UID:
almahu_9949070725602882
Format:
VIII, 270 p. 118 illus., 106 illus. in color.
,
online resource.
Edition:
1st ed. 2021.
ISBN:
9783030660574
Content:
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.
Note:
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 Future-Capabilities 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 PAPI's 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 Cube's analysis capabilities with plugins -- Advanced Python Performance Monitoring with Score-P.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783030660567
Additional Edition:
Printed edition: ISBN 9783030660581
Additional Edition:
Printed edition: ISBN 9783030660598
Language:
English
DOI:
10.1007/978-3-030-66057-4
URL:
https://doi.org/10.1007/978-3-030-66057-4
URL:
Volltext
(URL des Erstveröffentlichers)
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