GCC: compilation of the AVX512 commands fails (Werror=uninitialized)

[bulvara]

Dear devs,
I'm using ArchLinux (gcc=default) on AMD Ryzen, so I don't even need AVX512 commands.

Here is an example error message with GCC:

In Funktion »__m512i _mm512_inserti64x4(__m512i, __m256i, int)«,
    eingefügt von »__m512i fbgemm::internal::permute_row(__m512i)« bei ./pytorch/third_party/fbgemm/src/UtilsAvx512.cc:606:28,
    eingefügt von »void fbgemm::internal::core_transpose_16x32_block_i8(__m512i*, __m512i*)« bei ./pytorch/third_party/fbgemm/src/UtilsAvx512.cc:665:21,
    eingefügt von »void fbgemm::internal::transpose_16x32_block(const uint8_t*, int, uint8_t*, int, int, int) [mit bool MREM = false; bool NREM = true]« bei ./pytorch/third_party/fbgemm/src/UtilsAvx512.cc:937:32:
/usr/lib/gcc/x86_64-pc-linux-gnu/12.0.1/include/avx512fintrin.h:6137:10: Fehler: »__Y« ist nicht initialisiert, wird aber benutzt [-Werror=uninitialized]
 6137 |   return (__m512i) __builtin_ia32_inserti64x4_mask ((__v8di) __A,
      |          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 6138 |                                                     (__v4di) __B,
      |                                                     ~~~~~~~~~~~~~
 6139 |                                                     __imm,
      |                                                     ~~~~~~
 6140 |                                                     (__v8di)
      |                                                     ~~~~~~~~
 6141 |                                                     _mm512_undefined_epi32 (),
      |                                                     ~~~~~~~~~~~~~~~~~~~~~~~~~~
 6142 |                                                     (__mmask8) -1);
      |                                                     ~~~~~~~~~~~~~~
/usr/lib/gcc/x86_64-pc-linux-gnu/12.0.1/include/avx512fintrin.h: In Funktion »void fbgemm::internal::transpose_16x32_block(const uint8_t*, int, uint8_t*, int, int, int) [mit bool MREM = false; bool NREM = true]«:
/usr/lib/gcc/x86_64-pc-linux-gnu/12.0.1/include/avx512fintrin.h:206:11: Anmerkung: »__Y« wurde hier deklariert
  206 |   __m512i __Y = __Y;
      |           ^~~

When using Clang instead the configure step fails because AVX512 intrinsics are disabled when compiling with -march=native on my platform.

Is there any way to completely patch out AVX512?

[jianyuh]

Could you share the build command? Currently FBGEMM (CPU) primarily supports Intel CPUs. For AMD CPUs (e.g., Ryzen with only AVX2 supports), we can possibly remove those fbgemm_avx512 build (e.g.,

FBGEMM/CMakeLists.txt

Line 127 in 06c6369

target_compile_options(fbgemm_avx512 PRIVATE

).

[bulvara]

I'm building pytorch after https://github.com/archlinux/svntogit-community/blob/packages/python-pytorch/trunk/PKGBUILD

Is setup.py using BUILD.bazel or CMakeLists.txt ? I've tried to patch the bazel file, but a myriad of deletions is necessary there.

[Bidski]

I am also seeing this error. I have an Intel CPU.

[jianyuh]

@Bidski : do you have more information on the Intel CPU and the compiler you have? We currently require a Intel CPU after Broadwell (AVX2) and a compiler supporting AVX512.

[Bidski]

@jianyuh my apologies, it's been a long day and I forgot I was working on a remote PC 😟

I am actually experiencing this issue on an AMD CPU. Is it possible to build this on an AMD CPU?

I will test further on an Intel CPU tomorrow to confirm that it isn't affected.

[ankurvdev]

I'm seeing this on fedora 36 gcc-12.1

[kgizdov]

Should work with:

  export CFLAGS+=" -Wno-error=maybe-uninitialized -Wno-error=uninitialized -Wno-error=restrict"
  export CXXFLAGS+=" -Wno-error=maybe-uninitialized -Wno-error=uninitialized -Wno-error=restrict"

[Bidski]

@jianyuh Intel CPU build seems fine, sorry for the alarm

The CFLAGS and CXXFLAGS suggested by @kgizdov do allow the build to succeed on the AMD CPU.

[ankurvdev]

This is a GCC regression. Here's the bug for reference.
https://gcc.gnu.org/bugzilla/show_bug.cgi?id=105593

[mjanderson09]

@bulvara did the above fix regarding CFLAGS and CXXFLAGS work for you?

[lindsayad]

This was a saving thread for me, thank you. Although I had to remember that simply re-running cmake (at the pytorch build level in my case) with a different CXXFLAGS in my environment does not reconfigure with a different CXXFLAGS. I had to make sure to clean everything first before re-running cmake