Can I make my compiler use fast-math on a per-function basis?

Question

Suppose I have

template <bool UsesFastMath> void foo(float* data, size_t length);

and I want to compile one instantiation with -ffast-math (--use-fast-math for nvcc), and the other instantiation without it.

This can be achieved by instantiating each of the variants in a separate translation unit, and compiling each of them with a different command-line - with and without the switch.

My question is whether it's possible to indicate to popular compilers (*) to apply or not apply -ffast-math for individual functions - so that I'll be able to have my instantiations in the same translation unit.

Notes:

• If the answer is "no", bonus points for explaining why not.
• This is not the same questions as this one, which is about turning fast-math on and off at runtime. I'm much more modest...

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(*) by popular compilers I mean any of: gcc, clang, msvc icc, nvcc (for GPU kernel code) about which you have that information.

Answer 1

As of CUDA 7.5 (the latest version I am familiar with, although CUDA 8.0 is currently shipping), nvcc does not support function attributes that allow programmers to apply specific compiler optimizations on a per-function basis.

Since optimization configurations set via command line switches apply to the entire compilation unit, one possible approach is to use as many different compilation units as there are different optimization configurations, as already noted in the question; source code may be shared and #include-ed from a common file.

With nvcc, the command line switch --use_fast_math basically controls three areas of functionality:

• Flush-to-zero mode is enabled (that is, denormal support is disabled)
• Single-precision reciprocal, division, and square root are switched to approximate versions
• Certain standard math functions are replaced by equivalent, lower-precision, intrinsics

You can apply some of these changes with per-operation granularity by using appropriate intrinsics, others by using PTX inline assembly.