This book constitutes the refereed conference proceedings of the workshops held at the 37th International ISC High Performance 2022 Conference, in Hamburg, Germany, in June 2, 2022. The 27 full papers were included in this book were carefully reviewed and selected from 43 submissions. ISC High Performance 2022 presents the following workshops: Compiler-assisted Correctness Checking and Performance Optimization for HPC HPC on Heterogeneous Hardware (H3) Malleability Techniques Applications in High Performance Computing Fifth Workshop on Interactive High Performance Computing 3rd ISC HPC International Workshop on Monitoring & Operational Data Analytics 6th International Workshop on In Situ Visualization 17th Workshop on Virtualization in High Performance Cloud Computing

This book constitutes the refereed proceedings of the 37th International Conference on High Performance Computing, ISC High Performance 2022, held in Hamburg, Germany, during May 29 - June 2, 2022. The 18 full papers presented were carefully reviewed and selected from 53 submissions. The papers are categorized into the following topical sub-headings: Architecture, Networks, and Storage; Machine Learning, AI, 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 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.

With new processor families appearing every few years, it is increasingly harder to achieve high performance rates in sparse matrix computations. This monograph studies new methods for sparse matrix factorizations and applies them efficiently while retaining ease of use of existing solutions. The implementations are timed and analyzed using a commonly accepted set of test matrices. Contemporary processors are used for the tests. The new factorization techniques are proven to be quite competitive with state of the art software. In addition, an optimization effort is applied to an iterative algorithm that stands out for its numerical robustness. This also gives satisfactory results on the tested computing platforms in terms of performance improvement. The same set of test matrices is used to enable an easy comparison between both investigated techniques, even though they are customarily treated separately in the literature. Possible extensions of the presented work range from easily conceivable merging with existing solutions to rather more evolved schemes dependent on hard to predict progress in theoretical and algorithmic research.