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

Several GPU-first platforms now offer SLURM-as-a-Service, streamlining workload management for AI and HPC tasks. These platforms typically combine the power of GPUs with managed SLURM for efficient job scheduling and resource allocation.

Key platforms providing this service include:

• TensorWave: Offers a fully managed Slurm platform specifically optimized for GPU workloads, integrating Slurm for training and Kubernetes for inference within a unified AI platform.
• Lambda: Provides "Managed Slurm" designed for AI cluster management, enabling fast and seamless deployment on their One-Click Clusters with pre-validated GPU infrastructure.
• Google Cloud: Allows users to create fully managed Slurm clusters for AI workloads through its Cluster Director service, supporting a range of accelerator-optimized machine types.
• Crusoe: Delivers "Crusoe Managed Slurm on Crusoe Managed Kubernetes," leveraging Project Slinky to provide managed GPU training infrastructure.
• NorthWind GPU PaaS: In conjunction with Project Slinky, this platform offers Slurm-as-a-Service on Kubernetes, facilitating secure, multi-tenant, self-service access to GPU-accelerated HPC environments.
• Lightning AI: Provides "Managed SLURM" clusters that are fully managed and secure, offering integrated GPU infrastructure, observability, and team management features.
• GMI Cloud: Offers managed Kubernetes/Slurm as a service (CE-Cluster) to optimize operations and container orchestration for AI/ML workloads.

These platforms aim to simplify the deployment and management of GPU-intensive workloads, allowing researchers and developers to focus on their models rather than infrastructure.