1. Profile your code to identify performance bottlenecks.
2. Refactor code for readability and maintainability.
3. Minimize the number of data access operations.
4. Use appropriate data structures and algorithms.
5. Leverage hardware features like SIMD instructions.
6. Pre-allocate memory and minimize dynamic allocations.
7. Utilize caching, parallel optimization, and vectorization.
8. Avoid synchronization, if possible.
9. Use optimized libraries whenever possible.
10. Learn low-level optimization techniques such as LTO, ASM, and JIT.