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Running Linux and Windows on M1 with QEMU

30.11.2020: Updated with the new patchseries and instructions for Windows

02.12.2020: Added tweaks

08.12.2020: Updated with patchseries v4

31.01.2020: Updated with patchseries v6

The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.

The correct way of creating a private frok by duplicating the repo is documented here.

For this assignment the commands are:

Create a bare clone of the repository. (This is temporary and will be removed so just do it wherever.)

git clone --bare [email protected]:usi-systems/easytrace.git

Getting a USB device to show up in a Docker container on OS X

Some background

I was trying to get the Arduino IDE to work inside a Docker container on OS X. I was able to get the IDE working (see Getting X11 GUI applications to work on OS X with Docker), but I could not figure out how to make the USB port for the Arduino visible.

The solution

I first tried to directly map hardware serial port into the Docker container, doing something like this:

	# This file contains the sources.list files as found on preinstalled Ubuntu 18.04
	# on the Dell Precision 5750 laptop. Since the hardware is very similar,
	# they will probably also work on the Dell XPS 17 9700.

	# /etc/apt/sources.list not included here
	# - just the stock Ubuntu bionic sources.list

	# the following are stored in /etc/apt/sources.list.d/*.list

	# bionic-dell.list

	# WSL2 network port forwarding script v1
	# for enable script, 'Set-ExecutionPolicy -ExecutionPolicy Bypass -Scope CurrentUser' in Powershell,
	# for delete exist rules and ports use 'delete' as parameter, for show ports use 'list' as parameter.
	# written by Daehyuk Ahn, Aug-1-2020

	# Display all portproxy information
	If ($Args[0] -eq "list") {
	netsh interface portproxy show v4tov4;
	exit;
	}

	from __future__ import print_function
	'''
	Basic Multi GPU computation example using TensorFlow library.
	Author: Aymeric Damien
	Project: https://github.com/aymericdamien/TensorFlow-Examples/
	'''

	'''
	This tutorial requires your machine to have 1 GPU
	"/cpu:0": The CPU of your machine.