Now that we have readied the WSL2 environment with Singularity and the relevant CUDA libraries, it’s time to run the sample Keras workflow.
Nowadays Linux Containers which have operating system level virtualization, are very popular over virtual machines (VMs) which have hypervisor or kernel level virtualization in high performance computing (HPC) due to reasons, such as high portability, high performance, efficiency and high security. Hence, LXCs can make an efficient and secure big data analytic framework with the help of secure, efficient, easily scalable, and highly available databases. A concern for security on high performance computing clusters is high for the transdisciplinary Texas Tech University (TTU) EXPOSOME Project. This project mainly focuses on sensitive healthcare data which is operating in the Quanah Linux cluster in the High Performance Computing Center of Texas Tech University.
A Review of MongoDB and Singularity Container Security in regards to HIPAA Regulations:
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...