Devices supported by HAMi
Applicable version: HAMi v2.10.0.
Last verified: 2026-11-06, against the HAMi source, default device configuration, and device guides.
The table below lists device integration status, allocation modes, and multi-card partitioning capabilities for released and experimental HAMi integrations. See the device guides below for the required plugins, drivers, and container runtimes.
Stable means available in v2.10.0. Experimental means the integration is still in development or validation and is not part of the released support in v2.10.0.
Teco is not included in v2.10.0. Device models and capabilities remain to be validated. Track subsequent integration work in HAMi #3369 and documentation PR #979.
Capability columns:
- Memory control: The memory quota or partition size that a container can request. Templates and fixed partition sizes round memory allocations up to the corresponding size.
- Compute control: Devices control compute resources through time slices, core allocation, hardware partitions, or QoS policies. See the linked references in the table for limitations.
- Multi-card partitioning: A single container can allocate resources across multiple physical devices while using only part of the resources on some of those devices. Allocating only whole devices does not count as multi-card partitioning. See the linked references for allocation granularity and limitations.
N/Ameans the mode allocates whole devices only.
Component integration guides
For NVIDIA sharing, Volcano vGPU and KAI Scheduler retain their own scheduling capabilities and use HAMi-core for runtime isolation; the KAI Scheduler integration provides memory isolation. HAMi-DRA works with the Kubernetes scheduler through DRA drivers; its NVIDIA sharing path uses HAMi-core to enforce memory and compute limits at runtime.
The table below links to device and scheduling component integration guides, including installation steps, configuration requirements, and limitations. - means no guide is available.
| Manufacturer | HAMi | HAMi-DRA | Volcano | KAI-scheduler |
|---|---|---|---|---|
| NVIDIA | Allocate device memory | Dynamic Resource Allocation | Use Volcano vGPU | Use KAI Scheduler |
| Cambricon | Enable Cambricon MLU sharing | - | - | - |
| Hygon | Enable Hygon DCU sharing | - | - | - |
| Huawei Ascend | Enable Huawei Ascend sharing | - | Volcano Ascend vNPU | - |
| Iluvatar | Enable Iluvatar GPU sharing | - | - | - |
| Mthreads | Enable Mthreads GPU sharing | - | - | - |
| MetaX | Enable MetaX GPU sharing | - | - | - |
| Enflame | Enable Enflame GCU sharing | - | - | - |
| Kunlunxin | Whole-device scheduling · VXPU sharing | - | - | - |
| Teco (Tecorigin) | - | - | - | - |
| Vastai | Enable Vastai sharing | - | - | - |
| AMD | Enable AMD GPU sharing | - | - | - |
| AWS | Manage AWS Neuron devices | - | - | - |
| Biren | Enable Biren sharing | - | - | - |
Device documentation index
NVIDIA
- Allocate device memory to container
- Dynamic Resource Allocation
- Enable dynamic MIG feature
- Scheduling Policies
- Allocate device core to container
- Assign to certain device type
- Assign to Certain Device UUID
- Using Extended ResourceQuota for NVIDIA Devices
- Use Exclusive GPU
- Allocate certain device memory to container
- Allocate a part of device memory by percentage to container
- Allocate device core to container
- Assign task to a certain type
- Assign task to a certain GPU
- Assign task to MIG instance
Cambricon
- Enable Cambricon MLU Sharing
- Allocate device memory
- Allocate device core usage
- Assign to certain device type
- Allocate device core and memory to container
- Allocate exclusive device
Hygon
- Enable Hygon DCU sharing
- Allocate device memory
- Allocate device core to container
- Assign to certain device
- Allocate device core and memory resource
- Allocate exclusive device
- Assign task to certain DCU cards
Mthreads
- Enable Mthreads GPU sharing
- Allocate device memory to container
- Allocate device core to container
- Allocate device core and memory resource
- Allocate exclusive device
Iluvatar
- Enable Iluvatar GPU Sharing
- Allocate BI-V150 slice
- Allocate MR-V100 slice
- Allocate exclusive BI-V150 device
- Allocate exclusive MR-V100 device
Enflame
AMD
AWS Neuron
Vastai
Biren
Kunlunxin
- Enable Kunlunxin GPU Topology-Aware Scheduling
- Enable Kunlunxin VXPU
- Allocate a whole xpu card
- Allocate vxpu device
MetaX
- Enable MetaX GPU sharing
- Allocate device core and memory resource
- Allocate exclusive device
- Allocate specific QoS policy devices
- Enable MetaX GPU topology-aware scheduling
- Binpack schedule policy
- Spread schedule policy
- Allocate metax device
- Binpack schedule policy
- Spread schedule policy
