I got 32 additional GB of ram at a low, low cost from someone. What can I actually do with it?

    • slazer2au
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      171 month ago

      One docker container per VM just to maximise the ram usage.

      • Onno (VK6FLAB)
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        171 month ago

        I realise that you are making a joke, but here’s what I used it for:

        • Debian VM as my main desktop
        • Debian VN as my main Docker host
        • Windows VM for a historical application
        • Debian VM for signal processing
        • Debian VM for a CNC

        At times only the first two or three were running. I had dozens of purpose built VM directories for clients, different hardware emulation, version testing, video conferencing, immutable testing, data analysis, etc.

        My hardware failed in June last year. I didn’t lose any data, but the hardware has proven hard to replace. Mind you, it worked great for a decade, so, swings and roundabouts.

        I’m currently investigating, evaluating and costing running all of this in AWS. Whilst it’s technically feasible, I’m not yet convinced of actual suitability.

        • slazer2au
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          21 month ago

          Any reason for not using LXC as PX has native support?

          • Onno (VK6FLAB)
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            51 month ago

            In my case, I’m not a fan of running unknown code on the host. Docker and LXC are ways of running a process in a virtual security sandbox. If the process escapes the sandbox, they’re in your host.

            If they escape inside a VM, that’s another layer they have to penetrate to get to the host.

            It’s not perfect by any stretch of the imagination, but it’s better than a hole in the head.

  • grandel
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    341 month ago

    Sell it to somebody at a medium, medium cost who needs it

  • TXL
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    341 month ago

    You could run a Java program, but you’d quickly run out of ram.

  • @vividspecter@lemm.ee
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    311 month ago
    • Compressed swap (zram)

    • Compiling large C++ programs with many threads

    • Virtual machines

    • Video encoding

    • Many Firefox tabs

    • Games

  • zkfcfbzr
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    221 month ago

    I have 16 GB of RAM and recently tried running local LLM models. Turns out my RAM is a bigger limiting factor than my GPU.

    And, yeah, docker’s always taking up 3-4 GB.

    • Mubelotix
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      51 month ago

      Either you use your CPU and RAM, either your GPU and VRAM

      • zkfcfbzr
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        21 month ago

        Fair, I didn’t realize that. My GPU is a 1060 6 GB so I won’t be running any significant LLMs on it. This PC is pretty old at this point.

        • @fubbernuckin@lemmy.dbzer0.com
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          11 month ago

          You could potentially run some smaller MoE models as they don’t take up too much memory while running. I’d suspect the deepseek r1 8B distill with some quantization would work well.

          • zkfcfbzr
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            130 days ago

            I tried out the 8B deepseek and found it pretty underwhelming - the responses were borderline unrelated to the prompts at times. The smallest I had any respectable output with was the 12B model - which I was able to run, at a somewhat usable speed even.

  • @Jesus_666@lemmy.world
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    211 month ago

    Run a fairly large LLM on your CPU so you can get the finest of questionable problem solving at a speed fast enough to be workable but slow enough to be highly annoying.

    This has the added benefit of filling dozens of gigabytes of storage that you probably didn’t know what to do with anyway.

  • spicy pancake
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    151 month ago

    Fold At Home!

    https://foldingathome.org/

    You can essentially donate your processing power to various science projects that need it to compute protein folding simulations. I used to run it whenever I wasn’t actively using my PC. This does cost electricity and increase rate of wear and tear on the device, as with any sustained high computational load. But it’s cool! :]

    • Rikudou_Sage
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      111 month ago

      Does additional 32 GB of RAM actually help there? I’d assume this is mostly CPU-intensive work.

      • spicy pancake
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        430 days ago

        looking into it, seems like you’re actually right. looks like it runs best with a solid GPU. there may be other distributed computing projects better suited for abundant RAM.

  • linuxgator
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    131 month ago

    You could use it to finally level off that wobbly table in the kitchen.

  • @lordnikon@lemmy.world
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    121 month ago

    If you are on Linux and I guess windows but nor sure. You already use it for cache. So you can never have enough ram. As long as it’s the same speed of your existing ram or you will screw yourself in preformence.