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Showing posts with the label Container

Use an NVIDIA Container Image to verify container access to NVIDIA GPUs

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Verify that your container can communicate with the GPU and the type of NVIDIA GPUs your Docker containers can access using one of NVIDIA's container images. docker run --rm --runtime=nvidia --gpus all ubuntu nvidia-smi  Sample Output The containers on this server have access to a single Titan RTX card Source This came from  NVIDIA getting started with large language models Revision  Created 2024/07  Corrected NVIDIA captialization 2025/08

Software Development in a Container - Coding by Copy - a Primer

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Containers make it easy to set up a complex data scientist development environment.  A developer can just spin up a Python, Jupyter Notebook, Spark, Hadoop, or another type of container on a local machine in minutes. Containers can be confusing when you first work with them. Here we talk a little about how you can get code and data into your container environment and how you can get it back out. I want to write code  local  to my laptop and run the code inside a fully configured Anaconda container. And, I'm lazy. Two ways to get code onto a container for development Containers are standalone  mini machines  with private disk space, CPU, networking  and other services.  They are not intended to retain state, something that we definitely want to do in a development environment. We need to get our code inside the container. We can do the same thing with data or we can have our code pull the data in at runtime. We plan on doing all  development on ...

Software Development in a Container - Mounting code into the container - A Primer

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Containers make it easy to set up a complex data scientist development environment.  A developer can just spin up a Python, Jupyter Notebook, Spark, Hadoop, or another type of container on a local machine in minutes. Containers can be confusing when you first work with them. Here we talk a little about how you can get code and data into your container environment and how you can get it back out. I want to write code local to my laptop and run the code inside a fully configured Anaconda container. And, I'm lazy. Two ways to get code onto a container for development Containers are standalone mini machines with private disk space, CPU, networking  and other services.  They are not intended to retain state, something that we definitely want to do in a development environment. We need to get our code inside the container. We can do the same thing with data or we can have our code pull the data in at runtime. There are two primary ways of getting code onto a machine.  We c...