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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

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Improving the Performance of Cardiac Simulations in a Multi-GPU Architecture Using a Coalesced Data and Kernel Scheme 16th

Improving the Performance of Cardiac Simulations in a Multi-...

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16th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Cordeiro, Raphael Pereira Oliveira, Rafael Sachetto dos Santos, Rodrigo Weber Lobosco, Marcelo Univ Fed Juiz de Fora Programa Modelagem Computac Juiz de Fora Brazil Univ Fed Sao Joao del Rei Dept Ciencia Computacao Sao Joao del Rei Brazil

ISBN: (纸本)9783319495835;9783319495828

In this paper we evaluate a new coalesced data and kernel scheme used to reduce the execution costs of cardiac simulations that run on multi-GPU environments. the new scheme was tested for an important part of the simulator, the solution of the systems of Ordinary Differential Equations (ODEs). the results have shown that the proposed scheme is very effective. the execution time to solve the systems of ODEs on the multi-GPU environment was reduced by half, when compared to a scheme that does not implemented the proposed data and kernel coalescing. As a result, the total execution time of cardiac simulations was 25% faster.

关键词： High performance computing parallel computing Multi-GPU Cardiac electrophysiology Computational modeling

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Doctoral symposium: Adaptive steering of cyber-physical systems with atomic complex event processing services 10

Doctoral symposium: Adaptive steering of cyber-physical syst...

引用

10th ACM international conference on Distributed and Event-Based Systems, DEBS 2016

作者： Ollesch, Julius Paluno - Ruhr Institute for Software Technology University of Duisburg-Essen Schuetzenbahn 70 Essen45127 Germany

ISBN: (纸本)9781450340212

Given the advent of cyber-physical systems (CPS), eventbased control paradigms such as complex event processing (CEP) are vital enablers for adaptive analytical control mechanisms. CPS are becoming a high-profile research topic as they are key to disruptive digital innovations such as autonomous driving, industrial internet, smart grid and ambient assisted living. However, organizational and technological scalability of today's CEP approaches is limited by their monolithic architectures. this leads to the research idea for atomic CEP entities and the hypothesis that a network of small event-based control services is better suited for CPS development and operation than current centralised approaches. In addition, the paper summarizes preliminary results of the presented doctoral work and outlines questions for future research as well as an evaluation plan. © 2016 ACM.

关键词： Web services

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Using HPX and OP2 for Improving parallel Scaling Performance of Unstructured Grid Applications 45

Using HPX and OP2 for Improving Parallel Scaling Performance...

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45th international conference on parallel processing (ICPP)

作者： Khatami, Zahra Kaiser, Hartmut Ramanujam, J. Louisiana State Univ Ctr Computat & Technol Baton Rouge LA 70803 USA STE AR Grp Baton Rouge LA 70815 USA

ISBN: (纸本)9781509028252

Computer scientists and programmers face the difficultly of improving the scalability of their applications while using conventional programming techniques only. As a base-line hypothesis of this paper we assume that an advanced runtime system can be used to take full advantage of the available parallel resources of a machine in order to achieve the highest parallelism possible. In this paper we present the capabilities of HPX - a distributed runtime system for parallel applications of any scale - to achieve the best possible scalability through asynchronous task execution [1]. OP2 is an active library which provides a framework for the parallel execution for unstructured grid applications on different multi-core/many-core hardware architectures [2]. OP2 generates code which uses OpenMP for loop parallelization within an application code for both single-threaded and multi-threaded machines. In this work we modify the OP2 code generator to target HPX instead of OpenMP, i.e. port the parallel simulation backend of OP2 to utilize HPX. We compare the performance results of the different parallelization methods using HPX and OpenMP for loop parallelization within the Airfoil application. the results of strong scaling and weak scaling tests for the Airfoil application on one node with up to 32 threads are presented. Using HPX for parallelization of OP2 gives an improvement in performance by 5%-21%. By modifying the OP2 code generator to use HPX's parallel algorithms, we observe scaling improvements by about 5% as compared to OpenMP. To fully exploit the potential of HPX, we adapted the OP2 API to expose a future and dataflow based programming model and applied this technique for parallelizing the same Airfoil application. We show that the dataflow oriented programming model, which automatically creates an execution tree representing the algorithmic data dependencies of our application, improves the overall scaling results by about 21% compared to OpenMP. Our results show

关键词： High Performance Computing HPX OP2 Asynchronous Task Execution

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parallel implementation of minimum spanning tree algorithm on CPU and GPU 10

Parallel implementation of minimum spanning tree algorithm o...

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10th Annual international Scientific conference on parallel Computing Technologies, PCT 2016

作者： Kolganov, A.S. Lomonosov Moscow State University Russia Keldysh Institute of Applied Mathematics RAS Russia

Solution of the finding a minimum spanning tree problem is common in various areas of research: recognition of different objects, computer vision, analysis and construction of networks (eg, telephone, electrical, computer, travel, etc.), chemistry and biology, and many others. there are at least three well-known algorithms for solving this problem: Boruvka, Kruskal and Prim. processing large graphs is a quite time-consuming task for the central processor (CPU), and in high demand at the present moment. the usage of Graphics processing units (GPUs) as a mean to solve general-purpose problems grows every day, because GPUs have more computing power than CPUs. But the minimum spanning tree (MST) computation on a general graph is an irregular algorithm. So it suits poorly the GPU architecture. this article examins a hybrid implementation of this algorithm on GPU and CPU.

关键词： Graphics processing unit

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A Bucket Sort Algorithm for the Particle-In-Cell Method on Manycore architectures 11th

A Bucket Sort Algorithm for the Particle-In-Cell Method on M...

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

作者： Jocksch, Andreas Hariri, Farah Tran, Trach-Minh Brunner, Stephan Gheller, Claudio Villard, Laurent Swiss Natl Supercomp Ctr CSCS Via Trevano 131 CH-6900 Lugano Switzerland Ecole Polytech Fed Lausanne Swiss Plasma Ctr CH-1015 Lausanne Switzerland

ISBN: (纸本)9783319321493;9783319321486

the Particle-In-Cell (PIC) method is effectively used in many scientific simulation codes. In order to optimize the performance of the PIC approach, data locality is required. this relies on efficient sorting algorithms. We present a bucket sort algorithm with small memory footprint for the PIC method targeting Graphics processing Units (GPUs). Our sorting algorithm shows an increased performance with the amount of storage provided and with the orderliness of the particles. For our application where particles are presorted it performs better and requires less memory than other sorting algorithms in the literature. the overall PIC algorithm performs at its best if the sorting is applied.

关键词： Particle-In-Cell GPU Bucket sort

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Scaling DBSCAN-like algorithms for Event Detection Systems in Twitter 16th

Scaling DBSCAN-like Algorithms for Event Detection Systems i...

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16th international conference on algorithms and architectures for parallel processing (ICA3PP)

作者： Capdevila, Joan Pericacho, Gonzalo Torres, Jordi Cerquides, Jesus Polytech Univ Catalonia UPC Dept Comp Architec Barcelona Spain Barcelona Supercomp Ctr BSC CNS Dept Comp Sci Barcelona Spain Artificial Intelligence Res Inst IIIA CSIC Barcelona Spain

ISBN: (纸本)9783319495835;9783319495828

the increasing use of mobile social networks has lately transformed news media. Real-world events are nowadays reported in social networks much faster than in traditional channels. As a result, the autonomous detection of events from networks like Twitter has gained lot of interest in both research and media groups. DBSCAN-like algorithms constitute a well-known clustering approach to retrospective event detection. However, scaling such algorithms to geographically large regions and temporarily long periods present two major shortcomings. First, detecting real-world events from the vast amount of tweets cannot be performed anymore in a single machine. Second, the tweeting activity varies a lot within these broad space-time regions limiting the use of global parameters. Against this background, we propose to scale DBSCAN-like event detection techniques by parallelizing and distributing them through a novel density-aware MapReduce scheme. the proposed scheme partitions tweet data as per its spatial and temporal features and tailors local DBSCAN parameters to local tweet densities. We implement the scheme in Apache Spark and evaluate its performance in a dataset composed of geo-located tweets in the Iberian peninsula during the course of several football matches. the results pointed out to the benefits of our proposal against other state-of-the-art techniques in terms of speed-up and detection accuracy.

关键词： Event detection parallel algorithm Data clustering DBSCAN MapReduce Apache Spark Twitter

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Demo: Complex event processing over streaming multi-cloud platforms - the FERARI approach 10

Demo: Complex event processing over streaming multi-cloud pl...

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10th ACM international conference on Distributed and Event-Based Systems, DEBS 2016

作者： Flouris, Ioannis Manikaki, Vasiliki Giatrakos, Nikos Deligiannakis, Antonios Garofalakis, Minos Mock, Michael Bothe, Sebastian Skarbovsky, Inna Fournier, Fabiana Štajcer, Marko Križan, Tomislav Yom-Tov, Jonathan Volarevíc, Marijo Technical University of Crete Greece IBM Research - Haifa Israel Fraunhofer IAIS Germany Israel Institute of Technology Technion Israel Poslovna Inteligencija Croatia T-Hrvatski Telekom Croatia

ISBN: (纸本)9781450340212

We present FERARI, a prototype for processing voluminous event streams over multi-cloud platforms. At its core, FERARI both exploits the potential for in-situ (intra-cloud) processing and orchestrates inter-cloud complex event detection in a communicationefficient way. At the application level, it includes a user-friendly query authoring tool and an analytics dashboard providing granular reports about detected events. In that, FERARI constitutes, to our knowledge, the first complete end-to-end solution of its kind. In this demo, we apply the FERARI approach on a real scenario from the telecommunication domain. © 2016 ACM.

关键词： Cloud analytics

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A parallel Multi-threaded Solver for Symmetric Positive Definite Bordered-Band Linear Systems 11th

A Parallel Multi-threaded Solver for Symmetric Positive Defi...

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

作者： Benner, Peter Ezzatti, Pablo Quintana-Orti, Enrique S. Remon, Alfredo Max Planck Inst Dynam Complex Tech Syst D-39106 Magdeburg Germany Univ Republica Inst Comp Montevideo 11300 Uruguay Univ Jaime I Dept Ingn & Ciencia Comp Castellon de La Plana 12701 Spain

ISBN: (纸本)9783319321493;9783319321486

We present a multi-threaded solver for symmetric positive definite linear systems where the coefficient matrix of the problem features a bordered-band non-zero pattern. the algorithms that implement this approach heavily rely on a compact storage format, tailored for this type of matrices, that reduces the memory requirements, produces a regular data access pattern, and allows to cast the bulk of the computations in terms of efficient kernels from the Level-3 and Level-2 BLAS. the efficiency of our approach is illustrated by numerical experiments.

关键词： Bordered-band matrices Symmetric positive definite linear systems Cholesky factorization Multicore architectures

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High Resolution Satellite Image processing using Hadoop framework 4

High Resolution Satellite Image Processing using Hadoop fram...

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4th IEEE international conference on Cloud Computing in Emerging Markets (CCEM)

作者： Rajak, Roshan Raveendran, Deepu Chandrasekhar, Maruthi Bh Medasani, Shanti Swarup Uurmi Syst Pvt Ltd Image Understanding Grp Hyderabad Andhra Pradesh India

ISBN: (纸本)9781467385664

Complex image processing algorithms that require higher computational power with large scale inputs can be processed efficiently using the parallel and distributed processing of Hadoop MapReduce Framework. Hadoop MapReduce is a scalable model which is capable of processing petabytes (10(15) order) of data with improved fault tolerance and data parallelism. In this paper we present a MapReduce framework for performing parallel remote sensing satellite data processing using Hadoop and storing the output in HBase. the speedup and performance show that by utilizing Hadoop, we can distribute our workload across different clusters to take advantage of combined processing power on commodity hardware.

关键词： Hadoop HDFS MapReduce Image processing Remote Sensing Efficient Satellite data analysis

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Efficient GPU-implementation of coherent stacking with CUDA 10

Efficient GPU-implementation of coherent stacking with CUDA

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10th Annual international Scientific conference on parallel Computing Technologies, PCT 2016

作者： Gorodnichev, M.A. Duchkov, A.A. Sarychev, V.G. Novosibirsk State Technical University Russia Novosibirsk State University Russia Institute of Computational Mathematics and Mathematical Geophysics SB RAS Russia Trofimuk Institute of Petroleum Geology and Geophysics SB RAS Russia

Coherent stacking is a key procedure for a class of algorithms that are used to process seismic data. the paper presents an efficient implementation of coherent stacking algorithm on CUDA-based GPUs. We discuss a complex of optimizations that allowed the implementation to reach 70% of peak hardware performance. Tests reveal linear dependency between computing time and problem size. Terabytes of seismic data can not be placed into the memory of GPU card at once and thus the processing must be organized in portions. Optimal portion sizes where found for the following generations of Nvidia GPUs: Fermi, Kepler, Maxwell.

关键词： Graphics processing unit

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