images, to localize 3D anatomical structures in medical volumes. For fast localization, we design and develop optimized parallel implementations of the proposed algorithm on multi-cores using OpenMP, and on GPUs using CUDA. We evaluate the quality, performance and scalability of the proposed algorithm on Computed Tomography (CT) volumes for various structures.

关键词： localization medical image processing GPGPU computing CUDA

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Image distribution mechanisms in large scale cloud providers

Image distribution mechanisms in large scale cloud providers

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2nd IEEE international conference on cloud computing Technology and Science, cloudCom 2010

作者： Wartel, Romain Cass, Tony Moreira, Belmiro Roche, Ewan Guijarro, Manuel Goasguen, Sebastien Schwickerath, Ulrich Geneva Switzerland Clemson University School of Computing SC United States

ISBN: (纸本)9780769543024

This paper presents the various mechanisms for virtual machine image distribution within a large batch farm and between sites that offer cloud computing services. The work is presented within the context of the Large Hadron Collider computing grid (LCG), it has two main goals. First it aims at presenting the CERN specific mechanisms that have been put in place to test the pre-staging of virtual machine images within a large cloud infrastructure of several hundred physical hosts. Second it introduces the basis of a policy for trusting and distributing virtual machine images between sites of the LCG. Finally experimental results are shown for the distribution of a 10 GB virtual machine image distributed to over 400 physical nodes using a binary tree and a BitTorrent algorithm. Results show that images can be pre-staged within 30 minutes. © 2010 IEEE.

关键词： Binary trees

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An Evaluation of CUDA-enabled Virtualization Solutions

An Evaluation of CUDA-enabled Virtualization Solutions

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2nd IEEE international conference on parallel, distributed and grid computing (PDGC)

作者： Vinaya, M. S. Vydyanathan, Nagavijayajakshmi Gajjar, Mrugesh Int Inst Infonnat Technol Bangalore Karnataka India Siemens Corp Res & Technol Bangalore Karnataka India

ISBN: (纸本)9781467329255;9781467329224

Virtualization, as a technology that enables easy and effective resource sharing with a low cost and energy footprint, is becoming increasingly popular not only in enterprises but also in high performance computing. Applications with stringent performance needs often make use of graphics processors for accelerating their computations. Hence virtualization solutions that support GPU acceleration are gaining importance. This paper performs a detailed evaluation of three frameworks: rCUDA, gVirtuS and Xen, which support GPU acceleration through CUDA, within a virtual machine. We describe the architectures of these three solutions and compare and contrast them in terms of their fidelity, performance, multiplexing and interposition characteristics.

关键词： virtualization gpgpu computing cuda gpu virtualization many-core computing

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Trust-based resource allocation and evaluation of workflows in distributed computing environments

Trust-based resource allocation and evaluation of workflows ...

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international conference on Software Technology and engineering

作者： Spitz, Stefan Bök, Patrick-Benjamin Tüchelmann, York Department of Electrical Engineering and Information Sciences Research Group Integrated Information Systems Bochum Germany

ISBN: (纸本)9781424486656

An optimal resource allocation is desired to increase the efficiency of systems processing business or scientific workflows. These systems include the processing of workflows in distributed computing environments such as grid or cloud computing. Current approaches used in this systems consider QoS-requirements as quality, speed or costs in the resource allocation process and just select the resources that satisfy these requirements. However, the selection of a resource should not be based solely on whether a resource meets the QoS-requirements or not, because it does not imply that a task is processed satisfactory by the selected resource according to its content. To evaluate resources regarding this aspect, trust models can be used. But current trust models are not specifically designed to model trust in distributed computing environments, hence handling the dynamics of business or scientific workflows that constantly change their requirements and conditions. In this paper, we present approaches which improve current trust models according to the problems mentioned. Thereby, the degree of automation in the trust evaluation process will be increased as well. Finally, in combination with an adjusted trust level workflow, the presented approach allows an optimal resource allocation for grid or cloud computing service providers. © 2010 IEEE.

关键词： cloud computing

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A Component Based Graphical parallel Programming Approach for Numerical Simulation Development 2

A Component Based Graphical Parallel Programming Approach fo...

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2nd IEEE international conference on High Performance and Smart computing (IEEE HPSC)

作者： Liao Li Mo Zeyao Zhang Aiqing Inst Appl Phys & Computat Math CAEP Software Ctr High Performance Numer Simulat High Performance Comp Ctr Beijing Peoples R China

ISBN: (纸本)9781509024032

Building massively parallel numerical simulations is not easy due to lasting changes of parallel programming models and various software technologies needed. We develop a component based graphical parallel programming approach to lower the difficulties of coding applications in scientific and engineering computing and support rapid development of large scale simulations basing on a domain specific framework. parallel applications can be constructed simply by configuring components and assembling them in predefined flowcharts interactively. Large part of codes is auto generated from the graphical configuration for an application. The approach facilitates the rapid design and development of parallel numerical simulations by shielding many knowledge and technologies required from domain experts. Real applications demonstrate that the approach for developing complex numerical is both practical and efficient.

关键词： scientific computing domain-specific framework component-based programming parallel application GUI

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Monte Carlo Optimisation Auto-Tuning on a Multi-GPU Cluster

Monte Carlo Optimisation Auto-Tuning on a Multi-GPU Cluster

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2nd IEEE international conference on parallel, distributed and grid computing (PDGC)

作者： Paukste, Andrius Vilnius Univ Fac Math & Informat Vilnius Lithuania

ISBN: (纸本)9781467329255

In this paper we investigate Monte Carlo optimisation of the fitness function on a multi-GPU cluster. Our main goal is to develop auto-tuning techniques for the GPU cluster. Monte Carlo or random sampling is a technique to optimise a fitness function by giving random values to function parameters. When execution of the fitness function requires a high amount of computational power Monte Carlo sampling becomes both very time and computational power consuming. A developer who is not familiar with the application, hardware, and the CUDA runtime cannot determine the optimal execution parameters. This makes GPU auto-tuning well suited to achieving better performance and reducing computing time. Finally, we compare the execution time with the consequent CPU as well as with multi-core CPU implementation.

关键词： GPU computing high performance computing Monte Carlo optimisation financial risks

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Techniques for Task Scheduling in cloud and Fog Environment: A Survey 2nd

Techniques for Task Scheduling in Cloud and Fog Environment:...

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2nd international conference on Futuristic Trends in Networks and computing Technologiess, FTNCT 2019

作者： Singh, Raj Mohan Awasthi, Lalit Kumar Sikka, Geeta Department of Computer Science and Engineering Dr B R Ambedkar National Institute of Technology Jalandhar India

ISBN: (纸本)9789811544507

computing paradigms have evolved over the years in the form of parallel, distributed, grid, cloud, and fog computing. Scheduling is a fundamental issue in distributed environments where several tasks compete among available resources. Inefficient scheduling mechanisms lead to underutilization and overutilization of resources. Scheduling algorithm should strive to maximize performance and optimize crucial parameters for improving the user QoS (Quality of Service). There is a pressing need to improve resource utilization for increasing the scheduling efficiency. A number of techniques including heuristic, metaheuristic, as well as hybrid approaches have been proposed in the literature to find near-optimum solutions for task scheduling. This paper presents a survey of various scheduling techniques along with the associated metrics in cloud and fog computing. Comparison with state of the art techniques is studied and limitations discussed in order to device more efficient scheduling techniques in future. Finally, future directions related to research on task scheduling are discussed. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Fog

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Simple parallel Genetic Algorithm Using cloud computing

Simple Parallel Genetic Algorithm Using Cloud Computing

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2nd international conference on Frontiers of Manufacturing and Design Science (ICFMD 2011)

作者： Zhao Jian Feng Zeng Wen Hua Li Guang Ming Liu Min Xiamen Univ Dept Cognit Sci Xiamen 361005 Fujian Peoples R China

ISBN: (纸本)9783037852828

cloud computing is a novel parallel platform, this paper proposed a kind of simple parallel genetic algorithm (PGA) using cloud computing called SMRPGA. Comparing with the traditional PGAs using high performance computers (HPC), cluster or grid, SMRPGA is simple and easy to be implemented. Another advantage is that PGA using cloud computing is easy to be extend to larger-scale, which is very useful for solving the time-consuming problems. A prototype is implemented based on Hadoop, which is an open source cloud computing. The result of running two benchmark functions showed that the speed-up of PGA using cloud computing is not obvious considering the long communication time and it is suitable to solve the time-consuming problems.

关键词： cloud computing parallel genetic algorithm MapReduce

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Performance evaluation of Intel Xeon E5-2600 family cluster using scientific and engineering benchmarks

Performance evaluation of Intel Xeon E5-2600 family cluster ...

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2012 2nd IEEE international conference on parallel, distributed and grid computing, PDGC 2012

作者： Gepner, Pawel Fraser, David L. Gamayunov, Victor Platform and Technology Enabling Group Intel Corporation Swindon United Kingdom Software and Services Group Intel Corporation Swindon United Kingdom

ISBN: (纸本)9781467329255

In this paper, we present an performance evaluation of a 256-core cluster based on the Intel Xeon Processor E5-2680. This is the new version of Sandy Bridge processor for server and workstation market. It employs an integrated memory controller, dual Intel Quick Path Interconnect (QPI) port and integrated PCIe 3.0 controller. We assessed these architectural enhancements using the High Performance computing Challenge (HPCC) benchmarks and NAS parallel Benchmarks (NPB). For Interconnect analysis we have used the NetPIPE performance evaluator. We compare and contrast the results of a cluster based on the Intel Xeon E5-2680 with a cluster based on Intel Xeon 5680 Processor and another cluster based on Intel Xeon 5570 Processor. © 2012 IEEE.

关键词： Benchmarking

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distributed High Performance computing in OpenStack cloud over SDN Infrastructure 2

Distributed High Performance Computing in OpenStack Cloud ov...

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2nd IEEE international conference on Smart cloud (Smartcloud)

作者： Basnet, Sadhu Ram Chaulagain, Ram Sharan Pandey, Santosh Shakya, Subarna Tribhuvan Univ Inst Engn Dept Elect & Comp Engn Lalitpur Nepal

ISBN: (纸本)9781538636848

cloud computing facilitates end users to allow high performance computing applications by allocating resources on demand. This avoids large capital expenditure for small and medium sized enterprises having limited resources to obtain High Performance computing(HPC). In this paper, we propose a new distributed HPC model in self-built OpenStack public cloud under SDN infrastructure. For partitioning any task in HPC, domain decomposition strategy is used. We analyse different parallel computation topologies and benchmark their performances. The public cloud constructed under OpenStack platform is integrated with Opendaylight SDN controller for network controlling and monitoring. Also, we analyze and compare the performance of the OpenStack cloud with and without proposed distributed HPC system. The result shows that the speed performance of OpenStack cloud under SDN infrastructure is enhanced by implementation of our HPC system based on Hypercube algorithm and Mesh Algorithm.

关键词： HPC OpenStack Public cloud SDN Opendaylight controller Hypercube Algorithm Mesh Algorithm

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