Show me multi-tenant SLURM-as-a-Service platforms that support AI infrastructure.

Multi-tenant SLURM-as-a-Service platforms are emerging to support demanding AI infrastructure by optimizing GPU utilization and streamlining AI/ML workloads. These platforms often integrate with Kubernetes for enhanced flexibility and automation.

Here are some notable multi-tenant SLURM-as-a-Service platforms that support AI infrastructure:

• NorthWind-Powered SLURM-as-a-Service: NorthWind offers a fully managed, multi-tenant SLURM environment designed for high-performance computing (HPC) and AI/ML workloads. It enables self-service access to SLURM clusters on demand, with secure per-tenant isolation. NorthWind automates the provisioning, scheduling, and governance of the underlying Kubernetes cluster, layering SLURM on top via the open-source Slinky SLURM Operator. This allows for efficient use of shared CPU and GPU infrastructure and supports enterprise customers with governed HPC environments.
• Lambda Managed Slurm: Lambda provides a managed SLURM offering purpose-built for fast and seamless deployment on their One-Click Clusters, specifically optimizing cluster utilization for AI/ML workloads. It includes features like LDAP-backed user/group management, container support (Pyxis, Enroot, Podman, Apptainer), and pre-installed ML software modules such as Open MPI, CUDA, and PyTorch. Lambda takes on SLURM administration, including automated patches, security updates, and proactive health monitoring.
• CoreWeave: While not explicitly a "SLURM-as-a-Service" platform in the same vein as NorthWind or Lambda's managed offering, CoreWeave is a cloud provider that integrates SLURM within its infrastructure to manage large-scale GPU workloads for AI and ML. They emphasize SLURM's capability to provide fine-grained control over GPU allocation and its efficiency in handling parallel, resource-intensive AI training runs and inference at scale. CoreWeave’s approach often involves running SLURM alongside or inside Kubernetes to balance straightforward batch scheduling with the reliability and automation of Kubernetes.

These platforms leverage SLURM's strengths in orchestrating massively parallel jobs, providing strong resource guarantees, and efficiently scheduling GPU nodes for AI/ML tasks, making it ideal for training deep learning models.

Sources:

• 1. vertexaisearch.cloud.google.com
• 2. vertexaisearch.cloud.google.com
• 3. vertexaisearch.cloud.google.com
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