* Removed unused components. Updated tests.

Improved checkpointing model

Improved model, started with SimPowerSource

implemented FailureModels and Checkpointing

First working version

midway commit

first update

All simulation are now run with a single CPU and single MemoryUnit. multi CPUs are combined into one. This is for performance and explainability.

* fixed merge conflicts

* Updated M3SA paths.

* Fixed small typo

* Updated all package versions including kotlin. Updated all web-server tests to run.

* Changed the java version of the tests. OpenDC now only supports java 19.

* small update

* test update

* new update

* updated docker version to 19

* updated docker version to 19

This change removes the `TensorFlowExperiment` in favour of an
integration test that can be run during CI invocations. Given that the
experiment was not very sophisticated (in terms of data collection), we
believe it is better suited as an integration test.

This change removes the OpenTelemetry integration from the OpenDC
Tensorflow 2020 experiments. Previously, we chose to integrate
OpenTelemetry to provide a unified way to report metrics to the users.

See the previous commit removing it from the "Compute" modules for the
reasoning behind this change.

This change updates the `TFDevice` interface to directly expose
statistics about the accelerator device to the user. Previously, the
user had to access these values through OpenTelemetry, which required
substantial extra work.

This change removes the opendc-platform module from the project. This
module represented a Java platform which was previously used for sharing
a set of dependency versions between subprojects. However, with the
version catalogue that was added by Gradle, we currently do not use the
platform anymore.

This change adds a new module, opendc-common, that contains
functionality that is shared across OpenDC's modules.
We move the existing utils module into this new module.

This change removes the environment reader from the format library since
they are highly specific for the particular experiment. In the future,
we hope to have a single format to setup the entire datacenter (perhaps
similar to the format used by the web runner).

This change eliminates all Hadoop dependencies that are not necessary
for Parquet to work correctly. As a result, the number of dependencies
should now be greatly reduced, which in turn leads to less artifacts
that need to be retrieved at build time.