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One suggested workaround on Stack Overflow was to pass a number of -ffixed-<reg> flags to prevent GCC from producing code using the unsupported registers:
I found that this workaround worked for me. So a possible workaround in Numpy would be to automatically add these flags to CFLAGS, at least on Cygwin and GCC < 8.4 (does Numpy's build system have an existing routine to check the compiler version?)
Error message:
numpy/core/src/umath/loops.c.src:3058:1: warning: AVX512F vector return without AVX512F enabled changes the ABI [-Wpsabi]
}
^
numpy/core/src/umath/loops.c.src:3058:1: warning: AVX vector return without AVX enabled changes the ABI [-Wpsabi]
{standard input}: Assembler messages:
{standard input}:9023: Error: invalid register for .seh_savexmm
{standard input}:9025: Error: invalid register for .seh_savexmm
{standard input}:9027: Error: invalid register for .seh_savexmm
... several more similar lines ...
Numpy/Python version information:
1.20.0.dev0+7f7d19d 3.6.8 (default, Feb 14 2019, 22:09:48)
[GCC 7.4.0]
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I encountered this issue at build time while testing #16246 on a Haswell-based CPU supporting AVX2.
This is due to a confirmed bug in GCC that is fixed since GCC 8.4: https://gcc.gnu.org/bugzilla/show_bug.cgi?id=65782
One suggested workaround on Stack Overflow was to pass a number of
-ffixed-<reg>flags to prevent GCC from producing code using the unsupported registers:I found that this workaround worked for me. So a possible workaround in Numpy would be to automatically add these flags to
CFLAGS, at least on Cygwin and GCC < 8.4 (does Numpy's build system have an existing routine to check the compiler version?)Error message:
Numpy/Python version information:
The text was updated successfully, but these errors were encountered: