Enable -fno-reciprocal-math to fix div accuracy.

[SanityRemnants]

Added -fno-reciprocal-math to SYCL_KERNEL_OPTIONS to eliminate issues with division of the number by itself returning non 1 output which caused: #1895.

[Copilot]

Pull request overview

This PR addresses a division accuracy issue in SYCL kernels where dividing a number by itself could return non-1 results. The fix adds the -fno-reciprocal-math compiler flag to disable reciprocal math optimizations that can introduce numerical inaccuracies.

Key Changes:

• Added -fno-reciprocal-math to SYCL_KERNEL_OPTIONS to prevent compiler optimizations that replace division operations with multiplication by reciprocals

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[riverliuintel]

@CuiYifeng

[SanityRemnants]

Currently evaluating the use of a more localized approach using #pragma clang fp reciprocal(off) to minimize the impact on performance. Do not merge for now.

[EikanWang]

Let's study the NVCC behaviors first. I think reciprocal-math is a general optimization, and most the compilers enable it by default.

[SanityRemnants]

@EikanWang I believe --prec-div https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html?highlight=reciprocal#prec-div-true-false-prec-div is the corresponding NVCC flag by default set to True unless --use_fast_math (https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html?highlight=reciprocal#use-fast-math-use-fast-math) is set to True. I do not believe pytorch is built with --use_fast_math correct me if I'm wrong.

[SanityRemnants]

There are a few options regarding #pragma clang fp reciprocal(off) (https://clang.llvm.org/docs/LanguageExtensions.html#extensions-to-specify-floating-point-flags) with the least invasive being adding it only to the BinaryDivTrueKernel.cpp file. However, I'm not sure whether it's worth it to sacrifice some performance for accuracy in this oddly specific use case (calling div first and than trunc instead of div_trunc) for which we have no known business need outside the failing UT. Both the div and div_trunc results are within needed norms. It might be better to modify the UT. What is your opinion on that @EikanWang?