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024 7 _a10.1007/978-3-030-17872-7
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245 1 0 _aProgramming and Performance Visualization Tools
_h[electronic resource] :
_bInternational 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 /
_cedited by Abhinav Bhatele, David Boehme, Joshua A. Levine, Allen D. Malony, Martin Schulz.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXIV, 285 p. 166 illus., 105 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
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490 1 _aProgramming and Software Engineering,
_x2945-9168 ;
_v11027
520 _aThis 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. .
650 0 _aSoftware engineering.
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650 0 _aComputer engineering.
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650 0 _aComputer networks .
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650 0 _aLogic design.
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650 0 _aComputer programming.
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650 0 _aCompilers (Computer programs).
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650 0 _aPattern recognition systems.
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650 1 4 _aSoftware Engineering.
_94138
650 2 4 _aComputer Engineering and Networks.
_9110888
650 2 4 _aLogic Design.
_93686
650 2 4 _aProgramming Techniques.
_9110889
650 2 4 _aCompilers and Interpreters.
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650 2 4 _aAutomated Pattern Recognition.
_931568
700 1 _aBhatele, Abhinav.
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700 1 _aBoehme, David.
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700 1 _aLevine, Joshua A.
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700 1 _aMalony, Allen D.
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700 1 _aSchulz, Martin.
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776 0 8 _iPrinted edition:
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830 0 _aProgramming and Software Engineering,
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