High Performance Computing: ISC High Performance 2020 International Workshops, Frankfurt, Germany, June 21-25, 2020, Revised Selected Papers

by Heike Jagode (Editor), Hartwig Anzt (Editor), Guido Juckeland (Editor), Hatem Ltaief (Editor)

Overview

This book constitutes the refereed post-conference proceedings of 10 workshops held at the 35th International ISC High Performance 2020 Conference, in Frankfurt, Germany, in June 2020:
First Workshop on Compiler-assisted Correctness Checking and Performance Optimization for HPC (C3PO); First International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics Simulations and Analysis (CFDML); HPC I/O in the Data Center Workshop (HPC-IODC); First Workshop \Machine Learning on HPC Systems" (MLHPCS); First International Workshop on Monitoring and Data Analytics (MODA); 15th Workshop on Virtualization in High-Performance Cloud Computing (VHPC).

The 25 full papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include high-performance computing (HPC), computer architecture and hardware,programming models, system software, performance analysis and modeling, compiler analysis and optimization techniques, software sustainability, scientific applications, deep learning.

Product Details

ISBN-13:	9783030598518
Publisher:	Springer-Verlag New York, LLC
Publication date:	10/19/2020
Series:	Lecture Notes in Computer Science , #12321
Sold by:	Barnes & Noble
Format:	eBook
File size:	36 MB
Note:	This product may take a few minutes to download.

Table of Contents

Checking and Performance Optimization for HPC (C3PO'20).- Compiler-assisted type-safe checkpointing.- Static analysis to enhance programmability and performance in OmpSs-2 21 Automatic detection of MPI assertions.- Automatic Code Motion to Extend MPI Nonblocking Overlap Window.- First International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics Simulations and Analysis (CFDML) .-Complete Deep Computer-Vision Methodology for Investigating Hydrodynamic Instabilities.- Prediction of Acoustic Fields using a Lattice-Boltzmann Method and Deep Learning.- Unsupervised Learning of Particle Image Velocimetry.- Reduced order modeling of dynamical systems using arti cial neural networks applied to water circulation.- Parameter Identification of RANS turbulence model using Physics-embedded neural network.- Investigating the Overhead of the REST Protocol when Using Cloud Services for HPC Storage.- Characterizing I/O Optimization E ect Through Holistic LogData Analysis of Parallel File Systems and Interconnects.- The Importance of Temporal Behavior when Classifying Job IO Patterns Using Machine Learning Techniques.- GOPHER, an HPC framework for large scale graph exploration and inference.- Ensembles of Networks Produced from Neural Architecture Search.- SmartPred: Unsupervised Hard Disk Failure Detection.- Application IO analysis with Lustre Monitoring using LASSi for ARCHER.- Characterizing HPC Performance Variation with Monitoring and Unsupervised Learning.- Service Function Chaining Based on Segment Routing Using P4 and SR-IOV (P4-SFC) .- Seamlessly managing HPC workloads through Kubernetes.- Interference-aware Orchestration in Kubernetes.- RustyHermit: A Scalable, Rust-based Virtual Execution Environment.- Rootless Containers with Podman for HPC.- Bioinformatics application with Kube ow for batch processing in clouds.- Converging HPC, Big Data and Cloud technologies for precision agriculture data analytics on supercomputers.