High Performance Computing (eBook, PDF)

ISC High Performance 2020 International Workshops, Frankfurt, Germany, June 21-25, 2020, Revised Selected Papers
Redaktion: Jagode, Heike; Ltaief, Hatem; Juckeland, Guido; Anzt, Hartwig

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 382
• Erscheinungstermin: 19. Oktober 2020
• Englisch
• ISBN-13: 9783030598518
• Artikelnr.: 62290898

Inhaltsangabe

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.