Bytes before FLOPS: your algorithm is (mostly) fine, your data isn't
13 hours ago
- #data-oriented-design
- #optimization
- #performance
- Profile your code before optimizing to identify real bottlenecks.
- Specialize algorithms to fit your data for better performance.
- Optimize data access patterns to be cache-friendly.
- Use SIMD instructions for vectorization where possible.
- Parallelize processing for additional speed gains.
- Be aware of false sharing in multithreaded scenarios.
- Consider data layout and structure padding for cache efficiency.
- Use tools like hyperfine, perf, VTune, and godbolt.org for analysis.
- Scripting languages may not fit high-performance needs; prefer systems languages like C/C++/Rust.