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Programming and Performance Visualization Tools - International Workshops, ESPT 2017 and VPA 2017, Denver, CO, USA, November 12 and 17, 2017, and ESPT 2018 and VPA 2018, Dallas, TX, USA, November 16 and 11, 2018, Revised Selected Papers (Paperback, 1st ed. 2019)
Abhinav Bhatele, David Boehme, Joshua A. Levine, Allen D. Malony, Martin Schulz
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R1,793
Discovery Miles 17 930
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Ships in 10 - 15 working days
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This book contains the revised selected papers of 4 workshops held
in conjunction with the International Conference on High
Performance Computing, Networking, Storage and Analysis (SC) in
November 2017 in Denver, CO, USA, and in November 2018 in Dallas,
TX, USA: the 6th and 7th International Workshop on Extreme-Scale
Programming Tools, ESPT 2017 and ESPT 2018, and the 4th and 5th
International Workshop on Visual Performance Analysis, VPA 2017 and
VPA 2018. The 11 full papers of ESPT 2017 and ESPT 2018 and the 6
full papers of VPA 2017 and VPA 2018 were carefully reviewed and
selected for inclusion in this book. The papers discuss the
requirements for exascale-enabled tools as well as new approaches
of applying visualization and visual analytic techniques to
large-scale applications. Topics of interest include: programming
tools; methodologies for performance engineering; tool technologies
for extreme-scale challenges (e.g., scalability, resilience,
power); tool support for accelerated architectures and large-scale
multi-cores; tool infrastructures and environments; evolving/future
application requirements for programming tools and technologies;
application developer experiences with programming and performance
tools; scalable displays of performance data; case studies
demonstrating the use of performance visualization in practice;
data models to enable scalable visualization; graph representation
of unstructured performance data; presentation of high-dimensional
data; visual correlations between multiple data sources;
human-computer interfaces for exploring performance data; and
multi-scale representations of performance data for visual
exploration.
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