Re: Machine learning to schedule optimization passes

Jon Chesterfield <jonathanchesterfield@gmail.com>
Thu, 29 Aug 2024 20:45:17 +0100

          From comp.compilers
Related articles
Machine learning to schedule optimization passes johnl@taugh.com (John R Levine) (2024-08-29)
Re: Machine learning to schedule optimization passes jonathanchesterfield@gmail.com (Jon Chesterfield) (2024-08-29)
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From: Jon Chesterfield <jonathanchesterfield@gmail.com>
Newsgroups: comp.compilers
Date: Thu, 29 Aug 2024 20:45:17 +0100
Organization: Compilers Central
References: 24-08-011
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
In-Reply-To: 24-08-011

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: <https://arxiv.org/abs/2404.16077>

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