Profile guided optimization with gcc

Yesterday I wrote how certain build optimizations can have performance differences – and I decided to step a bit deeper into a quite interesting field – profile guided binary optimization. There’re quite a few interesting projects out there, like LLVM (I hear it is used extensively in iphone?) – which analyze run-time profile of compiled code and can do just in time adjustments of binary code. Apparently, you don’t need that fancy technology, and can use plain old gcc.

The whole plan is:

  1. Compile all code with -fprofile-generate in {C|CXX|LD}FLAGS
  2. Run the binary
  3. Run your application/benchmark against that binary
  4. Recompile all code with -fprofile-use (above steps will place lots of .gcda files in source tree)
  5. PROFIT!!! (note the omission of “???” step)

How much profit? I measured ~7% of sysbench performance increase (and probably would see much higher value in CPU-tight benchmarks). YMMV. Can such PGO be useful for every user out there? Maybe – but the best results are achieved once looking at actual use patterns – though of course, lots of them are similar everywhere around.

Also, I am showing the actual profiling process with too much of pink. Apparently gcc/gcov profiles tend to get corrupted in multithreaded applications, so I did multiple profile/build passes, until I managed to assemble final binary. :-)

Now I have to figure out how to use -combine flag in gcc, and treat whole MySQL codebase as one huge .c file (apparently compilers can make much much better decisions then).