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008			230909s2023 si | o |||| 0|eng d
020			_a9789819943661
024	7		_a10.1007/978-981-99-4366-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.88 _b2023 EB
100	1		_aZhai, Jidong _eautor _9689680
245	1	0	_aPerformance Analysis of Parallel Applications for HPC _cby Jidong Zhai, Yuyang Jin, Wenguang Chen, Weimin Zheng
250			_a1st ed 2023
264		1	_aSingapore _bSpringer Nature _c2023
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
505	0		_aChapter 1. Background and Overview -- Part I. Performance Analysis Methods: Communication Analysis -- Chapter 2. Fast Communication Trace Collection -- Chapter 3. Structure-Based Communication Trace Compression -- Part II. Performance Analysis Methods: Memory Analysis -- Chapter 4. Informed Memory Access Monitoring -- Part III. Performance Analysis Methods: Scalability Analysis -- Chapter 5. Graph Analysis for Scalability Analysis -- Chapter 6. Performance Prediction for Scalability Analysis -- Part IV. Performance Analysis Methods: Noise Analysis -- Chapter 7. Lightweight Noise Detection -- Chapter 8. Production-Run Noise Detection -- Part V. Performance Analysis Framework -- Chapter 9. Domain-Specific Framework for Performance Analysis -- Chapter 10. Conclusion and Future Work.
520			_aThis book presents a hybrid static-dynamic approach for efficient performance analysis of parallel applications on HPC systems. Performance analysis is essential to finding performance bottlenecks and understanding the performance behaviors of parallel applications on HPC systems. However, current performance analysis techniques usually incur significant overhead. Our book introduces a series of approaches for lightweight performance analysis. We combine static and dynamic analysis to reduce the overhead of performance analysis. Based on this hybrid static-dynamic approach, we then propose several innovative techniques for various performance analysis scenarios, including communication analysis, memory analysis, noise analysis, computation analysis, and scalability analysis. Through these specific performance analysis techniques, we convey to readers the idea of using static analysis to support dynamic analysis. To gain the most from the book, readers should have a basic grasp of parallel computing, computer architecture, and compilation techniques.
988			_aSpringer_Computer_2023
650		7	_2embne _9468437 _aComputación de altas prestaciones
700	1		_9689681 _aJin, Yuyang _eautor
700			_9100805 _aChen, Wenguang _eautor
700	1		_9689682 _aZheng, Weimin _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-99-4366-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2024 _dz _eb _zSI