Zhai J., Jin Y., Chen W., Zheng W. Performance Analysis of Parallel Applications for HPC

Springer, 2023. — 259 p. — ISBN: 978-981-99-4365-4.This 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.Background and Overview.
Performance Analysis Methods: Communication Analysis
Fast Communication Trace Collection.
Structure-Based Communication Trace Compression.
Performance Analysis Methods: Memory Analysis
Informed Memory Access Monitoring.
Performance Analysis Methods: Scalability Analysis
Graph Analysis for Scalability Analysis.
Performance Prediction for Scalability Analysis.
Performance Analysis Methods: Noise Analysis
Lightweight Noise Detection.
Production-Run Noise Detection.
Performance Analysis Framework
Domain-Specific Framework for Performance Analysis.
Conclusion and Future Work.