Complete day-long jobs in 20 minutes. Accelerate TensorFlow deep learning up to 25 times (2,500%) faster than other popular developer laptops that cost twice a much.
The Focus ships with libraries for deep-learning and gaming. However, adding repositories or packages can modify break them. You may check and reset these libraries using a terminal as shown below:
Use kfocus-001-conda to install an Anaconda suite. This is professionally vetted, comprehensive, and GPU accelerated. Open a terminal and enter the following:
Follow the prompts. CUDA 10.0 and 10.1 libraries are pre-installed. Prompt will pop up asking you to consider installing these additional components:
(GPU)cuDNN libraries (required)
(GPU)TensorRT libraries (required)
Pycharm is an excellent IDE for Python. It can be installed through the Jetbrains toolbox which is pre-installed on all Focus laptops.
Tests are run at the end of the script. It is non-destructive by default and can be rerun at any time. You may, for example, only install TensorFlow to start and then add Pytorch on a subsequent run. Run the AI suite at the end and compare to the results below.
Comprehensive TensorFlow benchmarks can be run at the end of the
kfocus-001-conda script. Please compare to the official results.
|RTX 2080||RTX 2070||RTX 2060||Titan X||Titan XPW10||Titan XP|
 Kubuntu Focus 2.2Kg, 20mm thick
 Unconstrained Desktop GPU
This is a partial revision history. See the
git repository for all entries.
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 70b4aa40Initial document
We try hard to provide a useful workflow validated by professionals. However, we cannot anticipate every situation, and therefore cannot guarantee this procedure will work for your needs. Always back up your data and test the workflow to determine the correct procedure for you.
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