Achieving Cloud-Native HPC Capabilities in a Mixed Workload Environment
As the lines blur between traditional workloads and new applications like deep-learning, containers becoming are a hot topic in enterprise HPC as well. Not surprisingly, like their internet colleagues deploying cloud-scale services, HPC architects see value in cloud-native approaches. HPC developers have been building distributed applications since before clusters were cool, open source is in their DNA, and they also appreciate the elegance of parallelism, resilience and horizontal scaling. While the term CI/CD didn’t originate in HPC, some HCP admins face the same challenge as their DevOps colleagues, needing to deploy new functionality quickly and reliably.
Barriers to Adoption
So why don’t we see a mass migration to the cloud and widespread availability of containerized HPC applications expressed as Kubernetes YAML templates? As is often the case, the answer is complicated.
There are several issues, but we explore two in more detail below.
- Significant investments in certified and trusted application workflows
- Technical considerations related to workload management
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