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testing matrix multiplication benchmarks shows that FMA on a critical chain
is a perofrmance loss over separate multiply and add. While the latency of 4
is lower than multiply + add (3+2) the problem is that all values needs to
be ready before computation starts.
While on znver4 AVX512 code fared well with FMA, it was because of the split
registers. Znver5 benefits from avoding FMA on all widths. This may be different
with the mobile version though.
On naive matrix multiplication benchmark the difference is 8% with -O3
only since with -Ofast loop interchange solves the problem differently.
It is 30% win, for example, on S323 from TSVC:
real_t s323(struct args_t * func_args)
{
// recurrences
// coupled recurrence
initialise_arrays(__func__);
gettimeofday(&func_args->t1, NULL);
for (int nl = 0; nl < iterations/2; nl++) {
for (int i = 1; i < LEN_1D; i++) {
a[i] = b[i-1] + c[i] * d[i];
b[i] = a[i] + c[i] * e[i];
}
dummy(a, b, c, d, e, aa, bb, cc, 0.);
}
gettimeofday(&func_args->t2, NULL);
return calc_checksum(__func__);
}
gcc/ChangeLog:
* config/i386/x86-tune.def (X86_TUNE_AVOID_128FMA_CHAINS): Enable for
znver5.
(X86_TUNE_AVOID_256FMA_CHAINS): Likewise.
(X86_TUNE_AVOID_512FMA_CHAINS): Likewise.
(cherry picked from commit
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