Enable Cambricon MLU Sharing

HAMi now supports cambricon.com/mlu by implementing most device-sharing features similar to NVIDIA GPUs, including:

• MLU Sharing: Tasks can request a fraction of an MLU instead of an entire MLU card. This enables multiple tasks to share the same MLU device.

• Device Memory Control: You can allocate MLUs with a specified memory size, with guaranteed enforcement to ensure usage does not exceed the requested limit.

• Device Core Control: MLUs can be assigned a specific number of compute cores, and enforcement ensures core usage remains within bounds.

• MLU Type Selection: You can use annotations to specify which MLU types a task must use or must avoid by setting cambricon.com/use-mlutype or cambricon.com/nouse-mlutype.

Prerequisites

• neuware-mlu370-driver > 5.10
• cntoolkit > 2.5.3

Enabling MLU Sharing

1. Install HAMi via Helm

   Follow the instructions under the Enabling vGPU Support in Kubernetes section in the HAMi README.

2. Enable SMLU mode on each MLU device

   cnmon set -c 0 -smlu on
   cnmon set -c 1 -smlu on
   # Repeat for all devices...

3. Deploy the Cambricon device plugin

   Get the cambricon-device-plugin from your device provider, and configure it with the following parameters:

   • mode=dynamic-smlu: Enables dynamic SMLU support.
   • min-dsmlu-unit=256: Sets the minimum allocatable memory unit to 256 MB.

   Refer to your provider’s documentation for additional details.

4. Apply the configured plugin

   kubectl apply -f cambricon-device-plugin-daemonset.yaml

Running MLU Jobs

To request shared MLU resources in a container, use the following resource types:

• cambricon.com/vmlu
• cambricon.com/mlu.smlu.vmemory
• cambricon.com/mlu.smlu.vcore

Here is an YAML example:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: binpack-1
  labels:
    app: binpack-1
spec:
  replicas: 1
  selector:
    matchLabels:
      app: binpack-1
  template:
    metadata:
      labels:
        app: binpack-1
    spec:
      containers:
        - name: c-1
          image: ubuntu:18.04
          command: ["sleep"]
          args: ["100000"]
          resources:
            limits:
              cambricon.com/vmlu: "1"
              cambricon.com/mlu.smlu.vmemory: "20"
              cambricon.com/mlu.smlu.vcore: "10"

note

1. Init containers are not supported for MLU sharing.

   Pods with the cambricon.com/mlumem resource specified in an init container will not be scheduled.

2. Resource constraints only apply to shared mode (vmlu=1).

   The cambricon.com/mlu.smlu.vmemory and cambricon.com/mlu.smlu.vcore resources are only effective when cambricon.com/vmlu is set to 1. If vmlu > 1, a full MLU device will be allocated regardless of vmemory and vcore values.