Still, the general point is good. last time I tried ICC on a heavily vectorized (with intrinsics) program, ICC was a 30% boost over clang or gcc.
The Ubuntu packages I'm using are compiled appear to have been compiled to support AVX, but not AVX2, and hence no FMA. So while GCC and Clang are much slower, this is really an issue of having suboptimal system libraries. The speedup is real, but it's not clear that either GCC or Clang are actually to blame.
When I can get g++ to use Intel's libimf instead of glibc's libm, it's only ~5% slower than icpc. I'd guess much of the remaining difference is function call overhead vs inlining. Clang still lags by another 10%, but I think that's probably because I haven't figured out quite the right incantation to get it to use libimf without also disabling some other useful optimization.
Here are the commands that I ended up with:
clang++ -fno-finite-math-only -march=native -Wall -Wextra -g -O3 option.cc -o option -Wl,-rpath=/opt/intel/compilers_and_libraries/linux/lib/intel64 -L/opt/intel/compilers_and_libraries/linux/lib/intel64 -limf -lintlc
g++ -fno-finite-math-only -march=native -Wall -Wextra -g -Ofast option.cc -o option -Wl,-rpath=/opt/intel/compilers_and_libraries/linux/lib/intel64 -L/opt/intel/compilers_and_libraries/linux/lib/intel64 -limf -lintlc
icpc -march=native -Wall -Wextra -g -Ofast option.cc -o option
The "-fno-finite-math-only" disables an otherwise good clang++ and g++ optimization that requires a __finite_exp() function that libimf does not have. clang++ seems to also need to switch from -Ofast to -O3 to make this stick.
What I don't know yet is whether recompiling glibc (or upgrading to the most recent glibc) will produce better performance out-of-the-box on recent Intel. My searches aren't turning up much information --- anyone know?
gcc and clang will vectorize that, but not exp / log
I don't know how well it's currently working, but it looks like this might have changed recently: https://sourceware.org/glibc/wiki/libmvec
In the answers, I think Peter covers most of the likely attacks. One that isn't mentioned is "choosing the wrong compiler". Not just compiler options, but compiler. While there isn't a "best" compiler for everything, for a given program often one will perform better than the others. Especially if one is targetting recent Intel CPUs, Intel's compiler can occasionally beat GCC and Clang by surprisingly large amounts. This appears to be one of those times.
Here are the times I see for for this example on a 3.4 GHz Skylake running 64-bit Linux when compiled with different modern compilers:
All were compiled with "-march=native -g -Ofast", which I think causes all of the compilers to use the equivalent of "-ffast-math". At least, I'm pretty sure icpc uses it by default, and I didn't see any difference in performance when I added "-ffast-math" or "-funsafe-math-optimizations" to clang++ and g++. So in this case, I (provocatively) would suggest that using clang++ or g++ would be a subtle 2x deoptimization. There are definitely reasons to prefer them, but for this example that choice looks to come at a large cost in performance.If you want to do your own comparison, Version 17 of the Intel compiler is currently available as a free beta for Windows, Mac, and Linux: https://software.intel.com/en-us/articles/intel-parallel-stu.... I don't know how they are defining the license duration, but when I downloaded yesterday it gave me a license valid until October 2016. Separately, I'd be interested to see what MSVC does with this on a comparable machine.