dendibakh/perf-ninja resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

3825 stars · 395 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

An online course in the form of C++ lab assignments for learning low-level performance analysis and tuning, covering issues like CPU cache misses and branch mispredictions. Solutions are submitted to GitHub for automated benchmarking and verification across modern Intel, AMD, and Apple hardware.

Use cases

• learn low-level performance analysis and tuning
• practice fixing CPU cache misses
• learn to fix branch mispredictions
• improve C++ code performance through hands-on labs
• learn vectorization and compiler intrinsics
• benchmark code optimizations on modern CPUs

When to choose

• you want hands-on practice optimizing C++ code performance
• you want to learn performance analysis on modern Intel, AMD, or Apple hardware
• you prefer learning through lab assignments and videos rather than theory alone

When to avoid

• you don't know basic C++
• you need a tool or library rather than a course
• you need a formally licensed open-source project (the repo has no license)

Facets

learning-resource · maturity active

benchmarking developer-tools performance tutorials developer-tools windows cpp performance-analysis cpu-optimization course lab-assignments low-level-optimization computer-architecture linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="dendibakh/perf-ninja")