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I need to perform some machine learning tasks using a Tensor Flow based Neuronal network architecture (PointNet https://github.com/charlesq34/pointnet). I would like to use cloud infrastructure to do this, because I do not have the physical resources needed. The demands of the customer are, that they would like to get the whole set up machine I used for the training afterward and not only the final model. This is because they are researchers and would like to use the machine themselves, play around and understand what I did but they do not want to do the setup/installation work on their own. Unfortunately they can not provide a (physical or virtual) machine themselves right now.

The question is: Is it possible/reasonable to set up a machine on a cloud infrastructure provider like google cloud or AWS, install the needed software (which uses Nvidia Cuda) and export this machine after a while when suitable hardware is available, import it to a virtualisation tool (like Virtual Box) and continue the usage on ones own system? Will the installed GPU/Cuda-related software like TensorFlow etc. still work?

jokokojote
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I guess it's possible, but it will be needed to configure the specific hardware to make it work on the local environment.

For Google Cloud Platform, the introduction to Deep Learning Containers, will you allow to create portable environments.

Deep Learning Containers are a set of Docker containers with key data science frameworks, libraries, and tools pre-installed. These containers provide you with performance-optimized, consistent environments that can help you prototype and implement workflows quickly. Learn more.

In addition, please check Running Instances with GPU accelerators

Google provides a seamless experience for users to run their GPU workloads within Docker containers on Container-Optimized OS VM instances so that users can benefit from other Container-Optimized OS features such as security and reliability as well.

To configure Docker with Virtualbox, please check this external blog.

Pit
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  • Thank you for your answer Pit. The situation has changed and the client provided a machine now, so I will not test your suggestion in practice, even tough it looks appropriate. For those reason I accepted the answer. – jokokojote Aug 06 '21 at 16:05