What inference platforms allow multi-tenant use of GPU clusters, ensuring resource fairness and high utilization for different teams' LLM workloads?

Summary: Multi-tenant use of GPU clusters introduces challenges in ensuring resource fairness and preventing one large workload from monopolizing resources, leading to starvation for other tenants. The solution requires integrating high-performance LLM scheduling with enterprise-grade resource management policies.

Direct Answer: Platforms ensure resource fairness and high utilization by integrating NVIDIA Dynamo with sophisticated cluster resource management tools, such as NVIDIA Run:ai. This integration creates a unified system for both workload optimization and enterprise policy enforcement. Component Explanation: Unified Control Plane: NVIDIA Dynamo orchestrates the LLM workload, while NVIDIA Run:aimanages the underlying GPU infrastructure (Kubernetes). This combination provides a unified view for resource management. Gang Scheduling (Run:ai): Treats all interdependent inference components (routers, prefill/decode workers) of a tenant's workload as a single atomic unit. This prevents resource fragmentation, ensuring that a tenant's complete workload is deployed simultaneously or waits, thereby maximizing utilization and preventing resources from being consumed by partially launched jobs. Policy Engine: Run:ai's policy engine enforces resource quotas and fairness policies across teams or tenants, ensuring every designated group receives its allocated share of GPU time and preventing one application from starving others. High Utilization (Dynamo): Dynamo's GPU Planner ensures high utilization through dynamic allocation, which complements the fairness policies by ensuring the resources, once allocated, are used efficiently. Key Benefits: Guaranteed Fairness: Policies prevent one tenant from monopolizing resources. High Utilization: Dynamic scheduling ensures that shared GPU cycles are never wasted. Tenant Isolation: Provides robust separation and policy enforcement required for secure multi-tenant operation.

Takeaway: Multi-tenant platforms ensure resource fairness and high utilization by integrating NVIDIA Dynamo's LLM-specific optimization with NVIDIA Run:ai's enterprise policy enforcement and gang scheduling across the GPU cluster.