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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

共 2574 条记录，以下是251-260 订阅

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SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enabled systems 34

SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-enab...

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34th ieee international parallel and distributed processing symposium (IPDPS)

作者： Acer, Seher Boman, Erik G. Rajamanickam, Sivasankaran Sandia Natl Labs Ctr Comp Res POB 5800 Albuquerque NM 87185 USA

ISBN: (纸本)9781728174457

Graph partitioning has been an important tool to partition the work among several processors to minimize the communication cost and balance the workload. While accelerator-based supercomputers are emerging to be the standard, the use of graph partitioning becomes even more important as applications are rapidly moving to these architectures. However, there is no scalable, distributed-memory, multi-GPU graph partitioner available for applications. We developed a spectral graph partitioner, Sphynx, using the portable, accelerator-friendly stack of the Trilinos framework. We use Sphnyx to systematically evaluate the various algorithmic choices in spectral partitioning with a focus on GPU performance. We perform those evaluations on irregular graphs, because state-of-the-art partitioners have the most difficulty on them. We demonstrate that Sphynx is up to 17x faster on GPUs compared to the case on CPUs, and up to 580x faster compared to a state-of-the-art multilevel partitioner. Sphynx provides a robust alternative for applications looking for a GPU-based partitioner.

关键词： graph partitioning spectral partitioning GPUs distributed-memory systems

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Proceedings - 2014 ieee 13th international symposium on Network Computing and applications, NCA 2014

Proceedings - 2014 IEEE 13th International Symposium on Netw...

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2014 13th ieee international symposium on Network Computing and applications, NCA 2014

ISBN: (纸本)9781479953936

the proceedings contain 49 papers. the topics discussed include: using virtual mobile nodes for neighbor detection in proximity-based mobile applications;ADD: a data dissemination solution for highly dynamic highway environments;strip interoperability for wireless ad hoc routing protocols;a deadline aware DTN approach based on epidemic routing;VANets: an exploratory evaluation in vehicular ad hoc network for urban environment;optimal configuration for n-dimensional twin Torus networks;resource management in cloud federation using XMPP;on-demand resource allocation middleware for massively multiplayer online games;a resilient hierarchical distributed loop self-scheduling scheme for cloud systems;interference avoidance through frequency assignment and association control in ieee 802.11 WLAN;recovery of information lost by the least squares estimation in real-time network environment;and based-agent distributed architecture to manage the dynamic multi-hop ridesharing system.

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Highly Scalable X10-based Agent Simulation Platform and its Application to Large-scale Traffic Simulation 12

Highly Scalable X10-based Agent Simulation Platform and its ...

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16th ieee/ACM international symposium on distributed Simulation and Real Time applications

作者： Suzumura, Toyotaro Kanezashi, Hiroki IBM Res Tokyo Tokyo Japan Tokyo Inst Technol Tokyo Japan JST CREST Tokyo Japan

ISBN: (纸本)9780769548463

this paper describes highly scalable X10-based agent simulation platform called XAXIS. XAXIS is designed to handle millions or billions of agents on recent highly distributed and parallel computing environments with more than hundreds of CPU cores. To make the runtime scalable on such environments, we need to redesign and implement the simulation middleware. In this paper, we propose the software design, implementation on X10, one of the state-of-the-art PGAS language, and then application to large-scale traffic simulation. By using 192 CPU cores in distributed memory computing environment, the performance scalability is achieved with a traffic simulation.

关键词： Traffic simulation Scalability Agents Environments parallel processing (COMPUTERS) simulating central processing units Platform

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Multi-path Routing for Energy Efficient Mobile Offloading in Software Defined Networks 15

Multi-path Routing for Energy Efficient Mobile Offloading in...

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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Hou, Haixiang Jin, Hai Liao, Xiaofei Zeng, Deze Huazhong Univ Sci & Technol Sch Comp Sci & Technol Serv Comp Technol & Syst Lab Cluster & Grid Comp Lab Wuhan Hubei Peoples R China China Univ Geosci Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9781538637906

In Software Defined Network (SDN), rule space is an unavoidable restriction caused by Ternary Content Addressable Memory (TCAM). When offloading becomes more popular, a sharp increase in the number of flows influences the link scheduling and the Quality of Service (QoS) for customers. thus, the link scheduling in SDN must consider the constraints about rule space, bandwidth, and QoS. To optimize the energy consumption in mobile computing, we build a model to understand the relationships among offloading decisions, latency, and energy consumption. We implement a two-phase algorithm to schedule links by the usage of rule space in the switches and the usage of bandwidth in links. through comparative evaluation, we verify the feasibility of the algorithm. When the usage of rule space in SDN network is not full, the algorithm can archive more than 90% energy efficiency compared to the optimal solution.

关键词： Software Defined Network Multi-Path Routing Rule Placement Optimization

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Iterative Krylov Methods for Acoustic Problems on Graphics processing Unit 13

Iterative Krylov Methods for Acoustic Problems on Graphics P...

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13th international symposium on distributed Computing and applications to Business, Engineering and Science (DCABES)

作者： Ahamed, Abal-Kassim Cheik Magoules, Frederic Ecole Cent Paris CUDA Res Ctr Chatenay Malabry France Ecole Cent Paris Appl Math & Syst Lab Chatenay Malabry France

ISBN: (纸本)9781479941698

this paper deals with linear algebra operations on Graphics processing Unit (GPU) with complex number arithmetic using double precision. An analysis of their uses within iterative Krylov methods is presented to solve acoustic problems. Numerical experiments performed on a set of acoustic matrices arising from the modelisation of acoustic phenomena inside a car compartment are collected, and outline the performance, robustness and effectiveness of our algorithms, with a speed-up up to 28x for dot product, 9.8x for sparse matrix-vector product and solvers.

关键词： Linear algebra Iterative Krylov methods CSR matrix GPU CUDA Acoustic Helmholtz equation parallel computing

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A distributed Greedy Heuristic for Computing Voronoi Tessellations With applications Towards Peer-to-Peer Networks 29

A Distributed Greedy Heuristic for Computing Voronoi Tessell...

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29th ieee international parallel and distributed processing symposium (IPDPS)

作者： Benshoof, Brendan Rosen, Andrew Bourgeois, Anu G. Harrison, Robert W. Georgia State Univ Dept Comp Sci Atlanta GA 30303 USA

ISBN: (纸本)9781467376846

Computing Voronoi tessellations in an arbitrary number of dimensions is a computationally difficult task. this problem becomes exacerbated in distributed environments, such as Peer-to-Peer networks and Wireless networks, where Voronoi tessellations have useful applications. We present our distributed Greedy Voronoi Heuristic, which approximates Voronoi tessellations in distributed environments. Our heuristic is fast, scalable, works in any geometric space with a distance and midpoint function, and has interesting applications in embedding metrics such as latency in the links of a distributed network.

关键词： Peer-to-Peer Networks Wireless Sensor Networks Ad-Hoc Networks Computational Geometry

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On-Demand processing for Remote Sensing Big Data Analysis 15

On-Demand Processing for Remote Sensing Big Data Analysis

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15th ieee international symposium on parallel and distributed processing with applications (ISPA) / 16th ieee international Conference on Ubiquitous Computing and Communications (IUCC)

作者： Huang, Zhenchun Zhong, Anrun Li, Guoqing Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Chinese Acad Sci Inst Remote Sensing & Digital Earth Beijing Peoples R China

ISBN: (纸本)9781538637906

In the recent decades, remote sensing data are rapidly growing in size and variety, and considered as "big geo data" because of their huge data volume, significant heterogeneity and challenge of fast analysis. In the traditional remote sensing analysis workflows, the data transfer for downloading raw image files to local workstations often costs a lot of time and slows down the data analysis workflows. Because results of remote sensing data analysis models are usually much smaller than raw data to be processed, "on-demand processing", which tries to upload data analysis models and execute them "near" where data stores, can significantly accelerate the execution of remote sensing analysis workflows. In this paper, a framework for on-demand remote sensing data analysis is proposed based on three-layered architecture;XML/JSON based runtime environment description;and on-demand model deployment methods. the evaluation on a prototype system shows that on-demand processing framework accelerates the execution of analysis models in 2.8 similar to 12.7 times by reducing data transfers, especially for those analysis workflows which transfer data through low bandwidth Internet. By on-demand processing, classical remote sensing data service systems can evolve into remote sensing data processing infrastructures, which provide IaaS (Infrastructure-as-a-Service) and PaaS (Platform-as-a Service) services, and make it possible to exchange knowledge among scientists by sharing models. Furthermore, a remote sensing data analysis platform for carbon satellites is designed based on the on-demand processing proposed by this paper and will soon be implemented under the support of SunWay-TaihuLight, the world's most powerful super computer.

关键词： remote sensing data analysis on-demand processing big geo data

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Dynamic Batch parallel Algorithms for Updating PageRank 36

Dynamic Batch Parallel Algorithms for Updating PageRank

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36th ieee international parallel and distributed processing symposium (ieee IPDPS)

作者： Sahu, Subhajit Kothapalli, Kishore Banerjee, Dip Sankar Int Inst Informat Technol Hyderabad Hyderabad India Indian Inst Technol Jodhpur Jodhpur Rajasthan India

ISBN: (纸本)9781665497473

the design and implementation of parallel algorithms for dynamic graph problems is attracting significant research attention in the recent years, driven by numerous applications to social network analysis, neuroscience, and protein interaction networks. One such problem is the computation of PageRank values of vertices in a directed graph. this paper presents two new parallel algorithms for recomputing the PageRank values of vertices in a dynamic graph. Our techniques require the recomputation of the PageRank of only the vertices affected by the insertion/deletion of a batch of edges. We conduct detailed experimental studies of our algorithm on a set of 11 real-world graphs. Our results on Intel Xeon Silver 4116 CPU and NVIDIA Tesla V100 PCIe 16GB GPU indicate that our algorithms outperform static and dynamic update algorithms by 6.1x and 8.6x on the CPU, and by 9.8x and 9.3x on the GPU respectively. We also compare the performance of the algorithms in batched mode to cumulative single-edge updates.

关键词： Proteins Silver distributed processing Neuroscience Social networking (online) Heuristic algorithms Graphics processing units

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A Tool for Bottleneck Analysis and Performance Prediction for GPU-accelerated applications 30

A Tool for Bottleneck Analysis and Performance Prediction fo...

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30th ieee international parallel and distributed processing symposium (IPDPS)

作者： Madougou, Souley Varbanescu, Ana Lucia de Laat, Cees van Nieuwpoort, Rob Univ Amsterdam NL-1012 WX Amsterdam Netherlands Netherlands eSci Ctr Amsterdam Netherlands

ISBN: (纸本)9781509036820

High-level tools for analyzing and predicting the performance GPU-accelerated applications are scarce, at best. Although performance modeling approaches for GPUs exist, their complexity makes them virtually impossible to use to quickly analyze the performance of real life applications and obtain easy-to-use, readable feedback. this is why, although GPUs are significant performance boosters in many HPC domains, performance prediction is still based on extensive benchmarking, and performance bottleneck analysis remains a nonsystematic, experience-driven process. In this context, we propose a tool for bottleneck analysis and performance prediction for GPU-accelerated applications. Based on random forest modeling, and using hardware performance counters data, our method can be used to quickly and accurately evaluate application performance on GPU-based systems for different problem characteristics and different hardware generations. We illustrate the benefits of our approach with three detailed use cases: a simple step-by-step example on a parallel reduction kernel, and two classical benchmarks (matrix multiplication and sequence alignment). Our results so far indicate that our statistical modeling is a quick, easy-to-use method to grasp the performance characteristics of applications running on GPUs. Our current work focuses on tackling some of its applicability limitations (more applications, more platforms) and improving its usability (full automation from input to user feedback).

关键词： GPU bottleneck analysis performance prediction application scaling hardware scaling

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On the Correctness of Mixing Lazy and Eager Version Management in Transactions

On the Correctness of Mixing Lazy and Eager Version Manageme...

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26th ieee international parallel and distributed processing symposium (IPDPS)

作者： Zhao, Lihang Draper, Jeff Univ So Calif Inst Informat Sci Marina Del Rey CA 90292 USA

ISBN: (纸本)9780769546766

Transactional memory has been proposed as an optimistic concurrency-control construct to ease parallel programming. Hardware transactional memory (HTM) approaches implement version management and conflict detection in hardware to guarantee the correctness of transaction execution. Based on the style of version management and conflict detection, state-of-the-art HTM systems fall into two main types, namely lazy systems and eager systems. Neither system type is able to always perform better than the other over a wide range of applications due to the broad variations in the execution behaviors in typical parallel workloads. In this paper, we focus on the correctness of mixing lazy and eager version management in a log-based HTM. this hybrid type of version management is demonstrated to satisfy the requirement of atomicity and conflict serializability, which are critical for correctness. Furthermore, it is shown that the new approach does not violate the memory coherence formal model.

关键词： parallel programming

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