Install and run Anaconda, TensorFlow, PyTorch, and an AI benchmark with a single command. Enjoy NVIDIA RTX, CUDA, and CuDNN-powered performance 5 to 30 times greater than popular Unix® laptops. Develop with the industry-standard PyCharm IDE using the expertly packaged JetBrains Toolbox and desktop integration. This solution only applies to the Kubuntu Focus M1 and M2 models, as they have the required Nvidia hardware.
Please read the disclaimer before proceeding. We review and update guided solutions like this regularly. If you have suggestions or requests, please write firstname.lastname@example.org.
Run the app from
App Menu > Kubuntu Focus > Anaconda GPU AI Suite Installer, or open a terminal and enter
kfocus-conda (on 22.04 LTS) or
kfocus-001-conda (on 20.04 LTS). This installs an
Anaconda suite that is professionally vetted, comprehensive, and GPU accelerated. You will be prompted to optionally install the following environments:
Kfocus Conda will not overwrite or delete data unless you tell it to do so. You may run it again to add environments as needed. For example, you may install only
TensorFlow at first and then add
PyTorch later. Run the AI suite at the end to compare to the results shown in the Benchmarks section.
When you wish to build on these Conda environments, we recommend using Pycharm. You may install this with the JetBrains Toolbox installed on all Kubuntu Focus laptops.
When running Deep Learning workloads, you may notice that the software reports less available RAM than the GPU actually has. Part of this is because of driver overhead, but also because the GPU uses some memory for your display. One can instead use the Intel GPU for the display and use the NVIDIA GPU for only Deep Learning or other computing tasks. To do this, use the GPU widget in the tool tray to select
Switch to Intel GPU (Power Save Mode), then point the deep learning tasks to use the Nvidia GPU. Notice in this mode, typically only two displays are available. If you need more displays, you can
Switch to Hybrid GPU (On-Demand Mode) as shown here; however, remember that this can result in additional overhead and slow response, so please remember to switch back when you are done.
You may run comprehensive TensorFlow benchmarks at the end of the Kfocus Conda script. Please compare to the official results. All tests are current as of April 2023.
|Results||RTX 3080 Ti||RTX 3070 Ti||RTX 3060||RTX 3080 Max-Q||RTX 3070 Max-Q||RTX 3060 Max-Q||Titan XP W10|
|Video RAM||16 GB||8 GB||6 GB||16 GB||8 GB||6 GB||12 GB|
 See official comparison chart
 Kubuntu Focus M2GEN 4
 Kubuntu Focus M2GEN 3
 Desktop GPU
Q: Starting NVIDIA Visual Profiler results in an error. How can I fix this?
A: One must install Java 8 and then call
nvvp with the correct path.
Q: I booted my Kubuntu Focus, and it never got past the splash screen. How do I fix this?
NVIDIA Settings and other applications may ask you to save an
xorg.conf file. Doing so may disable your internal display from functioning with a GUI upon logout or restart, and you will not be able to sign-in. If this happens, we recommend you remove this file:
sudo /bin/rm /etc/X11/xorg.conf, type your password when prompted.
sudo systemctl restart sddm && exit.
You should be able to sign-in normally.
Q: I see some libray errors when installing Anaconda. What can I do?
A: The Focus M2 ships with OpenGL and Vulkan libraries installed. When you run the Kfocus Conda script, you may be prompted to download and install additional libraries such as CUDA and CuDNN. Please ensure you are connected to the Internet with good bandwidth, as these can be quite large.If you still receive these errors, you can cancel, run the FocusRx diagnostics shown below, and then try again.
This is a partial revision history. See the
git repository for all entries.
2021-11-07 3e32a343Update table to current
2021-10-10 5728326eReformat to 2-column
2021-09-22 dc862884Update link and headline colors
2021-08-23 681261b4Review and update codeblocks
2021-08-19 b994dd79Add keywords for hybrid graphics mode
2021-03-07 e3c1285dRevise conda launch guide, update styles
2020-09-28 5d089610Update to M2 scores
2020-06-10 c4ed9299Restructure layout
2020-05-25 581c6523Expand benchmarks
2020-05-20 d00295d7Add Library check
2020-05-18 8c4b5b82Add GPU library fix
2020-05-15 0684cd5cAdd benchmark
2020-02-18 a4d437c5Add conda script
2020-01-31 70b4aa40First publication
We try hard to provide a useful solution validated by professionals. However, we cannot anticipate every situation, and therefore cannot guarantee this procedure will work for your needs. Always backup your data and test the solution to determine the correct procedure for you.
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