Table of Contents

Part I: Foundations - Benchmarking Methodology

Chapter 1: Why Benchmarking is Hard
Chapter 2: Setting Up Your Measurement Environment
Chapter 3: Measurement Methodology
Chapter 4: Presenting Results

Part II: Tools - Classic Benchmarks & Profiling

Chapter 5: CPU Benchmarks
Chapter 6: Memory Benchmarks
Chapter 7: System-Level Benchmarks
Chapter 8: Profiling Tools
Chapter 9: Embedded & RTOS Benchmarks

Part III: Theory - Performance Modeling

Chapter 10: Performance Modeling
Chapter 11: Galactic Algorithms
Chapter 12: Cache & Branch Prediction

Part IV: Data Structures & Algorithms

Chapter 13: Array vs Linked List
Chapter 14: Hash Table vs Tree
Chapter 15: Sorting Algorithms

Part V: Parallelism & Low-Level Optimization

Chapter 16: SIMD & Vectorization
Chapter 17: Multi-core Performance
Chapter 18: Memory Allocators

Part VI: Embedded Constraints

Chapter 19: Footprint Analysis Fundamentals
Chapter 20: Compiler Size Optimization
Chapter 21: Stack Analysis and Estimation
Chapter 22: RTOS Footprint Case Study

Part VII: AI/HPC Performance

Chapter 23: Evolution of Performance Metrics
Chapter 24: AI/ML Benchmarks
Chapter 25: HPC Benchmarks
Chapter 26: GPU Benchmarking
Chapter 27: LLM Performance Analysis
Chapter 28: ML Compilers and Runtime
Chapter 29: Edge AI Performance

Part VIII: Case Studies

Chapter 30: Case Study: Web Server Optimization
Chapter 31: Case Study: Database Query Optimization
Chapter 32: Case Study: ML Inference Optimization

Part IX: Synthesis

Chapter 33: How to Benchmark
Chapter 34: How to Optimize
Chapter 35: CI/CD for Performance

Appendices

Appendix A: Benchmark Automation
Appendix B: Embedded and RTOS Implementation
Appendix C: I/O and Storage Performance
Appendix D: Power and Performance
Appendix E: Exercises and Solutions
Appendix F: Environment Setup Guide
Appendix G: Further Reading
Appendix H: Performance Models Deep Dive