|
|
|
|
|
|
by vlovich123
719 days ago
|
|
|
Last I looked AutoFDO builds were similar in performance to PGO as ThinLTO vs LTO is. I’d say that collecting data with an instrumented Chrome build is extremely difficult - you’re relying on your synthetic benchmark environment which is very very different from the real world (eg extensions aren’t installed, the patterns of websites being browsed is not realistic, etc). There’s also a 2x compile cost because you have to build Chrome twice in the exact same way + you have to run a synthetic benchmark on each build to generate the trace. I’m just using an educated guess to say that at some point in the future Chrome will switch to AutoFDO, potentially using traces harvested from end user computers (potentially just from their employees even to avoid privacy complaints). |
|
|
Performance is also pretty different on the scales that performance engineers are interested in for these sorts of production codes, but without the build system scalability problems that LTO has. The original AutoFDO paper shows an improvement of 10.5%->12.5% going from AutoFDO to instrumented PGO. That is pretty big. It's probably even bigger with newer instrumentation based techniques like CSPGO.
They also mention the exact reasons that AutoFDO will not perform as well, with issues in debug info and losing profile accuracy due to sampling inaccuracy.
I couldn't find any numbers for Chrome, but I am reasonably certain that they have tried both and continue to use instrumented PGO for the extra couple percent. There are other pieces of the Chrome ecosystem (specifically the ChromeOS kernel) that are already optimized using sampling-based profiling. It's been a while since I last talked to the Chromium toolchain people about this though. I also remember hearing them benchmark FEPGO vs IRPGO at some point and concluding that IRPGO was better.