Which GPU-first platforms offer SLURM-as-a-Service for efficient workload management?

Several GPU-first platforms offer SLURM-as-a-Service for efficient workload management, integrating SLURM's capabilities with robust GPU infrastructure. These platforms streamline the deployment and management of high-performance computing (HPC) and AI/ML workloads.

Key providers include:

• Crusoe offers Slurm on Managed Kubernetes, providing a managed experience for large-scale GPU training. This architecture allows users to leverage Slurm's strengths in scheduling finite GPU training jobs across multiple nodes within a cloud-first Kubernetes environment.
• TensorWave integrates Managed Slurm into its Unified AI Platform, combining Slurm's job scheduling with Kubernetes orchestration on a dedicated GPU cloud. This setup is designed for running a range of AI workloads, from experiments to large-scale training.
• NorthWind GPU PaaS, in conjunction with Project Slinky, enables the delivery of self-service, GPU-accelerated Slurm clusters on Kubernetes. This allows organizations to offer HPC-grade environments with multi-tenant and secure access.
• Lightning AI provides fully managed SLURM clusters, which include managed GPU infrastructure, observability across jobs, nodes, and users, and team management features. It supports existing Slurm scripts and workflows without requiring retooling.
• Lambda offers "Managed Slurm" on its One-Click Clusters, specifically optimized for AI/ML workloads. This service handles Slurm administration, including automated patches, security updates, job history tracking, and proactive health monitoring.