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High Performance Computing de Heike Jagode

High Performance Computing: Lecture Notes in Computer Science, cartea 12761

Editat de Heike Jagode, Hartwig Anzt, Hatem Ltaief, Piotr Luszczek
en Limba Engleză Paperback – 13 noi 2021
This book constitutes the refereed post-conference proceedings of 9 workshops held at the 35th International ISC High Performance 2021 Conference, in Frankfurt, Germany, in June-July 2021:
Second International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis; HPC-IODC: HPC I/O in the Data Center Workshop; Compiler-assisted Correctness Checking and Performance Optimization for HPC; Machine Learning on HPC Systems;4th International Workshop on Interoperability of Supercomputing and Cloud Technologies;2nd International Workshop on Monitoring and Operational Data Analytics;16th Workshop on Virtualization in High­-Performance Cloud Computing; Deep Learning on Supercomputers; 5th International Workshop on In Situ Visualization.
The 35 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.
Chapter “Machine-Learning-Based Control of Perturbed and Heated Channel Flows” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

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Specificații

ISBN-13: 9783030905385
ISBN-10: 3030905381
Pagini: 532
Ilustrații: XIII, 515 p. 199 illus., 174 illus. in color.
Dimensiuni: 155 x 235 x 29 mm
Greutate: 0.8 kg
Ediția:1st ed. 2021
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Second International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis.- Machine-Learning-Based Control of Perturbed and Heated Channel Flows.- Novel DNNs for Stiff ODEs with Applications to Chemically Reacting Flows.- Lettuce: PyTorch-based Lattice Boltzmann Framework.- Reservoir computing in reduced order modeling for chaotic dynamical systems.- Film cooling prediction and optimization based on deconvolution neural network.- Turbomachinery Blade Surrogate Modeling using Deep Learning.- A Data-driven Wall-shear Stress Model for LES using Gradient Boosted Decision Trees.- Nonlinear mode decomposition and reduced-order modeling for three-dimensional cylinder flow by distributed learning on Fugaku.- Using physics-informed enhanced super-resolution generative adversarial networks to reconstruct mixture fraction statistics of turbulent jet flows.- HPC I/O in the Data Center.- Toward a Workflow for Identifying Jobs with Similar I/O Behavior Utilizing Time Series Analysis.- H3: An Application-Level, Low-Overhead Object Store.- Compiler-assisted Correctness Checking and Performance Optimization for HPC.- Automatic partitioning of MPI operations in MPI+OpenMP applications.- heimdallr: Improving Compile Time Correctness Checking for Message Passing with Rust.- Potential of Interpreter Specialization for Data Analysis.- Refactoring for Performance with Semantic Patching: Case Study with Recipes.- Negative Perceptions About the Applicability of Source-to-Source Compilers in HPC: A Literature Review.- Machine Learning on HPC Systems.- Automatic Tuning of Tensorflow's CPU Backend using Gradient-Free Optimization Algorithms.- MSM: Multi-Stage Multicuts for Scalable Image Clustering.- OmniOpt - a tool for hyperparameter optimization on HPC.- Parallel/distributed intelligent hyperparameters search for GANs.- Machine learning for generic energy models of high performance computing resources.- Fourth International Workshop on Interoperability of Supercomputing and Cloud Technologies.- Automation for Data-Driven Research with the NERSC Superfacility API.- A Middleware Supporting Data Movement inComplex and Software-Defined Storage andMemory Architectures.- Second International Workshop on Monitoring and Operational Data Analytics.- An Operational Data Collecting and Monitoring Platform for Fugaku: System Overviews and Case Studies in the Prelaunch Service Period.- An Explainable Model for Fault Detection in HPC Systems.- Sixteenth Workshop on Virtualization in High­-Performance Cloud Computing.- A Scalable Cloud Deployment Architecture for High-Performance Real-Time Online Interactive Applications.- Leveraging HW approximation for exploiting performance-energy trade-offs within the edge-cloud computing continuum.- Datashim and its applications in Bioinformatics.- FaaS and Curious: Performance implications of serverless functionson edge computing platforms.- Differentiated performance in NoSQL database access for hybrid Cloud-HPC workloads.- Deep Learning on Supercomputers.- JUWELS Booster - A Supercomputer for Large-Scale AI Research.- Fifth International Workshop on In Situ Visualization.- In Situ Visualization of WRF Data using Universal Data Junction.- Catalyst Revised: Rethinking the ParaView In Situ Analysis and Visualization API.- Fides: A General Purpose Data Model Library for Streaming Data.-Including in-situ visualization and analysis in PDI.-

Textul de pe ultima copertă

Chapter “Machine-Learning-Based Control of Perturbed and Heated Channel Flows” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.