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Joined 1 year ago
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Cake day: June 15th, 2023

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  • Nvidia drivers don’t tend to be as performant under linux.

    With AMD instead of using the AMD VLK driver, you would use the RADV (developed largely by valve). Which petforms better.

    Every AMD card under linux supports OpenCL (the driver is more based on graphics card architecture) and you install it very easily. Googling it with windows found pages of errors and missing support.

    Blender supports OpenCL. I bet the 2x improvement is Blender being able to ofload rendering to the AMD graphics card.

    Also this represents the biggest headache in Linux, lots of gamers insist they can only use Nvidia cards. Nvidia treats linux as an afterthought as best or deliberately sabotages things at worse.

    AMD embraced open source and so Linux land is much nicer on AMD (and to a less extent Intel).

    The results here will probably be a DxVK quirk, lots of “Nvidia optimised” games have game engines doing weird things and the Nvidia driver compensates. DxVK has been identifying that to produce “good” vulkan calls.


  • Mint was a reaction to Gnome 3, the unique workflow upset a lot of people and the people behind Mint decided to build Cinnamon desktop (its Gnome 3 made to look/work like Gnome 2). They needed a distribution to build/test their work and so based a distribution off of Ubuntu and called it Mint.

    As a bit of explanation, there are only a few projects which attempt to build an entire linux distribution from scratch. This involves finding code from thousands of sources, work out packaging, etc… We call these ‘base’ distributions, Debian is the base distribution for Ubuntu, Ubuntu is the base distribution for Mint.

    Ubuntu tends to be slightly ahead of Debian in the software versions it uses and automatically enables the ‘non-free’ repositories. Ubuntu tends to push some Canonical specific things like Snaps (which everyone hates)

    I believe Mint rolls the Canonical specific things out of Ubuntu and you get the latest version of Cinnamon.

    Its all a bit…


  • If its for work I would suggest picking a “stable” distribution like Debian, Kubuntu or OpenSuse.

    A lot of people recommend Arch or Fedora but the focus of those is getting the very latest releases, which increases your chance of stuff breaking.

    A lot of people will suggest niche distributions, those can be great for specific needs but generally you will always find Debian/Ubuntu/RHEL support for commercial apps.

    I would also suggest looking at the KDE Desktop, many distributions default to Gnome but it is unique in how it works, KDE (or XFCE) will provide a desktop similar to Windows 11.

    Lastly I would suggest looking at Crossover Linux by Codeweavers.

    Linux has something called WINE, its an attempt to implement the Windows 95 - 11 API’s so windows applications can run on linux.

    WINE is how the Steam Deck/Linux is able to play Windows games. Valve embedded it into Steam and called it “Proton”.

    WINE is primarily developed by Codeweavers and they provide the Crossover application that makes setting up and running a Windows application really easy.

    People will mention Lutris but that has a far higher learning curve.

    There is an application database so you can see in advance if your applications would work: https://appdb.winehq.org/


  • This advice isn’t grounded in reality.

    Management normally defines ways to track and judge itself, these are typically called Key Performance Indicators.

    KPI’s are normally things like contract value growth, new contracts signed, profit margin, etc…

    So if the project manager is meeting or exceeding their KPI’s and you walk up to their boss telling them the PM is failing as basic job functions, the boss won’t care.

    This is because the boss might have set the KPI’s or the boss might also be judged on them. In either situation its to the bosses advantage to ignore you.

    The boss will only care if there is a KPI you can demonstrate the PM failing to meet.

    Every person/group will have various incentives and motivations. To affect change you have to understand what they are.



  • A project manager has responsibility for delivery of a project but they typically lack domain specific knowledge. As a result they can’t directly deliver something, merely ask subject matter experts for advice and facilitate a team to deliver.

    Most PM’s cope with the stress of this position poorly.

    This cartoon is an example of micro management (a common coping mechanisim), the manager has involved themselves in the low level decisions because that gives a sense of control. If a technical team then tell them its a bad decison the team are effectively attacking their coping mechanisim.

    The solution isn’t to tell them their technical idea is terrible, when you’ve fallen down this rabbit hole you have to treat the PM as a stakeholder. They are someone you have to manage, so a common solution is to give them confidence there is a path to delivery, a way to track and understand it.


  • If you read the reports…

    Normally JPL outsource their Mars mission hardware to Lockheed Martin. For some reason they have decided to do Mars Sample Return in house. The reports argue JPL hasn’t built the necessary in house experience and should have worked with LM.

    Secondly JPL is suffering a staff shortage which is affecting other projects and the Mars Sample Return is making the problem worse.

    Lastly if an organisation stops performing an action it “forgets” how to do it. You can rebuild the capability but it takes time.

    A team arbitrary declaring they are experts and suddenly decideding they will do it is one that will have to relearn skills/knowledge on a big expensive high profile project. The project will either fail (and be declared a success) or masses of money will be spent to compensate for the teams learning.

    Either situation is not ideal


  • The GAO has performed an annual review of the Space Launch System every year since 2014 and switched to reviewing the Artemis program in 2019.

    Each year the GAO points out Nasa isn’t tracking any costs and Nasa argues with the GAO about the costs they assign. Then the GAO points out Nasa has no concrete plan to reduce costs, Nasa then goes nu’uh (see the articles cost reduction “objectives”).

    The last two reports have focused on the RS-25 engine, last time the GAO was unhappy because an engine cost Nasa $100 million and Nasa had just granted a development contract to reduce the cost of the engine.

    However if you took the headline cost of the contract and split it over planned engines it was greater than the desired cost savings. Nasa response was development costs don’t count.

    Congress reviews GAO reports and decides to give SLS more money.


  • The other person was just wrong.

    Large scale Hydrogen generation isn’t generated in a fossil free way, Hydrogen can be generated is a green way but the infrastructure isn’t there to support SLS.

    Hydrogen is high ISP (miles per gallon) by rubbish thrust (engine torque).

    This means SLS only works with Solid Rocket Boosters, these are highly toxic and release green house contributing material into the upper atmosphere. I suspect you would find Falcon 9/Starship are less polluting as a result.

    Lastly the person implies SLS could be fueled by space sources (e.g. the moon).

    SLS is a 2.5 stage rocket, the boosters are ditched in Earths Atmosphere and the first stage ditched at the edge of space. The current second stage doesn’t quite make low earth orbit.

    So someone would have to mine materials on the moon and ship them back. This would be far more expensive than producing hydrogen on Earth.

    Hydrogen on the moon makes sense if your in lunar orbit, not from Earth.


  • During the pandemic I had some unoccupied python graduates I wanted to teach data engineering to.

    Initially I had them implement REST wrappers around Apache OpenNLP and SpaCy and then compare the results of random data sets (project Gutenberg, sharepoint, etc…).

    I ended up stealing a grad data scientist because we couldn’t find a difference (while there was a difference in confidence, the actual matches were identical).

    SpaCy required 1vCPU and 12GiB of RAM to produce the same result as OpenNLP that was running on 0.5 vCPU and 4.5 GiB of RAM.

    2 grads were assigned a Spring Boot/Camel/OpenNLP stack and 2 a Spacy/Flask application. It took both groups 4 weeks to get a working result.

    The team slowly acquired lockdown staff so I introduced Minio/RabbitMQ/Nifi/Hadoop/Express/React and then different file types (not raw UTF-8, but what about doc, pdf, etc…) for NLP pipelines. They built a fairly complex NLP processing system with a data exploration UI.

    I figured I had a group to help me figure out Python best approach in the space, but Python limitations just lead to stuff like needing a Kubernetes volume to host data.

    Conversely none of the data scientists we acquired were willing to code in anything but Python.

    I tried arguing in my company of the time there was a huge unsolved bit of market there (e.g. MLOP’s)

    Alas unless you can show profit on the first customer no business would invest. Which is why I am trying to start a business.




  • @ergoplato I didn’t suggest that.

    Personally I don’t think its ego. I think you have two issues.

    The first is people go through stages learning DevOps. Stage 1 has people deploy a CI because its cool, they build a few basic pipelines and then 90% of people get bored. The 2nd stage is people start extending those pipelines, it results in really complex pipelines requiring lots of unique changes based on the opinion of the writer. You move to the 3rd stage when your asked to recreate/extend for a new project and realise how specific your solutions are.

    Learning how to make minor tweaks and hook in a few key points to get what you want takes years. Without that most packagers will want to make big changes upstream which won’t go down well.

    The second issue, I have met quite a few developers who become highly stressed when the build system is doing something they haven’t needed to do or understand.

    A really simple example I have a Jenkins function which I tend to slip into release pipelines, it captures the release version and creates a version in Jira.

    I normally deploy it first as a test before a few other functions to automate various service management requirements.

    Its surprising how many devs will suddenly decide every problem (test failed, code failed review, sharepoint breaks, bad os update, etc…) is due to that function.

    For me this little function is a test, if the team don’t care I will work to integrate various bits. If they freak out, I’ll revert decide if it is worth walking them through the process or walk away.


  • One of the reasons for the #DevOps movement is developers see building and packaging as #notmyjob.

    The task would historically fall on the most junior member of the team, who would make a pigs ear out of it due to complete lack of experience.

    This is compounded by the issue that most C/C++ build systems don’t really include dependency management.

    Linux distributions have all tried to work out those dependency trees but they came up with slightly different solutions. This is why there are a few “root” distributions everything branches from.

    That means developers have to learn about a few root distributions to design a deb/rpm/aur package systems to base their release around.

    That is a considerable amount of learning in a subject most aren’t interested in.

    The real question is why don’t package maintainers upstream a packaging solution?





  • Activity Pub has a few parts, Lemmy implements the Threaded message part.

    Mastodon implements a short messaging (posts) part. Meta’s Threads will implement this.

    KBin implemented both parts, within KBin you’ll see microblog as an option for magazines (communities/subredits). This shows either ‘posts’ made to the magazine or posts with hastags associated with the magazine.

    The posts and threaded message parts have overlap in how they work so mastodon users can see certain threaded messages and comment on them.