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The Art of Writing Efficient Programs

You're reading from   The Art of Writing Efficient Programs An advanced programmer's guide to efficient hardware utilization and compiler optimizations using C++ examples

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781800208117
Length 464 pages
Edition 1st Edition
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Author (1):
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Fedor G. Pikus Fedor G. Pikus
Author Profile Icon Fedor G. Pikus
Fedor G. Pikus
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Table of Contents (18) Chapters Close

Preface 1. Section 1 – Performance Fundamentals
2. Chapter 1: Introduction to Performance and Concurrency FREE CHAPTER 3. Chapter 2: Performance Measurements 4. Chapter 3: CPU Architecture, Resources, and Performance 5. Chapter 4: Memory Architecture and Performance 6. Chapter 5: Threads, Memory, and Concurrency 7. Section 2 – Advanced Concurrency
8. Chapter 6: Concurrency and Performance 9. Chapter 7: Data Structures for Concurrency 10. Chapter 8: Concurrency in C++ 11. Section 3 – Designing and Coding High-Performance Programs
12. Chapter 9: High-Performance C++ 13. Chapter 10: Compiler Optimizations in C++ 14. Chapter 11: Undefined Behavior and Performance 15. Chapter 12: Design for Performance 16. Assessments 17. Other Books You May Enjoy

Chapter 2:

  1. Performance measurements are needed for two main reasons. First, they are used to define targets and describe the current status; without such measurements, we cannot say whether performance is poor or excellent; neither can we judge whether the performance targets are met. Second, measurements are used to study the effects of various factors on performance, evaluate the results of code changes and other optimizations.
  2. There is no single way to measure performance for all situations because there are usually too many contributing factors and causes to analyze using a single approach and because of the sheer volume of data that is needed to characterize the performance fully.
  3. Benchmarking done by manual instrumentation of the code has the advantage that it can collect any data you want, and it is easy to put the data in context: for each line of code, you know what function or step of the algorithm it belongs to. The main limitation is in the invasive nature...
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