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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.
This book constitutes the refereed proceedings of the 36th International Conference on High Performance Computing, ISC High Performance 2021, held virtually in June/July 2021.The 24 full papers presented were carefully reviewed and selected from 74 submissions. The papers cover a broad range of topics such as architecture, networks, and storage; machine learning, AI, and emerging technologies; HPC algorithms and applications; performance modeling, evaluation, and analysis; and programming environments and systems software.
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.
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.
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