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+# GPU Sharing User guide
+
+## Environment setup
+
+### Install volcano
+
+
+#### 1. Install from source
+
+Refer to [Install Guide](../../installer/README.md) to install volcano.
+
+After installed, update the scheduler configuration:
+
+```shell script
+kubectl edit cm -n volcano-system volcano-scheduler-configmap
+```
+
+```yaml
+kind: ConfigMap
+apiVersion: v1
+metadata:
+  name: volcano-scheduler-configmap
+  namespace: volcano-system
+data:
+  volcano-scheduler.conf: |
+    actions: "enqueue, allocate, backfill"
+    tiers:
+    - plugins:
+      - name: priority
+      - name: gang
+      - name: conformance
+    - plugins:
+      - name: drf
+      - name: predicates
+        arguments:
+          predicate.GPUSharingEnable: true # enable gpu sharing
+      - name: proportion
+      - name: nodeorder
+      - name: binpack
+```
+
+#### 2. Install from release package.
+
+Same as above, after installed, update the scheduler configuration in `volcano-scheduler-configmap` configmap.
+
+### Install Volcano device plugin
+
+Please refer to [volcano device plugin](https://github.com/volcano-sh/devices/blob/master/README.md#quick-start)
+
+### Verify environment is ready
+
+Check the node status, it is ok if `volcano.sh/gpu-memory` and `volcano.sh/gpu-number` are included in the allocatable resources. 
+
+```shell script
+$ kubectl get node {node name} -oyaml
+...
+status:
+  addresses:
+  - address: 172.17.0.3
+    type: InternalIP
+  - address: volcano-control-plane
+    type: Hostname
+  allocatable:
+    cpu: "4"
+    ephemeral-storage: 123722704Ki
+    hugepages-1Gi: "0"
+    hugepages-2Mi: "0"
+    memory: 8174332Ki
+    pods: "110"
+    volcano.sh/gpu-memory: "89424"
+    volcano.sh/gpu-number: "8"    # GPU resource
+  capacity:
+    cpu: "4"
+    ephemeral-storage: 123722704Ki
+    hugepages-1Gi: "0"
+    hugepages-2Mi: "0"
+    memory: 8174332Ki
+    pods: "110"
+    volcano.sh/gpu-memory: "89424"
+    volcano.sh/gpu-number: "8"   # GPU resource
+```
+
+### Running GPU Sharing Jobs
+
+NVIDIA GPUs can now be shared via container level resource requirements using the resource name `volcano.sh/gpu-memory`:
+```shell script
+$ cat <<EOF | kubectl apply -f -
+apiVersion: v1
+kind: Pod
+metadata:
+  name: gpu-pod1
+spec:
+  containers:
+    - name: cuda-container
+      image: nvidia/cuda:9.0-devel
+      command: ["sleep"]
+      args: ["100000"]
+      resources:
+        limits:
+          volcano.sh/gpu-memory: 1024 # requesting 1024MB GPU memory
+EOF
+
+$ cat <<EOF | kubectl apply -f -
+apiVersion: v1
+kind: Pod
+metadata:
+  name: gpu-pod2
+spec:
+  containers:
+    - name: cuda-container
+      image: nvidia/cuda:9.0-devel
+      command: ["sleep"]
+      args: ["100000"]
+      resources:
+        limits:
+          volcano.sh/gpu-memory: 1024 # requesting 1024MB GPU memory
+EOF
+```
+
+If only the above pods are claiming gpu resource in a cluster, you can see the pods sharing one gpu card:
+
+```shell script
+$ kubectl exec -ti  gpu-pod1 env
+...
+VOLCANO_GPU_TOTAL=11178
+VOLCANO_GPU_ALLOCATED=1024
+NVIDIA_VISIBLE_DEVICES=0
+...
+
+$ kubectl exec -ti  gpu-pod1 env
+...
+VOLCANO_GPU_TOTAL=11178
+VOLCANO_GPU_ALLOCATED=1024
+NVIDIA_VISIBLE_DEVICES=0
+...
+```
+
+### Understanding how GPU sharing works
+
+The GPU sharing workflow is depicted as below:
+
+![gpu_sharing](../images/gpu-share-flow.png)
+
+1. create a pod with `volcano.sh/gpu-memory` resource request,
+
+2. volcano scheduler predicates and allocate gpu resource for the pod. Adding the below annotation
+
+```yaml
+annotations:
+  volcano.sh/gpu-index: “0”
+  volcano.sh/predicate-time: “1593764466550835304”
+```
+
+3. kubelet watches the pod bound to itself, and call allocate API to set env before running the container.
+
+```yaml
+env:
+  NVIDIA_VISIBLE_DEVICES: “0” # GPU card index
+  VOLCANO_GPU_ALLOCATED: “1024” # GPU allocated
+  VOLCANO_GPU_TOTAL: “11178” # GPU memory of the card
+```
+
+
+
+