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检索条件"任意字段=5th International Conference on Algorithms and Architectures for Parallel Processing"

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Exploiting a Parametrized Task Graph Model for the parallelization of a Sparse Direct Multifrontal Solver 22nd

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22nd international European conference on parallel and Distributed Computing (Euro-Par)

作者： Agullo, Emmanuel Bosilca, George Buttari, Alfredo Guermouche, Abdou Lopez, Florent INRIA LaBRI Bordeaux France CNRS IRIT Toulouse France Univ Bordeaux LaBRI Bordeaux France RAL STFC Didcot Oxon England Univ Tennessee Knoxville TN USA

ISBN: (纸本)9783319589435;9783319589428

the advent of multicore processors requires to reconsider the design of high performance computing libraries to embrace portable and effective techniques of parallel software engineering. One of the most promising approaches consists in abstracting an application as a directed acyclic graph (DAG) of tasks. While this approach has been popularized for shared memory environments by the OpenMP 4.0 standard where dependencies between tasks are automatically inferred, we investigate an alternative approach, capable of describing the DAG of task in a distributed setting, where task dependencies are explicitly encoded. So far this approach has been mostly used in the case of algorithms with a regular data access pattern and we show in this study that it can be efficiently applied to a higly irregular numerical algorithm such as a sparse multifrontal QR method. We present the resulting implementation and discuss the potential and limits of this approach in terms of productivity and effectiveness in comparison with more common parallelization techniques. Although at an early stage of development, preliminary results show the potential of the parallel programming model that we investigate in this work.

关键词： Multicore architectures Programming models Runtime system Parametrized task graph Numerical scientific library Sparse direct solver Multifrontal QR factorization

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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10th international conference on Security of Information and Networks, SIN 2017

ISBN: (纸本)9781450353038

the proceedings contain 49 papers. the topics discussed include: models and approaches for the safety and the security of distributed systems;redesign CloudRAID for flexible and secure enterprise file sharing over public cloud storage;a universal user revocation scheme with key-escrow resistant for Ciphertext-policy attribute-based access control systems;an enhanced parallel version of RSA public key crypto based algorithm using OpenMP;a model of a secure electronic voting system based on blind intermediaries using Russian cryptographic algorithms;privacy preserving two-server Diffie-Hellman key exchange protocol;attribute-based approach of defining the secure behavior of automata objects;network security architectures for VANET;tamperproof complex event processing in IoT devices using side channel information;integer overflow vulnerabilities detection in software binary code;a novel malware analysis for malware detection and classification using machine learning algorithms;collaborative representation of Grassmann manifold projection metric for robust multi-spectral face recognition;extended multi-spectral imaging for gender classification based on image set;parameters of the two-stage synchronization algorithm for the quantum key distribution system;abnormal leakage of energy in battery-based IoT-devices;a framework for data security in the cloud using collaborative intrusion detection scheme;and integration of role based access control with homomorphic cryptosystem for secure and controlled access of data in cloud.

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Meso-Scale Radioactive Dispersion Modelling using GPU 5

Meso-Scale Radioactive Dispersion Modelling using GPU

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5th international conference on Advances in Nuclear Science and Engineering (ICANSE)

作者： Sunarko Suud, Zaki BATAN Jakarta 10270 Indonesia ITB Jl Ganesha 10 Bandung 50254 Indonesia

Lagrangian Particle Dispersion Method (LPDM) is applied to model atmospheric dispersion of radioactive material in a meso-scale of a few tens of kilometers for site study purpose. Empirical relationships are used to determine the dispersion coefficient for various atmospheric stabilities. Diagnostic 3-D wind field is created based on data from a meteorological station using mass-conservation principle. Particles imitating radioactive pollutant are dispersed in the wind-field as a point source. Time-integrated air concentration is calculated using kernel density estimator (KDE) in the lowest layer of the atmosphere. parallel code is developed for GTX-660Ti GPU with a total of 1344 scalar processors using CUDA programming. Significant speedup of about 20 times is achieved compared to the serial version of the code while accuracy is kept at reasonable level. Only small differences in particle positions and grid doses are observed when using the same sets of random number and meteorological data in both CPU and GPU versions of the code.

关键词： Graphics processing unit

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An Actor-Based Runtime Monitoring System for Web and Desktop Applications 18

An Actor-Based Runtime Monitoring System for Web and Desktop...

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18th IEEE/ACIS international conference on Software Engineering, Artificial Intelligence, Networking and parallel/Distributed Computing (SNPD)

作者： Lavery, Paul Watanabe, Takuo Tokyo Inst Technol Dept Comp Sci Meguro Ku 2-12-1 Ookayama Tokyo 1528552 Japan

ISBN: (纸本)9781509055043

In this paper, we introduce a runtime monitoring method for Actor-based programs and present a Scala module that realizes the proposed method. the primary characteristic of our method is that it supports asynchronous message-passing based on the Actor model. Besides, the module does not require specialized languages for describing application properties to be monitored. Once a developer incorporates the module in his/her application, it continuously checks whether the application satisfies certain properties described as Scala code and invokes mitigation code when it finds the violation of the properties. this paper also provides two non-trivial use cases to illustrate how the module can be seamlessly integrated into actual modern Scala applications. We also demonstrate the efficiency of the module using a set of benchmarks that resulted in only 8% of the experiments causing more than 5% runtime overhead.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Performance Characterization of parallel Discrete Event Simulation on Knights Landing Processor 17

Performance Characterization of Parallel Discrete Event Simu...

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5th ACM SIGSIM conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS)

作者： Williams, Barry Ponomarev, Dmitry Abu-Ghazaleh, Nael Wilsey, Philip SUNY Binghamton Binghamton NY 13902 USA UC Riverside Riverside CA USA Univ Cincinnati Cincinnati OH 45221 USA

ISBN: (纸本)9781450344890

Performance and scalability of parallel Discrete Event Simulation (PDES) is often limited by fine-grain communication, especially in execution environments with high communication cost. However, the low cost of on-chip communication in emerging many-core processors offers a promise to substantially alleviate conventional PDES bottlenecks. In this paper, we present a detailed evaluation and characterization of multi-threaded ROSS simulator on Intel's Knights Landing (KNL) processor. KNL is the second generation of the Intel Xeon Phi family of processors offering significant architecture improvements including 64 out-of-order multi-threaded cores, sharing of some levels of the cache hierarchy among the cores, fast 2D mesh interconnect network and the ability to reconfigure the processor to support various clustering modes. We analyze the performance and scalability of ROSS simulator on KNL processor under different thread counts, communication patterns, event processing granularities, synchronization periods, thread placement policies, and workload partitioning schemes. We conclude that within a single KNL processor, up to 2X performance improvement can be achieved compared to commodity Xeon multicore processors. We show that in most cases the performance of ROSS scales well with the best results achieved when thread affinity is assigned, CPU cores are evenly loaded, cache sharing is exploited and communication is limited to small clusters of cores.

关键词： parallel Discrete Event Simulation Intel Xeon Phi Knights Landing Manycore architectures Performance

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Improving Performances of an Embedded Relational Database Management System with a Hybrid CPU/GPU processing Engine 1

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5th international conference on Data Management Technologies and Applications (DATA)

作者： Cremer, Samuel Bagein, Michel Mahmoudi, Said Manneback, Pierre Haute Ecole Hainaut Comp Engn Dept Ave Maistriau 8A B-7000 Mons Belgium Univ Mons Comp Sci Dept Rue Houdain 9 B-7000 Mons Belgium

ISBN: (数字)9783319629117

ISBN: (纸本)9783319629117;9783319629100

End-user systems are increasingly impacted by the exponential growth of data volumes and their processing. Moreover, post-processing operations, essentially dedicated to ergonomic features, require more and more resources. Improving overall performances of embedded relational database management systems (RDBMS) can contribute to deliver better responsiveness of end-user systems while increasing the energy efficiency. In this paper, it is proposed to upgrade SQLite, the most-spreaded embedded RDBMS, with a hybrid CPU/GPU processing engine combined with appropriate data management. With the proposed solution, named CuDB, massively parallel processing is combined with strategic data placement, closer to computing units. Experimental results revealed, in all cases, better performances and power efficiency compared to SQLite with an in-memory database.

关键词： In-memory database systems Embedded databases Relational database management systems GPU

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Asynchronous Population-Based Hill Climbing Applied to SPICE Model Generation from EM Simulation Data 37th

Asynchronous Population-Based Hill Climbing Applied to SPICE...

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37th SGAI international conference on Artificial Intelligence (AI)

作者： Nolle, Lars Werner, Jens Jade Univ Appl Sci Wilhelmshaven Germany

ISBN: (纸本)9783319710785;9783319710778

In order to utilise the computing power offered by modern multi-core computer systems, APBHC, a new parallel search algorithm is proposed in this paper. this algorithm uses a number of parallel, asynchronous threads, each performing hill climbing independently of each other whilst sharing information about the best solution found so far amongst all threads. this information is used to adapt the maximum step size during the search. One advantage of this approach is that this new algorithm has no control parameters, which would require tuning. the other advantage is that it can make use of all processing cores available in a computer system. the new method was applied to the problem of Spice Model Generation. It was shown that it out-performs Genetic algorithms (GA), which were applied to this problem in the past, without the need of time consuming parameter tuning.

关键词： Electro-Magnetic simulation Optimisation parallel processing Hill climbing Self-adaptation APBHC

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DengueViz: A knowledge-based expert system integrated with parallel coordinates visualization in the dengue diagnosis 5th

DengueViz: A knowledge-based expert system integrated with p...

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5th international Visual Informatics conference, IVIC 2017

作者： Ooi, Jodene Yen Ling thomas, J. Joshua Department of Computing School of Engineering Computing and Built Environment KDU Penang University College George TownPenang Malaysia

ISBN: (纸本)9783319700090

the DengueViz is a knowledge-based expert system integrated with parallel coordinates as its visualization technique to diagnose dengue. the dengue diagnosis results includes the dengue classifications and their probability according to the interactions of users with the system. the knowledge base of this system consists of 140 rules for the classification of dengue. the integration of parallel coordinates visually presents the large amount of dengue information into a single visualization, where data interactions such as the selection of axes, filtering and highlighting reduces the clutter for it to be more comprehensible and enhances the correlation between the attributes of the information. © Springer international Publishing AG 2017.

关键词： Classification (of information)

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Speed-Up Computational Finance Simulations with OpenCL on Intel Xeon Phi 22nd

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22nd international European conference on parallel and Distributed Computing (Euro-Par)

作者： Papadimitriou, Michail Cramwinckel, Joris Varbanescu, Ana Lucia Delft Univ Technol Delft Netherlands Ortec Finance Rotterdam Netherlands Univ Amsterdam Amsterdam Netherlands

ISBN: (纸本)9783319589435;9783319589428

Computational finance is a domain where performance is in high demand. In this work, we investigate the suitability of Intel Xeon Phi for computational finance simulations. Specifically, we use a scenario based ALM (Asset Liability Management) model and propose a novel OpenCL implementation for Xeon Phi. To further improve the performance of the application, we apply several optimization techniques (data layout and data locality improvement, loop unrolling) and study their effects. Our results show that the optimized OpenCL code deployed on the Phi can run up to 135x faster than the original scalar code running on an Intel i7 GPP. Furthermore, we also show that choosing the optimal work-item/work-group distribution has a compelling effect on massively parallel and heavily-branching code. Overall, these results are significant for the computational finance specialists, as they enable a major increase in model accuracy, because 10x more simulations can be performed in less than a 10th of the original time.

关键词： OpenCL Computing Accelerated architectures Intel Xeon Phi MIC GPGPU parallel computing Asset Liability Management

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Sparse signal recovery from compressed measurements using hybrid particle swarm optimization 5

Sparse signal recovery from compressed measurements using hy...

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5th IEEE international conference on Signal and Image processing Applications, ICSIPA 2017

作者： Haider, Hassaan Shah, Jawad Ali Ikram, Shahid Latif, Idris Abd Department of Electrical Engineering Faculty of Engineering and Technology International Islamic University Islamabad Pakistan Electronic Technology Section Universiti Kuala Lumpur British Malaysian Institute Malaysia

ISBN: (纸本)9781509055593

the computationally intensive part of compressed sensing (CS) deals with the sparse signal reconstruction from lesser number of random projections. Finding sparse solution to such an underdetermined system is highly ill-conditioned and therefore requires additional regularization constraints. this research paper introduces a new approach for recovering a K-sparse signal from compressed samples using particle swarm optimization (PSO) along with separable surrogate functionals (SSF) algorithm. the suggested hybrid mechanism applied with appropriate regularization constraints speeds up the convergence of PSO. the estimated original sparse signal is also recovered with great precision. Simulation results show that the signal estimated with PSO-SSF combination outperforms the signal recovery through PSO, SSF and parallel coordinate descent (PCD) methods in terms of reconstruction accuracy. Finally, the efficiency of the proposed algorithm is validated experimentally by exactly recovering a one-dimensional K-sparse signal from only a few number of non-Adaptive random measurements. © 2017 IEEE.

关键词： Compressed sensing

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