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High Performance Computing

35th International Conference, ISC High Performance 2020, Frankfurt/Main, Germany, June 22–25, 2020, Proceedings

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Ponnuswamy Sadayappan

    1. School of Computing, University of Utah, Salt Lake City, USA

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  2. Bradford L. Chamberlain

    1. Cray, a Hewlett Packard Enterprise Company, Seattle, USA

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  3. Guido Juckeland

    1. Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany

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  4. Hatem Ltaief

    1. Extreme Computing Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12151)

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 2020.

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Table of contents (28 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. FASTHash: FPGA-Based High Throughput Parallel Hash Table

      • Yang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
      Pages 3-22

    3. Running a Pre-exascale, Geographically Distributed, Multi-cloud Scientific Simulation

      • Igor Sfiligoi, Frank Würthwein, Benedikt Riedel, David Schultz
      Pages 23-40

    4. Scalable Hierarchical Aggregation and Reduction Protocol (SHARP)TM Streaming-Aggregation Hardware Design and Evaluation

      • Richard L. Graham, Lion Levi, Devendar Burredy, Gil Bloch, Gilad Shainer, David Cho et al.
      Pages 41-59Open Access

  3. Artificial Intelligence and Machine Learning

    1. Front Matter

      Pages 61-61
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    2. Predicting Job Power Consumption Based on RJMS Submission Data in HPC Systems

      • Théo Saillant, Jean-Christophe Weill, Mathilde Mougeot
      Pages 63-82

    3. HyPar-Flow: Exploiting MPI and Keras for Scalable Hybrid-Parallel DNN Training with TensorFlow

      • Ammar Ahmad Awan, Arpan Jain, Quentin Anthony, Hari Subramoni, Dhabaleswar K. Panda
      Pages 83-103

    4. Time Series Mining at Petascale Performance

      • Amir Raoofy, Roman Karlstetter, Dai Yang, Carsten Trinitis, Martin Schulz
      Pages 104-123

  4. Data, Storage and Visualization

    1. Front Matter

      Pages 125-125
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    2. Shared-Memory Parallel Probabilistic Graphical Modeling Optimization: Comparison of Threads, OpenMP, and Data-Parallel Primitives

      • Talita Perciano, Colleen Heinemann, David Camp, Brenton Lessley, E. Wes Bethel
      Pages 127-145

    3. Opportunities for Cost Savings with In-Transit Visualization

      • James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki et al.
      Pages 146-165

    4. Semi-automatic Assessment of I/O Behavior by Inspecting the Individual Client-Node Timelines—An Explorative Study on \(10^{6}\) Jobs

      • Eugen Betke, Julian Kunkel
      Pages 166-184

  5. Emerging Technologies

    1. Front Matter

      Pages 185-185
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    2. Embedding Algorithms for Quantum Annealers with Chimera and Pegasus Connection Topologies

      • Stefanie Zbinden, Andreas Bärtschi, Hristo Djidjev, Stephan Eidenbenz
      Pages 187-206

  6. HPC Algorithms

    1. Front Matter

      Pages 207-207
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    2. Solving Acoustic Boundary Integral Equations Using High Performance Tile Low-Rank LU Factorization

      • Noha Al-Harthi, Rabab Alomairy, Kadir Akbudak, Rui Chen, Hatem Ltaief, Hakan Bagci et al.
      Pages 209-229Open Access

    3. DGEMM Using Tensor Cores, and Its Accurate and Reproducible Versions

      • Daichi Mukunoki, Katsuhisa Ozaki, Takeshi Ogita, Toshiyuki Imamura
      Pages 230-248

  7. HPC Applications

    1. Front Matter

      Pages 249-249
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    2. Using High-Level Synthesis to Implement the Matrix-Vector Multiplication on FPGA

      • Alessandro Marongiu, Paolo Palazzari
      Pages 251-269
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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 35th International Conference on High Performance Computing, ISC High Performance 2020, held in Frankfurt/Main, Germany, in June 2020.*

The 27 revised full papers presented were carefully reviewed and selected from 87 submissions. The papers cover a broad range of topics such as architectures, networks & infrastructure; artificial intelligence and machine learning; data, storage & visualization; emerging technologies; HPC algorithms; HPC applications; performance modeling & measurement; programming models & systems software.

*The conference was held virtually due to the COVID-19 pandemic.

Chapters "Scalable Hierarchical Aggregation and Reduction Protocol (SHARP) Streaming-Aggregation Hardware Design and Evaluation", "Solving Acoustic Boundary Integral Equations Using High Performance Tile Low-Rank LU Factorization", "Scaling Genomics Data Processing with Memory-Driven Computing to Accelerate Computational Biology", "Footprint-Aware Power Capping for Hybrid Memory Based Systems", and "Pattern-Aware Staging for Hybrid Memory Systems" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Editors and Affiliations

  • School of Computing, University of Utah, Salt Lake City, USA

    Ponnuswamy Sadayappan

  • Cray, a Hewlett Packard Enterprise Company, Seattle, USA

    Bradford L. Chamberlain

  • Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany

    Guido Juckeland

  • Extreme Computing Research Center, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia

    Hatem Ltaief

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