Hello, I have been playing around with the profile guided optimization flags in GCC and had a few questions. I actually noticed that with the particular application I was profiling, I in some cases got worse results after recompiling with -fprofile-use and re-running the same test I used to generate the profile. I could not find any detailed documentation about how the profile is applied during the optimization steps, but my working hypothesis is as follows. The application in question is very latency sensitive, so it spins in a tight loop while polling for data from various sources. When data is received, it then processes it – and this processing is the portion in which speed is most important and which I am timing. If one were to look at hit counts for individual functions or source lines, though, it would appear that the polling loop was “hot” while everything else by comparison was extremely “cold”. Global optimizations that use this sort of data would then likely hurt, rather than help those processing times. What optimizations does -fprofile-use turn on that would be sensitive to this sort of behavior? Does this seem like a reasonable explanation, and if so is there anything I can tweak to help? The specific flags that -fprofile-use turns on (-fbranch-probabilities, -fvpt, -funroll-loops, -fpeel-loops and –ftracer) don’t seem like they would be affected since these optimizations appear local in scope, but I assume there are other things happening under the hood. Regards, Paul
