HAMi vs NVIDIA Base Command Manager

HAMi is open-source middleware for sharing and scheduling GPUs and other accelerators among AI workloads on Kubernetes. Workloads can request GPU memory and core limits through Kubernetes resource controls. Scheduling options include binpack, spread and numa-first, with binpack and spread available at node or GPU scope. The supported-device list spans NVIDIA, AMD, AWS Neuron, Huawei Ascend, Cambricon, Enflame, Hygon, Iluvatar, Kunlunxin, MetaX, Moore Threads, Vastai and Biren; isolation and partitioning capabilities vary by device. HAMi works with Kubernetes APIs, DRA and CDI, and documents scheduling integrations including Volcano, Kueue, Koordinator and NVIDIA KAI Scheduler. Its node metrics endpoint exposes device memory and core utilization for Prometheus. Classic HAMi requires Kubernetes v1.23 or later. HAMi-DRA requires Kubernetes v1.34 or later, the DRA Consumable Capacity feature gate, CDI and NVIDIA driver 440 or later. NVIDIA limits use user-space library interception, which does not cover applications that bypass CUDA. Enforcement is described as soft and best-effort; the FAQ recommends MIG when hardware-enforced isolation is required.

NVIDIA Base Command Manager provides Linux and web tools for deploying and administering compute environments. It supports OS image deployment, PXE bootstrapping, lifecycle management, hardware inventory, API access, and out-of-band management. The Free-to-use Base Command Manager plan costs nothing and allows 8 accelerators per server, node, or system, with no limit on the number of servers, nodes, or systems. A standalone-support option combines the manager license with NVIDIA Enterprise Support. NVIDIA AI Enterprise adds GPU Operator, Network Operator, vGPU, and AI and data-science software. NVIDIA Mission Control includes Run:ai, UFM, NetQ, and additional Mission Control capabilities. The product therefore offers a no-cost base tier alongside options that add support or broader NVIDIA management and software capabilities.