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Asahi Linux Now Officially Supports Apple M3 Macs - With Caveats

Asahi Linux developers announced today that they are now officially supporting the Linux distribution on Apple M3 powered Macs. With the exception of the Mac Studio M3 Ultra, other M3 / M3 Pro / M3 Max devices should now work with the latest Asahi Linux builds but with some feature caveats...
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LLVM Developers Discuss Enabling ClangIR Build By Default

ClangIR has been in development for a number of years now as a new intermediate representation for the Clang compiler. ClangIR makes use of MLIR and is higher-level than LLVM IR. With ClangIR able to preserve more C/C++ source semantics, its usage can lead to better diagnostics, code/static analysis, and more performance optimizations compared to everything lowered straight away from AST to LLVM IR. While not enabling its usage by default, LLVM stakeholders are discussing at least now building it by default...
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Linux Patches Posted For Initial Enablement Of The Apple A18 Pro + MacBook Neo

In addition to Linux developers focused on Apple Silicon being busy enabling functionality for the M3 and newer SoCs under the Linux kernel, there are also developers working on enabling the A18 Pro SoC used by the new, budget-friendly MacBook Neo laptop. Patches were posted this week for initial enablement of the A18 Pro and the MacBook Neo Device Tree... But even with these patches, the Linux support is still severely limited for now...
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Amazon Linux 2027 Shows Off Nice Performance Gains On AMD EPYC In The AWS Cloud

Yesterday AWS announced the public preview of Amazon Linux 2027 as their successor to the current Amazon Linux 2023 in-house distribution. With all the software upgrades and improvements like building packages now with link-time optimizations (LTO), enforcing x86-64-v3 builds, and other changes, I was eager to run some performance benchmarks of Amazon Linux 2023 vs. Amazon Linux 2027 in the EC2 cloud.
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NetworkManager Works To Enforce AI Policy By Tricking AI Agents To Add A Canary

Last month the NetworkManager project adopted an AI coding policy where authors are responsible for 100% of the code they submit and must be able to explain it all. In an attempt to catch AI coding agents that may be trying to bypass their policy, they have added an interesting canary to the project to try to catch such AI-generated patches so they can then be automatically dealt with...
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