Performance Engineering Projects - Expanded Learning Guides
Performance Engineering Projects - Expanded Learning Guides
This directory contains comprehensive, expanded project guides for mastering performance engineering as a full-stack discipline.
Learning Path Overview
After completing these projects, you will understand:
- How to profile reality: sampling vs tracing, perf events, flamegraphs
- How to debug performance bugs: GDB, core dumps, post-mortem analysis
- How hardware really behaves: cache hierarchies, branch prediction, SIMD
- How to optimize latency: tail latency, queuing effects, lock contention
- How to validate improvements: benchmarking discipline, statistical rigor
Project Index
| # | Project | Difficulty | Focus Area | Time Estimate |
|---|---|---|---|---|
| 01 | Performance Baseline Lab | Beginner | Benchmarking & Measurement | Weekend |
| 02 | perf + Flamegraph Investigator | Intermediate | Profiling & Flamegraphs | 1-2 weeks |
| 03 | GDB + Core Dump Performance Autopsy | Intermediate | Debugging & Post-Mortem | 1-2 weeks |
| 04 | Cache Locality Visualizer | Advanced | CPU Caches & Memory | 1-2 weeks |
| 05 | Branch Predictor and Pipeline Lab | Advanced | CPU Microarchitecture | 1-2 weeks |
| 06 | SIMD Throughput Explorer | Expert | SIMD & Vectorization | 1 month+ |
| 07 | Latency Budget and Tail Latency Simulator | Intermediate | Latency Engineering | 1-2 weeks |
| 08 | Lock Contention and Concurrency Profiler | Advanced | Concurrency & Contention | 1-2 weeks |
| 09 | System Call and I/O Latency Profiler | Intermediate | I/O & Syscalls | 1-2 weeks |
| 10 | End-to-End Performance Regression Dashboard | Advanced | Performance Systems | 1 month+ |
| 11 | Full-Stack Performance Engineering Field Manual | Expert | Integration | 1 month+ |
Recommended Learning Path
Foundation Track (Start Here)
- Project 1: Performance Baseline Lab - Build measurement discipline
- Project 2: perf + Flamegraph Investigator - Learn CPU time attribution
Hardware Track
- Project 4: Cache Locality Visualizer
- Project 5: Branch Predictor and Pipeline Lab
- Project 6: SIMD Throughput Explorer
Debugging Track
- Project 3: GDB + Core Dump Performance Autopsy
Latency Track
- Project 7: Latency Budget and Tail Latency Simulator
- Project 8: Lock Contention and Concurrency Profiler
- Project 9: System Call and I/O Latency Profiler
Capstone
- Project 10: End-to-End Performance Regression Dashboard
- Project 11: Full-Stack Performance Engineering Field Manual
Core Reading Materials
| Book | Author | Focus |
|---|---|---|
| Systems Performance (2nd Ed) | Brendan Gregg | Methodology, Profiling, Tracing |
| Computer Systems: A Programmer’s Perspective | Bryant & O’Hallaron | Memory Hierarchy, CPU |
| Performance Analysis and Tuning on Modern CPUs | Agner Fog | Microarchitecture |
| The Linux Programming Interface | Michael Kerrisk | Syscalls, Debugging |
| Computer Architecture: A Quantitative Approach | Hennessy & Patterson | CPU Design, SIMD |
| The Art of Multiprocessor Programming | Herlihy & Shavit | Concurrency |
Tools You’ll Master
- perf: CPU profiling, hardware counters
- Flamegraphs: Visual profiling analysis
- GDB: Core dump analysis, thread debugging
- bpftrace/strace: System call tracing
- taskset/cpupower: CPU pinning and frequency control
- cachegrind: Cache simulation (optional)
The Five Pillars of Performance Engineering
- Measurement First - You cannot optimize what you cannot measure
- The Performance Triangle - CPU, Memory, I/O trade-offs
- The Latency Stack - Why small delays add up
- Hardware Reality - Caches, pipelines, SIMD
- Debugging Performance - Finding the real cause
Each project guide includes: learning objectives, deep theoretical foundation, complete specification, solution architecture, phased implementation guide, testing strategy, common pitfalls, and real-world connections.