As AI workloads move from experimentation to production, enterprises are consolidating GPU infrastructure into shared platforms. However, organizations that take this road face several tradeoffs. For instance, instead of dedicating entire accelerator nodes to a single workload, organizations are increasingly aiming to support multiple tenants per node. This boosts overall efficiency, because underutilizing GPUs by dedicating them to individual workloads increases infrastructure cost. But in such multitenant GPU environments, poor isolation can lead to serious issues, including performance inte