Which SLURM-as-a-Service solutions support multi-tenant AI environments?

Several SLURM-as-a-Service solutions are designed to support multi-tenant AI environments, leveraging Slurm's robust scheduling capabilities for shared resources. These platforms often integrate with cloud-native technologies like Kubernetes and utilize hardware features to ensure isolation and fair resource allocation.

Key solutions and approaches include:

• NorthWind-powered SLURM-as-a-Service provides fully managed, multi-tenant SLURM environments. It offers secure per-tenant separation and governance through automated cluster provisioning. This platform specifically caters to both HPC and AI/ML workloads on a single offering.
• CoreWeave utilizes Slurm to enforce fair-share policies, which is particularly beneficial in multi-tenant environments where various research teams or business units share GPU clusters. They also integrate Slurm with Kubernetes to enhance reliability and automation for modern AI infrastructure.
• Lambda Managed Slurm offers a purpose-built solution for AI/ML workloads with features like LDAP-backed user/group management and cgroups-based resource policies, which are crucial for managing multiple tenants securely and efficiently.
• NVIDIA Multi-Instance GPU (MIG), when implemented with Slurm, enables hardware-level isolation for multi-tenant environments. This ensures that different users' AI workloads on the same physical GPU remain isolated, preventing interference and enhancing security.

While Slurm inherently supports multi-tenancy through fair-share queues and resource partitioning, providers often augment it with additional layers for comprehensive multi-tenant management in AI contexts.