m10-performance

Find Rust performance bottlenecks by running cargo bench to establish a baseline, then generate a flamegraph for the target hot path to visually locate code segments consuming the most execution time. This pinpoints exact lines needing optimization.

Optimize slow allocations and compute in Rust by applying memory- and cache-friendly techniques to critical paths identified during profiling, then re-benchmark with cargo bench to verify runtime reductions while preserving correctness.

Yes, you can use flamegraph and criterion to measure Rust performance improvements by locating hotspots and establishing baselines, allowing you to iteratively apply optimizations and verify execution gains through continuous benchmarking.

Yes, you need cargo bench to start optimizing Rust execution speed because it establishes the performance baseline required to measure the impact of any memory- or cache-friendly refactoring applied to the critical paths.

Your Rust code has slow runtime after profiling if memory- and cache-friendly techniques have not been applied to the critical paths, meaning the bottlenecks identified by the flamegraph still require iterative refactoring and re-benchmarking.