LEADER 03470oam 22004815 450 001 996550559803316 005 20231220164620.0 010 $a981-9943-66-3 024 7 $a10.1007/978-981-99-4366-1 035 $a(MiAaPQ)EBC30736802 035 $a(Au-PeEL)EBL30736802 035 $a(DE-He213)978-981-99-4366-1 035 $a(PPN)272740748 035 $a(EXLCZ)9928172724000041 100 $a20230909d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPerformance analysis of parallel applications for HPC /$fJidong Zhai, Yuyang Jin, Wenguang Chen, Weimin Zheng 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (xv, 256 pages) $cillustrations 311 08$aPrint version: Zhai, Jidong Performance Analysis of Parallel Applications for HPC Singapore : Springer,c2023 9789819943654 327 $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. 330 $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. 606 $aHigh performance computing 606 $aParallel programs (Computer programs) 615 0$aHigh performance computing. 615 0$aParallel programs (Computer programs) 676 $a004.35 700 $aZhai$b Jidong$01427800 701 $aJin$b Yuyang$01427801 701 $aChen$b Wenguang$01427802 701 $aZheng$b Weimin$01427803 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996550559803316 996 $aPerformance Analysis of Parallel Applications for HPC$93562734 997 $aUNISA