End result is detailed_benchmark.php runtimes dropped from 2.1243s to 1.6017s on average or ~24.6% faster when PHP 7.2.12 was compiled with Profile Guided Optimization (PGO) training specifically for detailed_benchmark.php. When combined with optimised PGO runtime was slightly slower micro_bench.php performance (2.0907 vs 2.0510), the combined

We now have a unified infrastructure for writing profile-guided transformations, which will work either at offline-compile-time or in the JIT, but we don't have many transformations. We would welcome new profile-guided transformations as well as improvements to the current profiling system. Ideas for profile-guided transformations: Enabling Profile Guided Optimizations for PyPy without impacting the JIT performance is Profile Guided Optimization (PGO or profopt). I thank the PyPy developer community for their patience, kind advice and constant feedback they gave me in #pypy IRC or through email, which helped me to make Profile-Guided Optimization (PGO) is an excellent means to improve the performance of a compiled program. Indeed, the execution path data it provides helps the compiler to generate better code and To use profile-guided optimization, follow these steps to optimize your app: Compile one or more source code files with /GL. Each module built with /GL can be examined during profile-guided optimization test runs to capture run-time behavior. Every module in a profile-guided optimization build does not have to be compiled with /GL. » Python Performance Boost by using Profile Guided Optimization. Python Performance Boost by using Profile Guided Optimization. By using GCC PGO when building the Python interpreter, I've managed to achieve a healthy **10% speedup** for CPU bound Python programs. PGO (Profile guided optimization) is a runtime compiler optimization which leverages profile data collected from running important or performance centric user scenarios to build an optimized version of the applicati