Yoko, Shinobu ni, eto… 🤔
עַם יִשְׂרָאֵל חַי Slava Ukraini 🇺🇦 ❤️ 🇮🇱
It’s actually a good thing that visual learners get a chance to learn useful stuff by watching videos. Not everyone has the attention span required to read through a Wikipedia page.
And you can’t really get a lot of words from “I waited 8 hours for Firefox to build.”
You actually can if you describe the build process and how emerge works, how you can customize the packages with Gentoo’s USE flags etc…
I already got functional laptops (an Alienware M15 r3 and a very recent HP Pavilion) but none of them come close to my Thinkpad T480 in terms of comfort of use, the overall build quality and the damn awesome keyboard.
Too bad that all (?) recent Thinkpads now have soldered RAM.
lacks an anime girl wallpaper IMO
It’s probably part of some homework and he has to describe the install process? Could have picked Gentoo for a higher word count IMO
Since you already know Java, you could jump straight to C++ with Bjarne’s book “Programming - Principles and Practice Using C++”: https://www.stroustrup.com/programming.html
You can then move to more modern C++ with his other book “A Tour of C++”: https://www.stroustrup.com/tour3.html
And then if you’re curious to know how software design is done in modern C++, even if you already know classical design patterns from your Java experience, you should get Klaus Iglberger’s book: https://www.oreilly.com/library/view/c-software-design/9781098113155/
In parallel also watch the “Back to Basics” video series by CppCon (see their YouTube channel: https://www.youtube.com/@CppCon , just type “back to basics” in that channel’s search bar).
Learning proper C++ should give you a much better understanding of the hardware while the syntax still remains elegant, and you get to add a new skill that’s in very high demand.
If you’re doing C++ then C++ Weekly by Jason Turner is an awesome must-watch.
For anyone wondering what Proton GE is, it’s Proton on steroids: https://github.com/GloriousEggroll/proton-ge-custom
For instance, even if you have an old Intel integrated GPU, chances are you can still benefit from AMD’s FSR just by pushing a few flags to Proton GE, even if the game doesn’t officially support it, and you’ll literally get a free FPS boost (tested it for fun and can confirm on an Intel UHD Graphics 620).
Congrats! Your laptop will be even happier with a lighter but still nice-looking desktop environment like Xfce and you even have an Ubuntu flavor around it: Xubuntu.
My bad, I’ll move there then
Hard to tell as it’s really dependent on your use. I’m mostly writing my own kernels (so, as if you’re doing CUDA basically), and doing “scientific ML” (SciML) stuff that doesn’t need anything beyond doing backprop on stuff with matrix multiplications and elementwise nonlinearities and some convolutions, and so far everything works. If you want some specific simple examples from computer vision: ResNet18 and VGG19 work fine.
Works out of the box on my laptop (the export
below is to force ROCm to accept my APU since it’s not officially supported yet, but the 7900XTX should have official support):
Last year only compiling and running your own kernels with hipcc
worked on this same laptop, the AMD devs are really doing god’s work here.
Yup, it’s definitely about the “open-source” part. That’s in contrast with Nvidia’s ecosystem: CUDA and the drivers are proprietary, and the drivers’ EULA prohibit you from using your gaming GPU for datacenter uses.
ROCm is that its very unstable
That’s true, but ROCm does get better very quickly. Before last summer it was impossible for me to compile and run HIP code on my laptop, and then after one magic update everything worked. I can’t speak for rendering as that’s not my field, but I’ve done plenty of computational code with HIP and the performance was really good.
But my point was more about coding in HIP, not really about using stuff other people made with HIP. If you write your code with HIP in mind from the start, the results are usually good and you get good intuition about the hardware differences (warps for instance are of size 32 on NVidia but can be 32 or 64 on AMD and that makes a difference if your code makes use of warp intrinsics). If however you just use AMD’s CUDA-to-HIP porting tool, then yeah chances are things won’t work on the first run and you need to refine by hand, starting with all the implicit assumptions you made about how the NVidia hardware works.
HIP is amazing. For everyone saying “nah it can’t be the same, CUDA rulez”, just try it, it works on NVidia GPUs too (there are basically macros and stuff that remap everything to CUDA API calls) so if you code for HIP you’re basically targetting at least two GPU vendors. ROCm is the only framework that allows me to do GPGPU programming in CUDA style on a thin laptop sporting an AMD APU while still enjoying 6 to 8 hours of battery life when I don’t do GPU stuff. With CUDA, in terms of mobility, the only choices you get are a beefy and expensive gaming laptop with a pathetic battery life and heating issues, or a light laptop + SSHing into a server with an NVidia GPU.
Wayland reduces bugs
As I have to give a few lectures, I can’t say I’m pleased with how screen-sharing or using a projector in the classroom fails almost half of the time and always embarrasses me in front of everyone. I ended up purging the Wayland stuff and going back to good ol’ i3 and I haven’t had a display-related issue ever since.
X11 works, it may not be as sexy or modern as Wayland but it’s battle-tested and just works and for the vast majority of people, excluding Wayland’s bugs, the differences are not even noticeable.
It’s a lifelong learning nerding process
It depends. I’m working in the quant department of a bank and we work on pricing libraries that the traders then use. Since traders often use Excel and expect add-ins, we have a mostly Windows environment. Our head of CI, a huge Windows and Powershell fan, once then decided to add a few servers with Linux (RHEL) on them to have automated Valgrind checks and gcc/clang builds there to continuously test our builds for warnings, undefined behavior (gcc with O3 does catch a few of them) and stuff.
I thought cool, at least Linux is making it into this department. Then I logged into one of those servers.
The fucker didn’t like the default file system hierarchy and did stuff like /Applications
and `/Temp’ and is installing programs by manually downloading binaries and extracting them there.
Bad track record with their privacy invasion via their Amazon shenanigans (which Richard Stallman called the Ubuntu Spyware), the shilling of Ubuntu One cloud and now Ubuntu Pro subscriptions that are reminiscent of Microsoft’s shilling of Microsoft accounts and OneDrive, Snap telemetry…
The tone may be a bit harsh but it’s muuuuch better than how he used to be during his most toxic days. This is how he used to talk: https://www.networkworld.com/article/706908/security-torvalds-to-bad-security-devs-kill-yourself-now.html
Linus definitely got much better at handling his anger since his public apology in 2018.