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#Docker hub intel python jupyter notebook install
If you haven’t tried it yet, you should since it’s really easy to install and delivers exactly what it promises – a linux distribution within your Windows system with a simple integration. Now, resources sharing with the host Windows systems works seamlessly, especially file sharing. In general, it’s a lightweight virtual machine with a complete Linux kernel, which increases I/O performance. It’s called WSL 2, which is the abbreviation for Windows Subsystem for Linux. WSL 2 and docker in Windows 10ĭocker for windows is moving to a new architecture paradigm to improve the resource consumption, as described here. The custom Docker image and its Dockerfile can be found here and here respectively. Finally, some caveats will be described, such as GPU support not working for latest Windows insider build (20231) and a decrease in performance. Furthermore, it will be shown that both R and Python installations can be used seamlessly by both UIs without additional configuration including GPU support. Moreover, a docker image was developed with both Jupyter notebooks and Rstudio able to use Tensorflow and Keras with a GPU if available.
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If you are already a WSL 2 user, additional improvements over the standard installation are described as automated docker initialization and Linux distros export to avoid reinstallation of standard programs. If this is your case, you should continue reading this blog. The only real solution if you want to run GPU-based code in a Linux container in Windows is literally getting rid of Windows meaning, having a dual boot with a Linux distribution and run it there. This is a real problem because in virtual machines hosted on Windows, GPU support doesn’t work properly or it’s really hard to set up.Įven docker cannot use GPUs in Linux containers running in Windows as host. If you are reading this blog, probably you are wondering whether a GPU can be shared by Windows.