Program Performance Profiling and Benchmarking
Measuring how fast and resource-efficient a program is -- via profiling to locate hotspots and benchmarking to compare execution time, memory, or throughput under controlled workloads. This Idea covers the metrics and methodology used to quantify performance and to verify that a proposed optimization is both correct and genuinely faster, the yardstick against which language-model code optimizations are judged.
Questions this Concept answers
- Why does changing several things at once between two measured runs spoil the comparison?
Benchmarking Function Runtime with the timeit Module in Python
Software profiling is the collection and analysis of measurements from a running program in order to locate performance bottlenecks (hotspots); it is diagnostic rather than prescriptive, identifying …