High Performance Computing [[electronic resource] ] : ISC High Performance 2020 International Workshops, Frankfurt, Germany, June 21–25, 2020, Revised Selected Papers / / edited by Heike Jagode, Hartwig Anzt, Guido Juckeland, Hatem Ltaief

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
• Edizione: 1st ed. 2020.
• Descrizione fisica: 1 online resource (XI, 382 p. 181 illus., 104 illus. in color.)
• Disciplina: 004.3
• Soggetto topico: Computer engineering; Computer networks; Application software; Artificial intelligence; Computers; Software engineering; Computer Engineering and Networks; Computer and Information Systems Applications; Artificial Intelligence; Computing Milieux; Computer Communication Networks; Software Engineering
• Persona (resp. second.): JagodeHeike
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: 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 Log Data 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.
• Sommario/riassunto: 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.
• Titolo autorizzato: High Performance Computing
• ISBN: 3-030-59851-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996418310003316
• Lo trovi qui: Univ. di Salerno
• Serie: Theoretical Computer Science and General Issues, . 2512-2029 ; ; 12321