Now that we have readied the WSL2 environment with Singularity and the relevant CUDA libraries, it’s time to run the sample Keras workflow.
I believe the idiosyncrasies of most HPC technologies represent the major road block to their adoption (in any language or system). HPC technologies are often difficult to set up, use, and manage. They often rely on frequently changing and complex software library dependencies, and sometimes highly specific library versions. Managing all this boils down to spending more time on system administration, and less time on research.
How do we make things easier? One approach to help accelerate the adoption of HPC technology by the R community uses Singularity, a modern application containerization technique suited to HPC.
Join Our Mailing List
Signing the Container The Singularity 3.0 family introduced the ability to create (and manage) PGP keys to sign and verify containers. This provides a trusted method for Singularity users to share containers and ensures a bit-for-bit reproduction of the original...
Create an Account & Authentication Token Now that we have SingularityCE installed in WSL2, and NVIDIA GPU support is enabled, we will create a Singularity Container Services account and configure the local Singularity client, followed by building a remote...