• 5 Posts
  • 42 Comments
Joined 3 years ago
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Cake day: June 22nd, 2023

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  • The Asus BT8 is a wifi 7 router supported by openWRT and there is quite a few of us running it. I think generally OpenWRT is a good way to go and the Table of Hardware on the OpenWRT site will give you a dizzying array of options for wifi 6 and 7 devices that are supported and you get to pick your spec and price from those available.

    You might need the modem device if you are using cable, otherwise its FTTH or DSL then you wont.

    If you search for OpenWRT tutorials on youtube you will find a McFly or something like that name and he has a bunch of tutorials on how to set up OpenWRT and a range of more advanced networking topics and how to use OpenWRT to utilise them.




  • I have just let it grow organically. The front page is an index of various topics from personal things and particular games to household information. Then below that there might be just a page or an index to a bunch of pages often starting just as a list of links. I am often refactoring once a page has a bunch of sub headings of related topics but ultimately now needing multiple pages and replacing the original with the index to those pages. I don’t think I could have designed an index system from the start without the content because I wouldn’t have known what I was going to store.





  • My ISP provides a /48 for IPv6 via prefix delegation so all internal machines that support it have a ULA and DHCPv6. I have disabled SLAAC . In docker I assign a /64 of that prefix to docker containers. The local addresses is what most of the internal network stuff is based on (DNS etc) rather than the globally accessible address. The PD addresses are only about going onto the internet.

    SLAAC actually is just fine, I just didn’t really want to be exposing the manufacturer information of the addresses online so preferred DHCP, but either or both together works from OpenWRT prefix delegation.




  • I still had some issues with the mouse speed on cachyos even after I disabled acceleration. I felt off on its default and I ended up boosting it. Thing is my mouse has its speed inbuilt so I don’t need external software or anything else to configure it on Linux so I don’t understand why I had to boost the speed to make it behave a bit better, it felt like there was some latency as well.







  • Every one always says XMPP and there were a lot of recommendations for ejabberd. I tried this recently and it was a total disaster, I do not have a working chat server. If I followed the docker instructions the server would just crash with no details of what went wrong. Where it should have been creating a default server config file it was instead creating a directory with the wrong permissions then promptly crashing. I tried following their documentation but after about 6 hours of messing about and adding more and more I still couldn’t get a client to login to it. I have no idea how to make this work.

    So whatever the solution ultimately is I can’t recommend Ejabberd.



  • Most technology adoption follows an S curve, it can often take a long time to start to get going. Linux has gradually and steadily been improving especially for games and other desktop uses while at the same time Microsoft has been making Windows worse. I feel more that this is Microsoft’s fault, they have abandoned the development of desktop Windows and the advancement of support for modern processor designs and gaming hardware. This has for the first time has let Linux catch up and in many cases exceed Windows capabilities on especially gaming which has always been a stubborn issue. Its still a problem especially in hardware support for VR and other peripherals but its the sort of thing that might sort itself out once the user base grows and companies start producing software for Linux instead.

    It might not be enough, but the switching off Windows 10 is causing a change which Microsoft might really regret in a few years.


  • Initially a lot of the AI was getting trained on lower class GPUs and none of these AI special cards/blades existed. The problem is that the problems are quite large and hence require a lot of VRAM to work on or you split it and pay enormous latency penalties going across the network. Putting it all into one giant package costs a lot more but it also performs a lot better, because AI is not an embarrassingly parallel problem that can be easily split across many GPUs without penalty. So the goal is often to reduce the number of GPUs you need to get a result quickly enough and it brings its own set of problems of power density in server racks.