The command arena top job <job name>
can display GPU monitoring metrics. Before using it, you must deploy a Prometheus and nodeExporter for GPU Metrics.
1. Deploy a Prometheus
kubectl apply -f kubernetes-artifacts/prometheus/prometheus.yaml
2. Deploy GPU node exporter
- If your cluster is ACK (Alibaba Cloud Kubernetes) cluster, you can just exec command:
# change gpu export nodeSelector to aliyun label
sed -i 's|accelerator/nvidia_gpu|aliyun.accelerator/nvidia_count|g' kubernetes-artifacts/prometheus/gpu-expoter.yaml
- If your cluster is not ACK cluster, you need to label your GPU node:
# label all your GPU nodes
kubectl label node <your GPU node> accelerator/nvidia_gpu=true
- Deploy gpu exporter
kubectl apply -f kubernetes-artifacts/prometheus/gpu-exporter.yaml
Notice: the prometheus and gpu-exporter components should be deployed in namespace
kube-system
, and so thatarena top job <job name>
can work.
3. You can check the GPU metrics by prometheus SQL request
# kubectl get --raw '/api/v1/namespaces/arena-system/services/prometheus-svc:prometheus/proxy/api/v1/query?query=nvidia_gpu_num_devices'
{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"nvidia_gpu_num_devices","app":"node-gpu-exporter","instance":"172.16.1.144:9445","job":"kubernetes-service-endpoints","k8s_app":"node-gpu-exporter","kubernetes_name":"node-gpu-exporter","node_name":"mynode"},"value":[1543202894.919,"2"]}]}}
4. Submit a traing job by arena
arena submit tf --name=style-transfer \
--gpus=2 \
--workers=2 \
--workerImage=registry.cn-hangzhou.aliyuncs.com/tensorflow-samples/neural-style:gpu \
--workingDir=/neural-style \
--ps=1 \
--psImage=registry.cn-hangzhou.aliyuncs.com/tensorflow-samples/style-transfer:ps \
"python neural_style.py --styles /neural-style/examples/1-style.jpg --iterations 1000000"
5. Check GPU metrics for the job you deployed
# arena top job style-transfer
INSTANCE NAME STATUS NODE GPU(Device Index) GPU(Duty Cycle) GPU(Memory MiB)
style-transfer-tfjob-ps-0 Running 192.168.0.95 N/A N/A N/A
style-transfer-tfjob-worker-0 Running 192.168.0.98 0 98% 15641MiB / 16276MiB
1 0% 15481MiB / 16276MiB
style-transfer-tfjob-worker-1 Running 192.168.0.99 0 98% 15641MiB / 16276MiB
1 0% 15481MiB / 16276MiB