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Survey of Adaptive Containerization Architectures for HPC
DescriptionContainers offer an array of advantages that benefit research reproducibility and portability. As container tools mature, container security improves, and high-performance computing (HPC) and cloud system tools converge, supercomputing centers are increasingly integrating containers into their workflows. Despite this, most research into containers remains focused on cloud environments.
We consider an adaptive containerization architecture approach, in which each component chosen represents the tool best adapted to the given system and site requirements, with a focus on accelerating the deployment of applications and workflows on HPC systems using containers. To this end, we discuss the HPC specific requirements regarding container tools, and analyze the entire containerization stack, including container engines and registries, in-depth. Finally, we consider various orchestrator and HPC workload manager integration scenarios, including Workload Manager (WLM) in Kubernetes, Kubernetes in WLM, and bridged scenarios. We present a proof-of-concept approach to a Kubernetes Agent in a WLM allocation.
We consider an adaptive containerization architecture approach, in which each component chosen represents the tool best adapted to the given system and site requirements, with a focus on accelerating the deployment of applications and workflows on HPC systems using containers. To this end, we discuss the HPC specific requirements regarding container tools, and analyze the entire containerization stack, including container engines and registries, in-depth. Finally, we consider various orchestrator and HPC workload manager integration scenarios, including Workload Manager (WLM) in Kubernetes, Kubernetes in WLM, and bridged scenarios. We present a proof-of-concept approach to a Kubernetes Agent in a WLM allocation.
