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From: "juzhe.zhong at rivai dot ai" <gcc-bugzilla@gcc.gnu.org>
To: gcc-bugs@gcc.gnu.org
Subject: [Bug tree-optimization/113441] [14 Regression] Fail to fold the last
 element with multiple loop
Date: Mon, 22 Jan 2024 22:16:55 +0000
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https://gcc.gnu.org/bugzilla/show_bug.cgi?id=3D113441

--- Comment #10 from JuzheZhong <juzhe.zhong at rivai dot ai> ---
(In reply to Tamar Christina from comment #9)
> So on SVE the change is cost modelling.
>=20
> Bisect landed on g:33c2b70dbabc02788caabcbc66b7baeafeb95bcf which changed
> the compiler's defaults to using the new throughput matched cost modelling
> used be newer cores.
>=20
> It looks like this changes which mode the compiler picks for when using a
> fixed register size.
>=20
> This is because the new cost model (correctly) models the costs for FMAs =
and
> promotions.
>=20
> Before:
>=20
> array1[0][_1] 1 times scalar_load costs 1 in prologue
> int) _2 1 times scalar_stmt costs 1 in prologue
>=20
> after:
>=20
> array1[0][_1] 1 times scalar_load costs 1 in prologue=20
> (int) _2 1 times scalar_stmt costs 0 in prologue=20
>=20
> and the cost goes from:
>=20
> Vector inside of loop cost: 125
>=20
> to
>=20
> Vector inside of loop cost: 83=20
>=20
> so far, nothing sticks out, and in fact the profitability for VNx4QI drops
> from
>=20
> Calculated minimum iters for profitability: 5
>=20
> to
>=20
> Calculated minimum iters for profitability: 3
>=20
> This causes a clash, as this is now exactly the same cost as VNx2QI which
> used to be what it preferred before.
>=20
> Which then leads it to pick the higher VF.
>=20
> In the end smaller VF shows:
>=20
> ;; Guessed iterations of loop 4 is 0.500488. New upper bound 1.
>=20
> and now we get:
>=20
> Vectorization factor 16 seems too large for profile prevoiusly believed to
> be consistent; reducing.=20=20
> ;; Guessed iterations of loop 4 is 0.500488. New upper bound 0.
> ;; Scaling loop 4 with scale 66.6% (guessed) to reach upper bound 0
>=20
> which I guess is the big difference.
>=20
> There is a weird costing going on in the PHI nodes though:
>=20
> m_108 =3D PHI <m_92(16), m_111(5)> 1 times vector_stmt costs 0 in body=20
> m_108 =3D PHI <m_92(16), m_111(5)> 2 times scalar_to_vec costs 0 in prolo=
gue
>=20
> they have collapsed to 0. which can't be right..

I don't think this change makes the regression since the regression not only
happens on ARM SVE but also on RVV.
It should be middle-end.

I believe you'd better use -fno-vect-cost-model.=