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High Performance Computing

34th International Conference, ISC High Performance 2019, Frankfurt/Main, Germany, June 16–20, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Michèle Weiland

    1. University of Edinburgh, Edinburgh, UK

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  2. Guido Juckeland

    1. Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany

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  3. Carsten Trinitis

    1. Technical University of Munich, Munich, Germany

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  4. Ponnuswamy Sadayappan

    1. Ohio State University, Columbus, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11501)

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

Included in the following conference series:

Conference proceedings info: ISC High Performance 2019.

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Table of contents (17 papers)

  1. Front Matter

    Pages i-xvi
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  2. Architectures, Networks and Infrastructure

    1. Front Matter

      Pages 1-1
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    2. Evaluating Quality of Service Traffic Classes on the Megafly Network

      • Misbah Mubarak, Neil McGlohon, Malek Musleh, Eric Borch, Robert B. Ross, Ram Huggahalli et al.
      Pages 3-20

  3. Artificial Intelligence and Machine Learning

    1. Front Matter

      Pages 21-21
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    2. Densifying Assumed-Sparse Tensors

      • Derya Cavdar, Valeriu Codreanu, Can Karakus, John A. Lockman III, Damian Podareanu, Vikram Saletore et al.
      Pages 23-39

    3. Learning Neural Representations for Predicting GPU Performance

      • Shweta Salaria, Aleksandr Drozd, Artur Podobas, Satoshi Matsuoka
      Pages 40-58

  4. Data, Storage and Visualization

    1. Front Matter

      Pages 59-59
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    2. SLOPE: Structural Locality-Aware Programming Model for Composing Array Data Analysis

      • Bin Dong, Kesheng Wu, Suren Byna, Houjun Tang
      Pages 61-80

    3. A Near-Data Processing Server Architecture and Its Impact on Data Center Applications

      • Xiaojia Song, Tao Xie, Stephen Fischer
      Pages 81-98

    4. Comparing the Efficiency of In Situ Visualization Paradigms at Scale

      • James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki et al.
      Pages 99-117

  5. Emerging Technologies

    1. Front Matter

      Pages 119-119
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    2. Layout-Aware Embedding for Quantum Annealing Processors

      • Jose P. Pinilla, Steven J. E. Wilton
      Pages 121-139

  6. HPC Algorithms

    1. Front Matter

      Pages 141-141
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    2. Toward Efficient Architecture-Independent Algorithms for Dynamic Programs

      • Mohammad Mahdi Javanmard, Pramod Ganapathi, Rathish Das, Zafar Ahmad, Stephen Tschudi, Rezaul Chowdhury
      Pages 143-164

  7. HPC Applications

    1. Front Matter

      Pages 165-165
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    2. Petaflop Seismic Simulations in the Public Cloud

      • Alexander Breuer, Yifeng Cui, Alexander Heinecke
      Pages 167-185

    3. MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles

      • Shashi M. Aithal, Prasanna Balaprakash
      Pages 186-205

  8. Performance Modeling and Measurement

    1. Front Matter

      Pages 207-207
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    2. PerfMemPlus: A Tool for Automatic Discovery of Memory Performance Problems

      • Christian Helm, Kenjiro Taura
      Pages 209-226

    3. GPUMixer: Performance-Driven Floating-Point Tuning for GPU Scientific Applications

      • Ignacio Laguna, Paul C. Wood, Ranvijay Singh, Saurabh Bagchi
      Pages 227-246
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Other volumes

  1. High Performance Computing

  2. High Performance Computing

Keywords

About this book

This book constitutes the refereed proceedings of the 34th International Conference on High Performance Computing, ISC High Performance 2019, held in Frankfurt/Main, Germany, in June 2019.

The 17 revised full papers presented were carefully reviewed and selected from 70 submissions. The papers cover a broad range of topics such as next-generation high performance components; exascale systems; extreme-scale applications; HPC and advanced environmental engineering projects; parallel ray tracing - visualization at its best; blockchain technology and cryptocurrency; parallel processing in life science; quantum computers/computing; what's new with cloud computing for HPC; parallel programming models for extreme-scale computing; workflow management; machine learning and big data analytics; and deep learning and HPC.





Editors and Affiliations

  • University of Edinburgh, Edinburgh, UK

    Michèle Weiland

  • Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany

    Guido Juckeland

  • Technical University of Munich, Munich, Germany

    Carsten Trinitis

  • Ohio State University, Columbus, USA

    Ponnuswamy Sadayappan

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