Multi-Tenant GPU Virtualization and Hardware Isolation in Clusters

Enforcing secure multi-tenant GPU sharing using NVIDIA Multi-Instance GPU (MIG), Multi-Process Service (MPS), and hardware-level isolation.

The Multi-Tenant Security Dilemma in Shared AI Clusters

Hosting multiple enterprise departments or external clients on a shared GPU cluster dramatically improves infrastructure efficiency, but introduces severe security and performance isolation risks. Without hardware-level boundaries, a rogue tenant or out-of-memory error on one container can crash neighboring workloads or expose sensitive GPU memory cache data.

NVIDIA MIG (Multi-Instance GPU) Hardware Partitioning

InferCluster integrates natively with NVIDIA MIG architecture, physically partitioning a single physical GPU (such as H100) into up to seven independent hardware instances with dedicated memory controllers, cache, and compute cores. MIG guarantees absolute fault and memory isolation between competing tenants.

Time-Siced MPS for High-Density Micro-Tenancy

For lightweight workloads that do not require dedicated MIG slices, InferCluster orchestrates NVIDIA Multi-Process Service (MPS). MPS enables concurrent CUDA kernel execution across shared GPU resources while maintaining memory protection boundaries and prioritized task scheduling.

Tenant-Aware Scheduling and Quota Enforcement

InferCluster's scheduler enforces strict tenant quotas and security policies. Workloads from distinct tenants are mapped to dedicated namespace boundaries, ensuring that network traffic, KV-cache pools, and GPU slices remain strictly segregated across the cluster.

Sources and technical context

Sources provide documentation, standards and industry context. Analysis and scenarios are editorial, not endorsements, benchmarks or product guarantees. Verify current versions, requirements and terms in the primary documents. infercluster.com is an editorial research platform focused on high-density GPU cluster orchestration.

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Educational information only, not a complete architecture, security, legal, compliance, procurement or financial opinion. No security, compliance, performance or availability outcome is guaranteed. Capabilities and regulatory requirements vary by version, jurisdiction and configuration. Test in your own environment and consult qualified professionals before production use.