Performance Analysis of Parallel Applications for HPC
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Product details:
- Edition number 2023
- Publisher Springer
- Date of Publication 10 September 2023
- Number of Volumes 1 pieces, Book
- ISBN 9789819943654
- Binding Hardback
- No. of pages256 pages
- Size 235x155 mm
- Weight 576 g
- Language English
- Illustrations 1 Illustrations, black & white 544
Categories
Short description:
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 graspof parallel computing, computer architecture, and compilation techniques.
Long description:
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 basicgrasp of parallel computing, computer architecture, and compilation techniques.
Table of Contents:
Chapter 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.
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