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Joined 2 years ago
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Cake day: August 24th, 2023

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  • Glibc’s qsort will default to either insertion sort mergesort or heapsort. Quicksort itself is used when it cannot allocate extra memory for mergesort or heapsort. Insertion sort is still used in the quicksort code, when there is a final 4 items that need to be sorted.

    Normally it is simply mergesort or heapsort. Why I know this? Because there was a recent CVE for quicksort and to reproduce the bug I had to force memory to be unable to be allocated with a max size item. It was interesting reading the source code.

    That is if you are not on a recent version of qsort which simply removed quicksort altogether for the mergesort + heapsort

    Older version still had quicksort and even some had insertion sort. Its interesting to look at all the different versions of qsort.


  • Don’t listen to the haters but it would have been nice if you collapsed this because it is very long and generalized to the point that it is pretty much an eyesore. Plus most people can ask their AI of choosing semi-random topics. I don’t see what was interesting in the AI response at all. It states some blatantly obvious facts and is rather too wordy. I intentionally include into the system prompt or “personalization” about how I like things to be kept short and to not reiterate what I had posted especially if it just sounds like the “AI” is thinking out loud.



  • I run a personal dnsmasq just for dns resolving/routing. It integrates well with Networkmanager. Easy to work with and very reliable to have the DNS resolution and routing be handled by dnsmasq. Single command to reload NetworkManager which also reloads the integrated dnsmasq. I like it and it offers a lot of control for me. I hate having to use the hosts file for when I am connecting to labs via VPN with their own network. dnsmasq is way better at handling subdomains than the hosts file and it feels way more reliable than just hoping the minimal DNS routing system works properly.



  • I think the biggest limiting factor for your mini PC will always be the VRAM and any workload that enjoys that fast RAM speed. Really, I think this mini PC from framework is only sensible for certain workloads. It was poised as a mobile chip and certainly is majorly power efficient. On the other hand I don’t think it is for large scaling but more for testing at home or working at home on the cheap. It isn’t something I expected from framework though as I expected them to maintain modularity and the only modularity here is the little USB cards and the 3D printed front panel designs lol

    Edit
    Personally I am in that niche market of high RAM speed. Also, access to high VRAM for occasional LLM testing. Though it is an AMD and I don’t know if am comfortable switching from Nvidia for that workload just yet. Renting a GPU is just barely cheap enough.