Deploying AI Frameworks on Secure HPC Systems with Containers

05/24/2019
by   David Brayford, et al.
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The increasing interest in the usage of Artificial Intelligence techniques (AI) from the research community and industry to tackle "real world" problems, requires High Performance Computing (HPC) resources to efficiently compute and scale complex algorithms across thousands of nodes. Unfortunately, typical data scientists are not familiar with the unique requirements and characteristics of HPC environments. They usually develop their applications with high-level scripting languages or frameworks such as TensorFlow and the installation process often requires connection to external systems to download open source software during the build. HPC environments, on the other hand, are often based on closed source applications that incorporate parallel and distributed computing API's such as MPI and OpenMP, while users have restricted administrator privileges, and face security restrictions such as not allowing access to external systems. In this paper we discuss the issues associated with the deployment of AI frameworks in a secure HPC environment and how we successfully deploy AI frameworks on SuperMUC-NG with Charliecloud.

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gmkurtzer

According to the article:

"Although Singularity has been developed to run in a non-privileged namespace, security issues have arisen on a test system at LRZ where users have escalated their privileges and the system had to be taken out of service."


If this is true, and you found a security issue, why did you not tell the Singularity developers? In looking through all security announcements and disclosures from the Singularity project, I don't see any that credit you or LRZ.  Additionally, Singularity, has a completely privilege-less mode using the "user namespace" and you can disable support for SquashFS/SIF images. Seems like a statement about "security breeches" and removal from the system is unjustified and overly dramatic.

Authors

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