Open-source News

Arm C1-Ultra Scheduling Model Merged For LLVM/Clang 23

Phoronix - Fri, 04/24/2026 - 18:23
Merged recently to the latest LLVM/Clang compiler development tree is the Arm C1-Ultra scheduling model for helping with delivering optimal binaries for that flagship next-gen Arm mobile CPU...

Pull Request For Linux To Remove Old Network Drivers, ISDN Subsystem Due To AI/LLM Noise

Phoronix - Fri, 04/24/2026 - 18:08
It was just days ago we reported on a proposal to drop old network drivers due to AI-driven bug reports becoming a burden on upstream kernel developers. Last night that culminated with an initial pull request to clear out some old, unused networking drivers plus also clearing out the entire ISDN subsystem and more...

hyperfine: Find Linux Command Execution Time Accurately

Tecmint - Fri, 04/24/2026 - 13:29
The post hyperfine: Find Linux Command Execution Time Accurately first appeared on Tecmint: Linux Howtos, Tutorials & Guides .

hyperfine is a command-line benchmarking tool that runs your commands repeatedly, collects timing data across multiple runs, and gives you

The post hyperfine: Find Linux Command Execution Time Accurately first appeared on Tecmint: Linux Howtos, Tutorials & Guides.

HDMI FRL Support Achieved With Open-Source Nouveau For NVIDIA GPUs

Phoronix - Fri, 04/24/2026 - 08:16
While the AMDGPU open-source driver has struggled with HDMI 2.1 support due to the HDMI Forum blocking open-source implementations, HDMI Fixed Rate Link (FRL) as a feature of the HDMI 2.1 specification is enjoying success now with the open-source Nouveau graphics driver on Linux for NVIDIA GPUs...

When less is more: Why less precision and fewer parameters carry enterprise AI

Red Hat News - Fri, 04/24/2026 - 08:00
Running Llama 70B as an on-demand cloud inference endpoint costs roughly $16,000 per month. Running Llama 8B costs about $734. For teams where an 8B model meets the quality bar for their workload, that gap is very hard to ignore.The question enterprise teams are asking is rarely, "how do we get the most powerful model?" It is almost always, "how do we get a model that's fast enough, accurate enough, and affordable enough to run reliably in our environment?" Those are different questions, and they often lead to different answers, pointing toward smaller models more often than teams expect.The c

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