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Tools for High Performance Computing 2018 / 2019: Proceedings of the 12th and of the 13th International Workshop on Parallel Tools for High Performance Computing, Stuttgart, Germany, September 2018, and Dresden, Germany, September 2019 2021 ed. [Minkštas viršelis]

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  • Formatas: Paperback / softback, 270 pages, aukštis x plotis: 235x155 mm, weight: 433 g, 106 Illustrations, color; 12 Illustrations, black and white; VIII, 270 p. 118 illus., 106 illus. in color., 1 Paperback / softback
  • Išleidimo metai: 24-May-2022
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030660591
  • ISBN-13: 9783030660598
  • Formatas: Paperback / softback, 270 pages, aukštis x plotis: 235x155 mm, weight: 433 g, 106 Illustrations, color; 12 Illustrations, black and white; VIII, 270 p. 118 illus., 106 illus. in color., 1 Paperback / softback
  • Išleidimo metai: 24-May-2022
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030660591
  • ISBN-13: 9783030660598

This book presents the proceedings of the 12th International Parallel Tools Workshop, held in Stuttgart, Germany, during September 17-18, 2018, and of the 13th International Parallel Tools Workshop, held in Dresden, Germany, during September 2-3, 2019. The workshops are a forum to discuss the latest advances in parallel tools for high-performance computing. 

High-performance computing plays an increasingly important role for numerical simulation and modeling in academic and industrial research. At the same time, using large-scale parallel systems efficiently is becoming more difficult. A number of tools addressing parallel program development and analysis has emerged from the high-performance computing community over the last decade, and what may have started as a collection of a small helper scripts has now matured into production-grade frameworks. Powerful user interfaces and an extensive body of documentation together create a user-friendly environment for parallel tools.



Detecting disaster before it strikes: On the challenges of automated
building and testing in HPC environments.- Saving Energy Using the READEX
Methodology.- The MPI Tool Interfaces: Past, Present, and FutureCapabilities
and Prospects.- A tool for runtime analysis of performance and energy usage
in NUMA systems.- Usage experiences of performance tools for modern C++ code
analysis and optimization.- Performance Analysis of Complex
Engineering Frameworks.- System-wide Low-frequency Sampling for Large HPC
Systems.- Exploring Space-Time Trade-Off in Backtraces.- Enabling Performance
Analysis of Kokkos Applications with Score-P.- Regional Profiling for
Efficient Performance Optimization.- Effortless Monitoring of Arithmetic
Intensity with PAPIs Counter Analysis Toolkit.- ONE View: a fully automatic
method for aggregating key performance metrics and providing users with a
synthetic view of HPC applications.- A picture is worth a thousand numbers
 Enhancing Cubes analysis capabilities with plugins.- Advanced Python
Performance Monitoring with Score-P.