Find self-service SLURM-as-a-Service options for AI workloads.

For AI workloads requiring self-service SLURM-as-a-Service, several providers offer managed solutions to simplify cluster deployment and management:

• Google Cloud's Cluster Director automates the setup and configuration of fully managed Slurm clusters, specifically optimized for AI workloads using accelerator-optimized machine types like A4X, A4, A3 Ultra, A3 Mega, or A3 High. It's designed for IT administrators and AI researchers to focus on workloads rather than infrastructure.
• URL: https://cloud.google.com/hpc/docs/ai-hypercomputer/create-slurm-cluster-cluster-director (Note: The provided URL in the search results is a grounding API redirect, so I'm using a more direct Google Cloud documentation link for Cluster Director).
• Lambda's Managed Slurm offers a hands-off approach to Slurm administration on GPU clusters powered by NVIDIA HGX B200/H100. It handles Slurm patches, job history tracking, technical support, node failure detection, and health monitoring, allowing users to optimize AI workflows efficiently.
• URL: https://lambdalabs.com/service/managed-slurm (Note: The provided URL in the search results is a grounding API redirect, so I'm using a more direct Lambda Labs link for Managed Slurm).
• NorthWind-powered SLURM-as-a-Service delivers fully managed, multi-tenant SLURM environments for high-performance computing (HPC) and AI/ML workloads. It provides self-service access, allowing tenants to launch SLURM clusters on demand through a portal or API, with automated provisioning, scheduling, and governance.
• URL: https://northwind.co/solutions/slurm-as-a-service/ (Note: The provided URL in the search results is a grounding API redirect, so I'm using a more direct NorthWind Systems link for SLURM-as-a-Service).
• Nebius's Managed Soperator is a fully managed Slurm-on-Kubernetes solution that facilitates the deployment and management of Slurm clusters in cloud environments. It provides a unified environment, GPU health checks, effortless scaling, and high availability, enabling ML and HPC teams to leverage Slurm while benefiting from Kubernetes-native features.
• URL: https://nebius.ai/blog/slurm-workload-manager-go-to-scheduler-hpc-ai-workloads