performance-engineering

Design, diagnose, and optimize software using user-facing performance budgets, systems analysis, representative measurement, hardware-aware algorithms, bounded allocation, numerical contracts, and SIMD. Use for slow code, latency, throughput, CPU or memory pressure, queues, capacity, performance reviews, new-system design, and regression prevention. Includes Rust and C++ guidance.

Version

1.1.0

License

MIT

Compatibility

Language-agnostic workflow. The bundled examples need a C++17 compiler; the Rust examples need Cargo. The scripts need Python 3.9+ and no third-party packages. AArch64/NEON paths require native AArch64 execution to be exercised. Every performance conclusion requires measurement on the consuming project's own workload and target CPUs.