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High Performance Computing for Computational Science – VECPAR 2016

12th International Conference, Porto, Portugal, June 28-30, 2016, Revised Selected Papers

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. Inês Dutra

    1. University of Porto, Porto, Portugal

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  2. Rui Camacho

    1. University of Porto, Porto, Portugal

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  3. Jorge Barbosa

    1. University of Porto, Porto, Portugal

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  4. Osni Marques

    1. Lawrence Berkeley National Laboratory, Berkeley, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10150)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: VECPAR 2016.

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Table of contents (23 papers)

  1. Front Matter

    Pages I-XIII
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  2. Invited Talks

    1. Front Matter

      Pages 1-1
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    2. Scalable Algorithms for Bayesian Inference of Large-Scale Models from Large-Scale Data

      • Omar Ghattas, Tobin Isaac, Noémi Petra, Georg Stadler
      Pages 3-6

    3. Analysis of High Performance Applications Using Workload Requirements

      • Mariza Ferro, Giacomo Mc Evoy, Bruno Schulze
      Pages 7-10

    4. Hard Faults and Soft-Errors: Possible Numerical Remedies in Linear Algebra Solvers

      • E. Agullo, S. Cools, L. Giraud, A. Moreau, P. Salas, W. Vanroose et al.
      Pages 11-18

  3. Applications

    1. Front Matter

      Pages 19-19
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    2. SIMD Parallel Sparse Matrix-Vector and Transposed-Matrix-Vector Multiplication in DD Precision

      • Toshiaki Hishinuma, Hidehiko Hasegawa, Teruo Tanaka
      Pages 21-34

    3. Accelerating the Conjugate Gradient Algorithm with GPUs in CFD Simulations

      • Hartwig Anzt, Marc Baboulin, Jack Dongarra, Yvan Fournier, Frank Hulsemann, Amal Khabou et al.
      Pages 35-43

    4. Parallelisation of MACOPA, A Multi-physics Asynchronous Solver

      • Ronan Guivarch, Guillaume Joslin, Ronan Perrussel, Daniel Ruiz, Jean Tshimanga, Thomas Unfer
      Pages 44-51

    5. Performance Analysis of SA-AMG Method by Setting Extracted Near-Kernel Vectors

      • Naoya Nomura, Akihiro Fujii, Teruo Tanaka, Kengo Nakajima, Osni Marques
      Pages 52-63

    6. Computing the Bidiagonal SVD Through an Associated Tridiagonal Eigenproblem

      • Osni Marques, Paulo B. Vasconcelos
      Pages 64-74

    7. HPC on the Intel Xeon Phi: Homomorphic Word Searching

      • Paulo Martins, Leonel Sousa
      Pages 75-88

    8. A Data Parallel Algorithm for Seismic Raytracing

      • Allen D. Malony, Stephanie McCumsey, Joseph Byrnes, Craig Rasmusen, Soren Rasmusen, Erik Keever et al.
      Pages 89-98

  4. Performance Modeling and Analysis

    1. Front Matter

      Pages 99-99
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    2. A Cross-Core Performance Model for Heterogeneous Many-Core Architectures

      • Rui Pinheiro, Nuno Roma, Pedro Tomás
      Pages 101-111

    3. On the Acceleration of Graph500: Characterizing PCIe Overheads with Multi-GPUs

      • Mayank Daga
      Pages 112-120

    4. Evaluation of Runtime Cut-off Approaches for Parallel Programs

      • Alcides Fonseca, Bruno Cabral
      Pages 121-134

    5. Implementation and Evaluation of NAS Parallel CG Benchmark on GPU Cluster with Proprietary Interconnect TCA

      • Kazuya Matsumoto, Norihisa Fujita, Toshihiro Hanawa, Taisuke Boku
      Pages 135-145

  5. Low Level Support

    1. Front Matter

      Pages 147-147
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    2. The Design of Advanced Communication to Reduce Memory Usage for Exa-scale Systems

      • Shinji Sumimoto, Yuichiro Ajima, Kazushige Saga, Takafumi Nose, Naoyuki Shida, Takeshi Nanri
      Pages 149-161
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About this book

This book constitutes the thoroughly refereed post-conference proceedings of the 12fth International Conference on High Performance Computing in Computational Science,

VECPAR 2016, held in Porto, Portugal, in June 2016.
The 20 full papers presented were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on applications; performance modeling and analysis; low level support; environments/libraries to support parallelization.

Editors and Affiliations

  • University of Porto, Porto, Portugal

    Inês Dutra, Rui Camacho, Jorge Barbosa

  • Lawrence Berkeley National Laboratory, Berkeley, USA

    Osni Marques

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