Path: csiph.com!weretis.net!feeder9.news.weretis.net!news.misty.com!news.iecc.com!.POSTED.news.iecc.com!nerds-end From: Jon Chesterfield Newsgroups: comp.compilers Subject: Re: Machine learning to schedule optimization passes Date: Thu, 29 Aug 2024 20:45:17 +0100 Organization: Compilers Central Sender: johnl%iecc.com Approved: comp.compilers@iecc.com Message-ID: <24-08-013@comp.compilers> References: <24-08-011@comp.compilers> MIME-Version: 1.0 Content-Type: text/plain; charset="UTF-8" Injection-Info: gal.iecc.com; posting-host="news.iecc.com:2001:470:1f07:1126:0:676f:7373:6970"; logging-data="86111"; mail-complaints-to="abuse@iecc.com" Keywords: optimize Posted-Date: 29 Aug 2024 15:58:13 EDT X-submission-address: compilers@iecc.com X-moderator-address: compilers-request@iecc.com X-FAQ-and-archives: http://compilers.iecc.com In-Reply-To: <24-08-011@comp.compilers> Xref: csiph.com comp.compilers:3593 This paper makes no mention of correctness or behaviour, only code size. Also no mention of compile time. I wonder how the results would compare to a baseline of running the usual O3 pipeline to fixpoint. Changing order of passes usually uncovers correctness bugs which papers of this genre rarely worry about. It's very easy to make programs smaller if you don't mind changing behaviour. Jon On Thu, 29 Aug 2024, 19:35 John R Levine, <[johnl@taugh.com](mailto:johnl@taugh.com)> wrote: > This paper used machine learning to select and order LLVM optimization > passes. Apparently it worked pretty well. > > > CompilerDream: Learning a Compiler World Model for General Code Optimization > > Effective code optimization in compilers is crucial for computer and > software engineering. ... > > Full paper at: