From mboxrd@z Thu Jan 1 00:00:00 1970 Return-Path: Received: by sourceware.org (Postfix, from userid 48) id C0D5C3858D20; Wed, 31 Jan 2024 14:45:52 +0000 (GMT) DKIM-Filter: OpenDKIM Filter v2.11.0 sourceware.org C0D5C3858D20 DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gcc.gnu.org; s=default; t=1706712352; bh=hEzo4Qm14WDJ27d6hIl5cdy3cim+G77eSopguKUf+Sc=; h=From:To:Subject:Date:In-Reply-To:References:From; b=q8py4hKrvCVoWxrHghyx3/3AMXrJRc2E+XzAi5JRdvyfShbMzpTaTxQJiEIn+ozk+ cVinYBa/i3chU2Ps9AUVIswyzn8rtQ9BKP93AUkWZ4W7mQ3B9JvL1CTXOQyBtkhz0f RixM1GIlRILqdgreS4To42g3+qrUYNRJYJ/3wopQ= From: "jamborm at gcc dot gnu.org" To: gcc-bugs@gcc.gnu.org Subject: [Bug gcov-profile/113646] PGO hurts run-time of 538.imagick_r as much as 68% at -Ofast -march=native Date: Wed, 31 Jan 2024 14:45:51 +0000 X-Bugzilla-Reason: CC X-Bugzilla-Type: changed X-Bugzilla-Watch-Reason: None X-Bugzilla-Product: gcc X-Bugzilla-Component: gcov-profile X-Bugzilla-Version: 14.0 X-Bugzilla-Keywords: missed-optimization X-Bugzilla-Severity: normal X-Bugzilla-Who: jamborm at gcc dot gnu.org X-Bugzilla-Status: UNCONFIRMED X-Bugzilla-Resolution: X-Bugzilla-Priority: P3 X-Bugzilla-Assigned-To: unassigned at gcc dot gnu.org X-Bugzilla-Target-Milestone: --- X-Bugzilla-Flags: X-Bugzilla-Changed-Fields: Message-ID: In-Reply-To: References: Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable X-Bugzilla-URL: http://gcc.gnu.org/bugzilla/ Auto-Submitted: auto-generated MIME-Version: 1.0 List-Id: https://gcc.gnu.org/bugzilla/show_bug.cgi?id=3D113646 --- Comment #3 from Martin Jambor --- (In reply to Richard Biener from comment #1) > Did you try with -fprofile-partial-training (is that default on? it > probably should ...). Can you please try training with the rate data > instead of train > to rule out a mismatch? With -fprofile-partial-training the znver4 LTO vs LTOPGO regression (on a n= ewer master) goes down from 66% to 54%.=20=20 So far I did not find a way to easily train with the reference run (when I = add "train_with =3D refrate" to the config, I always get "ERROR: The workload specified by train_with MUST be a training workload!")=