Esta página descreve como executar testes da Biblioteca de Comunicação Coletiva da NVIDIA (NCCL, na sigla em inglês) em clusters personalizados do GKE que usam os protocolos de rede GPUDirect-TCPXO e
GPUDirect-TCPX. Um cluster do GKE personalizado é um cluster que você cria usando comandos gcloud.
É possível usar os testes descritos nesta página para os seguintes cenários:
- Se o cluster do GKE usar nós de início flexível, use um teste básico em dois nós.
- Se o cluster do GKE usar diferentes tipos de nós, como nós sob demanda ou vinculados à reserva, use um teste de NCCL com programação consciente da topologia.
Antes de começar
Os testes nesta página usam o JobSet e o Kueue com a programação consciente da topologia (TAS, na sigla em inglês). Antes de executar qualquer teste, configure o cluster e faça o seguinte:
Instale o Kueue.
kubectl apply --server-side -f https://github.com/kubernetes-sigs/kueue/releases/download/v0.16.5/manifests.yaml
Configurar o cluster com o Jobset e o Kueue
Depois de instalar o JobSet e o Kueue, siga estas etapas:
Salve o seguinte manifesto como
kueue-config.yaml:A3 Alto
apiVersion: kueue.x-k8s.io/v1beta2 kind: Topology metadata: name: "gke-default" spec: levels: - nodeLabel: "cloud.google.com/gce-topology-block" - nodeLabel: "cloud.google.com/gce-topology-subblock" - nodeLabel: "cloud.google.com/gce-topology-host" - nodeLabel: "kubernetes.io/hostname" --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ResourceFlavor metadata: name: a3-high-flavor spec: nodeLabels: cloud.google.com/gke-accelerator: nvidia-h100-80gb topologyName: "gke-default" --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ResourceFlavor metadata: name: a3-high-dws-flavor spec: nodeLabels: cloud.google.com/gke-accelerator: nvidia-h100-80gb topologyName: "gke-default" tolerations: - key: "cloud.google.com/gke-queued" operator: "Exists" effect: NoSchedule --- apiVersion: kueue.x-k8s.io/v1beta2 kind: AdmissionCheck metadata: name: dws-prov spec: controllerName: kueue.x-k8s.io/provisioning-request parameters: apiGroup: kueue.x-k8s.io kind: ProvisioningRequestConfig name: dws-config --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ProvisioningRequestConfig metadata: name: dws-config spec: provisioningClassName: queued-provisioning.gke.io podSetUpdates: - key: autoscaling.gke.io/provisioning-request valueFromProvisioningClassDetail: ResizeRequestName managedResources: - nvidia.com/gpu --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ClusterQueue metadata: name: cq-tas spec: namespaceSelector: {} clusterQueueingStrategy: BestEffortFIFO resourceGroups: - flavors: - name: a3-high-flavor resources: - name: "cpu" nominalQuota: 1000 - name: "memory" nominalQuota: 1000Ti - name: "nvidia.com/gpu" nominalQuota: 1000 - name: a3-high-dws-flavor resources: - name: "cpu" nominalQuota: 1000 - name: "memory" nominalQuota: 1000Ti - name: "nvidia.com/gpu" nominalQuota: 1000 admissionChecksStrategy: admissionChecks: - name: "dws-prov" onFlavors: [a3-high-dws-flavor] --- apiVersion: kueue.x-k8s.io/v1beta2 kind: LocalQueue metadata: namespace: default name: lq-tas spec: clusterQueue: cq-tasA3 Mega
apiVersion: kueue.x-k8s.io/v1beta2 kind: Topology metadata: name: "gke-default" spec: levels: - nodeLabel: "cloud.google.com/gce-topology-block" - nodeLabel: "cloud.google.com/gce-topology-subblock" - nodeLabel: "cloud.google.com/gce-topology-host" - nodeLabel: "kubernetes.io/hostname" --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ResourceFlavor metadata: name: a3-mega-flavor spec: nodeLabels: cloud.google.com/gke-accelerator: nvidia-h100-mega-80gb topologyName: "gke-default" --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ResourceFlavor metadata: name: a3-mega-dws-flavor spec: nodeLabels: cloud.google.com/gke-accelerator: nvidia-h100-mega-80gb topologyName: "gke-default" tolerations: - key: "cloud.google.com/gke-queued" operator: "Exists" effect: NoSchedule --- apiVersion: kueue.x-k8s.io/v1beta2 kind: AdmissionCheck metadata: name: dws-prov spec: controllerName: kueue.x-k8s.io/provisioning-request parameters: apiGroup: kueue.x-k8s.io kind: ProvisioningRequestConfig name: dws-config --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ProvisioningRequestConfig metadata: name: dws-config spec: provisioningClassName: queued-provisioning.gke.io podSetUpdates: - key: autoscaling.gke.io/provisioning-request valueFromProvisioningClassDetail: ResizeRequestName managedResources: - nvidia.com/gpu --- apiVersion: kueue.x-k8s.io/v1beta2 kind: ClusterQueue metadata: name: cq-tas spec: namespaceSelector: {} clusterQueueingStrategy: BestEffortFIFO resourceGroups: - flavors: - name: a3-mega-flavor resources: - name: "cpu" nominalQuota: 1000 - name: "memory" nominalQuota: 1000Ti - name: "nvidia.com/gpu" nominalQuota: 1000 - name: a3-mega-dws-flavor resources: - name: "cpu" nominalQuota: 1000 - name: "memory" nominalQuota: 1000Ti - name: "nvidia.com/gpu" nominalQuota: 1000 admissionChecksStrategy: admissionChecks: - name: "dws-prov" onFlavors: [a3-mega-dws-flavor] --- apiVersion: kueue.x-k8s.io/v1beta2 kind: LocalQueue metadata: namespace: default name: lq-tas spec: clusterQueue: cq-tasAplique o manifesto:
kubectl apply -f kueue-config.yaml
Ao executar cargas de trabalho com o TAS ativado, é possível especificar a rigidez das restrições de topologia usando uma das seguintes anotações no manifesto da carga de trabalho:
kueue.x-k8s.io/podset-required-topology: se você usar essa anotação, o Kueue vai bloquear o agendamento até que a carga de trabalho possa ser agendada dentro da restrição de topologia solicitada. Use essa anotação para garantir que os pods sejam colocados juntos para otimizar a performance.kueue.x-k8s.io/podset-preferred-topology: se você usar essa anotação, o Kueue vai tentar agendar pods dentro da restrição de topologia solicitada, mas, se isso não for possível, ele vai admitir a carga de trabalho sem atender às restrições de topologia.
Observação:evite usar o modo obrigatório com o início flexível do DWS. Como o início flexível provisiona nós dinamicamente, os nós resultantes podem não atender aos requisitos topológicos rigorosos, o que pode resultar em cargas de trabalho não programáveis.
Para essas configurações, use podset-preferred-topology.
Para qualquer anotação, especifique um dos seguintes valores como a restrição de topologia:
cloud.google.com/gce-topology-block: agenda pods no mesmo bloco de rede.cloud.google.com/gce-topology-subblock: agenda pods no mesmo rack.cloud.google.com/gce-topology-host: agenda pods no mesmo host físico.
Teste em dois nós de início flexível
Para executar testes de NCCL em um cluster do GKE que usa VMs de início flexível A3 Mega ou A3 High, use o procedimento a seguir. Esse procedimento usa um JobSet para executar um teste de NCCL em dois nós.
Salve o seguinte manifesto como
nccl-tas-jobset.yaml:A3 Mega
apiVersion: v1 kind: ConfigMap metadata: name: nccl-configmap data: allgather.sh: | #!/bin/bash service ssh restart; /scripts/init_ssh.sh ${@}; pushd /scripts; /scripts/gen_hostfiles.sh ${@}; popd; # Set up environment variables for GPUDirect-TCPXO export LD_LIBRARY_PATH=/usr/local/nvidia/lib64 export NCCL_FASTRAK_CTRL_DEV=eth0 export NCCL_FASTRAK_IFNAME=eth1,eth2,eth3,eth4,eth5,eth6,eth7,eth8 export NCCL_SOCKET_IFNAME=eth0 export NCCL_CROSS_NIC=0 export NCCL_ALGO=Ring,Tree export NCCL_PROTO=Simple export NCCL_NET_GDR_LEVEL=PIX # Run the benchmark /scripts/demo-run-nccl-test-tcpxo-via-mpi.sh --- apiVersion: jobset.x-k8s.io/v1alpha2 kind: JobSet metadata: name: nccl-tas-test labels: kueue.x-k8s.io/queue-name: lq-tas spec: ttlSecondsAfterFinished: 1200 suspend: true network: enableDNSHostnames: true replicatedJobs: - name: worker replicas: 2 template: spec: parallelism: 1 completions: 1 template: metadata: annotations: kueue.x-k8s.io/podset-preferred-topology: "cloud.google.com/gce-topology-block" networking.gke.io/default-interface: 'eth0' networking.gke.io/interfaces: | [ {"interfaceName":"eth0","network":"default"}, {"interfaceName":"eth1","network":"vpc0"}, {"interfaceName":"eth2","network":"vpc1"}, {"interfaceName":"eth3","network":"vpc2"}, {"interfaceName":"eth4","network":"vpc3"}, {"interfaceName":"eth5","network":"vpc4"}, {"interfaceName":"eth6","network":"vpc5"}, {"interfaceName":"eth7","network":"vpc6"}, {"interfaceName":"eth8","network":"vpc7"} ] spec: activeDeadlineSeconds: 3600 restartPolicy: Never nodeSelector: cloud.google.com/gke-accelerator: nvidia-h100-mega-80gb tolerations: - key: cloud.google.com/gke-queued effect: NoSchedule value: "true" - key: "nvidia.com/gpu" operator: "Exists" effect: "NoSchedule" setHostnameAsFQDN: true volumes: - name: nvidia hostPath: path: /home/kubernetes/bin/nvidia - name: lib64 hostPath: path: /lib64 - name: proc hostPath: path: /proc - name: shared-memory emptyDir: medium: "Memory" sizeLimit: 250Gi - name: nccl-config configMap: name: nccl-configmap defaultMode: 0755 containers: - name: nccl-test image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpxo/nccl-plugin-gpudirecttcpx-dev:v1.0.15 stdin: true tty: true securityContext: privileged: true env: - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib64 volumeMounts: - name: nvidia mountPath: /usr/local/nvidia - name: shared-memory mountPath: /dev/shm - name: nccl-config mountPath: /configs resources: limits: cpu: "200" memory: "3700Gi" nvidia.com/gpu: 8 requests: cpu: "200" memory: "3700Gi" nvidia.com/gpu: 8 - name: tcpxo-daemon image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpxo/tcpgpudmarxd-dev:v1.0.21 imagePullPolicy: Always command: ["/bin/sh", "-c"] args: - | set -ex chmod 755 /fts/entrypoint_rxdm_container.sh /fts/entrypoint_rxdm_container.sh --num_hops=2 --num_nics=8 --uid= --alsologtostderr securityContext: privileged: true capabilities: add: - NET_ADMIN - NET_BIND_SERVICE volumeMounts: - name: nvidia mountPath: /usr/local/nvidia/lib64 - name: proc mountPath: /proc env: - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib64A3 Alto
apiVersion: v1 kind: ConfigMap metadata: name: nccl-config data: allgather.sh: | #!/bin/bash for script in /configs/*; do name=$(basename $script) cp $script "/scripts/$name" chmod +x "/scripts/$name" done /scripts/init_ssh.sh ${@}; pushd /scripts; /scripts/gen_hostfiles.sh ${@}; popd; /scripts/run-allgather.sh 8 eth1,eth2,eth3,eth4 1M 512M ${#}; --- apiVersion: jobset.x-k8s.io/v1alpha2 kind: JobSet metadata: name: nccl-tas-test labels: kueue.x-k8s.io/queue-name: lq-tas spec: suspend: true network: enableDNSHostnames: true replicatedJobs: - name: worker replicas: 2 template: spec: parallelism: 1 completions: 1 template: metadata: annotations: kueue.x-k8s.io/podset-preferred-topology: "cloud.google.com/gce-topology-block" networking.gke.io/default-interface: 'eth0' networking.gke.io/interfaces: | [ {"interfaceName":"eth0","network":"default"}, {"interfaceName":"eth1","network":"vpc0"}, {"interfaceName":"eth2","network":"vpc1"}, {"interfaceName":"eth3","network":"vpc2"}, {"interfaceName":"eth4","network":"vpc3"} ] spec: terminationGracePeriodSeconds: 0 nodeSelector: cloud.google.com/gke-accelerator: nvidia-h100-80gb tolerations: - key: cloud.google.com/gke-queued effect: NoSchedule value: "true" - key: "nvidia.com/gpu" operator: "Exists" effect: "NoSchedule" setHostnameAsFQDN: true containers: - name: tcpx-daemon image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpx/tcpgpudmarxd-dev:v2.0.11 command: - /tcpgpudmarxd/build/app/tcpgpudmarxd - --gpu_nic_preset - a3vm - --gpu_shmem_type - fd - --uds_path - /run/tcpx - --setup_param - "--verbose 128 2 0 " securityContext: privileged: true capabilities: add: - NET_ADMIN volumeMounts: - name: libraries mountPath: /usr/local/nvidia/lib64 - name: tcpx-socket mountPath: /run/tcpx - name: sys mountPath: /hostsysfs - name: proc-sys mountPath: /hostprocsysfs env: - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib64 - name: nccl-test image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpx/nccl-plugin-gpudirecttcpx-dev:v3.1.8 command: - bash - -c - | /scripts/container_entry.sh daemon; sleep infinity; securityContext: privileged: true volumeMounts: - name: tcpx-socket mountPath: /tmp - name: libraries mountPath: /usr/local/nvidia/lib64 - name: nccl-config mountPath: /configs - name: shared-memory mountPath: /dev/shm resources: limits: cpu: "200" memory: "1800Gi" nvidia.com/gpu: 8 requests: cpu: "200" memory: "1800Gi" nvidia.com/gpu: 8 volumes: - name: libraries hostPath: path: /home/kubernetes/bin/nvidia/lib64 - name: tcpx-socket emptyDir: {} - name: sys hostPath: path: /sys - name: proc-sys hostPath: path: /proc/sys - name: shared-memory emptyDir: medium: Memory sizeLimit: 250Gi - name: nccl-config configMap: name: nccl-config defaultMode: 0777Aplique o manifesto ao cluster:
kubectl apply -f nccl-tas-jobset.yamlVerifique se o JobSet foi admitido e está em execução:
kubectl get jobset nccl-tas-testAguarde até que o JobSet seja retomado e os pods atinjam o status
Running.Acione o teste de NCCL executando o script
allgather.shdo primeiro pod de trabalho:kubectl exec --stdin --tty --container=nccl-test nccl-tas-test-worker-0-0 -- /configs/allgather.sh nccl-tas-test-worker-0-0 nccl-tas-test-worker-1-0A saída de um teste de dois nós é semelhante a esta:
A3 Mega
# out-of-place in-place # size count type redop root time algbw busbw #wrong time algbw busbw #wrong # (B) (elements) (us) (GB/s) (GB/s) (us) (GB/s) (GB/s) 0 0 float none -1 0.24 0.00 0.00 0 0.18 0.00 0.00 0 ... 8589934592 134217728 float none -1 42603 201.63 189.03 0 42670 201.31 188.73 0 # Out of bounds values : 0 OK # Avg bus bandwidth : 45.7587A3 Alto
# out-of-place in-place # size count type redop root time algbw busbw #wrong time algbw busbw #wrong # (B) (elements) (us) (GB/s) (GB/s) (us) (GB/s) (GB/s) 1048576 16384 float none -1 696.8 1.50 1.41 0 729.0 1.44 1.35 0 ... 536870912 8388608 float none -1 7101.7 75.60 70.87 0 7060.9 76.03 71.28 0 # Out of bounds values : 0 OK # Avg bus bandwidth : 29.8293
Implantar uma carga de trabalho de teste de NCCL com TAS
Se você tiver mais de dois nós, recomendamos usar o teste a seguir, que usa a programação consciente da topologia (TAS, na sigla em inglês). Para executar testes de NCCL com TAS em um cluster do GKE que usa VMs de início flexível A3 Mega ou A3 High, use o procedimento a seguir.
Salve o seguinte manifesto como
nccl-jobset-test.yaml. SubstituaNUM_NODESpelo número de nós no pool de nós:A3 Mega
apiVersion: jobset.x-k8s.io/v1alpha2 kind: JobSet metadata: name: nccl-ag labels: kueue.x-k8s.io/queue-name: lq-tas spec: ttlSecondsAfterFinished: 1200 suspend: true network: enableDNSHostnames: true replicatedJobs: - name: worker template: spec: parallelism: NUM_NODES completions: NUM_NODES template: metadata: annotations: kueue.x-k8s.io/podset-preferred-topology: "cloud.google.com/gce-topology-subblock" networking.gke.io/default-interface: 'eth0' networking.gke.io/interfaces: | [ {"interfaceName":"eth0","network":"default"}, {"interfaceName":"eth1","network":"vpc0"}, {"interfaceName":"eth2","network":"vpc1"}, {"interfaceName":"eth3","network":"vpc2"}, {"interfaceName":"eth4","network":"vpc3"}, {"interfaceName":"eth5","network":"vpc4"}, {"interfaceName":"eth6","network":"vpc5"}, {"interfaceName":"eth7","network":"vpc6"}, {"interfaceName":"eth8","network":"vpc7"} ] spec: activeDeadlineSeconds: 3600 restartPolicy: Never nodeSelector: cloud.google.com/gke-accelerator: nvidia-h100-mega-80gb tolerations: - key: "nvidia.com/gpu" operator: "Exists" effect: "NoSchedule" setHostnameAsFQDN: true volumes: - name: proc hostPath: path: /proc - name: nvidia hostPath: path: /home/kubernetes/bin/nvidia - name: lib64 hostPath: path: /lib64 - name: shared-memory emptyDir: medium: "Memory" sizeLimit: 250Gi containers: - name: nccl-test stdin: true tty: true image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpxo/nccl-plugin-tcpxo-diagnostic:v1.0.6 securityContext: privileged: true env: - name: MY_NODE_NAME valueFrom: fieldRef: fieldPath: spec.nodeName - name: OMPI_ALLOW_RUN_AS_ROOT value: "1" - name: OMPI_ALLOW_RUN_AS_ROOT_CONFIRM value: "1" - name: N_NODES value: "NUM_NODES" - name: NCCL_SOCKET_IFNAME value: eth0 - name: NCCL_FASTRAK_CTRL_DEV value: eth0 - name: NCCL_FASTRAK_IFNAME value: eth1,eth2,eth3,eth4,eth5,eth6,eth7,eth8 - name: NCCL_CROSS_NIC value: "0" - name: NCCL_ALGO value: Ring,Tree - name: NCCL_PROTO value: Simple - name: NCCL_NET_GDR_LEVEL value: PIX - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib64 command: - bash - -c - | set -x /scripts/container_entry.sh daemon & export POSTFIX=$(hostname | cut -d . -f 2-) export WORKERS_BASENAME=$(hostname | cut -d . -f 1 | rev | cut -d - -f 2- | rev ) export NODE_RANK=$JOB_COMPLETION_INDEX for i in `seq 0 $(($N_NODES-1))`; do OTHER=<span class="katex"><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8333em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="mord mathnormal" style="margin-right:0.00773em;">OR</span><span class="mord mathnormal" style="margin-right:0.07153em;">K</span><span class="mord mathnormal" style="margin-right:0.00773em;">ER</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3283em;"><span style="top:-2.55em;margin-left:-0.0576em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.05017em;">B</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.10903em;">SEN</span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.05764em;">ME</span></span><span class="mord">−</span></span></span></span>{i}.${POSTFIX} until ssh -p 222 -o StrictHostKeyChecking=no $OTHER hostname; do sleep 10 done echo ${OTHER} port=222 slots=8 | tee -a /tmp/hostfile; done if [[ "${NODE_RANK}" -eq "0" ]]; then export NCCL_TESTS_SPLIT_MASK="0x0"; ENV_VARS=$(echo ${!NCCL*} ${!OMPI*} LD_LIBRARY_PATH PATH | sed 's/ / -x /g') mpirun --hostfile /tmp/hostfile \ -x $ENV_VARS \ -mca plm_rsh_no_tree_spawn 1 \ --mca orte_keep_fqdn_hostnames 1 \ --mca btl self,tcp \ --mca btl_tcp_if_include eth0 \ --bind-to none \ --mca plm_rsh_agent "ssh -q -o LogLevel=ERROR -o StrictHostKeyChecking=no -p 222" \ /third_party/nccl-tests/build/all_gather_perf -b 1K -e 8G -f 2 -g 1 -w 5 --iters 100 -c 1 else while ping -c 1 <span class="katex"><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8333em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="mord mathnormal" style="margin-right:0.00773em;">OR</span><span class="mord mathnormal" style="margin-right:0.07153em;">K</span><span class="mord mathnormal" style="margin-right:0.00773em;">ER</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3283em;"><span style="top:-2.55em;margin-left:-0.0576em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.05017em;">B</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.10903em;">SEN</span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.05764em;">ME</span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0.</span></span></span></span>{POSTFIX}; do sleep 5 done fi exit 0 volumeMounts: - name: nvidia mountPath: /usr/local/nvidia - name: lib64 mountPath: /lib64 - name: shared-memory mountPath: /dev/shm resources: limits: cpu: "200" memory: "3700Gi" nvidia.com/gpu: 8 requests: cpu: "200" memory: "3700Gi" nvidia.com/gpu: 8 - name: tcpxo-daemon image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpxo/tcpxo-daemon:v1.0.1 imagePullPolicy: Always command: - bash - -c - | /usr/bin/tcpxo_daemon securityContext: privileged: true volumeMounts: - name: nvidia mountPath: /usr/local/nvidia - name: proc mountPath: /proc env: - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib64A3 Alto
apiVersion: jobset.x-k8s.io/v1alpha2 kind: JobSet metadata: name: nccl-ag labels: kueue.x-k8s.io/queue-name: lq-tas spec: ttlSecondsAfterFinished: 1200 suspend: true network: enableDNSHostnames: true replicatedJobs: - name: worker template: spec: parallelism: NUM_NODES completions: NUM_NODES template: metadata: annotations: kueue.x-k8s.io/podset-preferred-topology: "cloud.google.com/gce-topology-subblock" networking.gke.io/default-interface: 'eth0' networking.gke.io/interfaces: | [ {"interfaceName":"eth0","network":"default"}, {"interfaceName":"eth1","network":"vpc0"}, {"interfaceName":"eth2","network":"vpc1"}, {"interfaceName":"eth3","network":"vpc2"}, {"interfaceName":"eth4","network":"vpc3"} ] spec: activeDeadlineSeconds: 3600 restartPolicy: Never nodeSelector: cloud.google.com/gke-accelerator: nvidia-h100-80gb tolerations: - key: "nvidia.com/gpu" operator: "Exists" effect: "NoSchedule" setHostnameAsFQDN: true volumes: - name: proc hostPath: path: /proc - name: nvidia hostPath: path: /home/kubernetes/bin/nvidia - name: libraries hostPath: path: /home/kubernetes/bin/nvidia/lib64 - name: tcpx-socket emptyDir: {} - name: shared-memory emptyDir: medium: "Memory" sizeLimit: 250Gi containers: - name: tcpx-daemon image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpx/tcpgpudmarxd-dev:v2.0.11 command: - /tcpgpudmarxd/build/app/tcpgpudmarxd - --gpu_nic_preset - a3vm - --uds_path - /run/tcpx securityContext: privileged: true volumeMounts: - name: tcpx-socket mountPath: /run/tcpx - name: libraries mountPath: /usr/local/nvidia/lib64 - name: nccl-test stdin: true tty: true image: us-docker.pkg.dev/gce-ai-infra/gpudirect-tcpx/nccl-plugin-gpudirecttcpx-dev:v3.1.8 securityContext: privileged: true env: - name: MY_NODE_NAME valueFrom: fieldRef: fieldPath: spec.nodeName - name: OMPI_ALLOW_RUN_AS_ROOT value: "1" - name: OMPI_ALLOW_RUN_AS_ROOT_CONFIRM value: "1" - name: N_NODES value: "NUM_NODES" - name: LD_LIBRARY_PATH value: /usr/local/nvidia/lib64 command: - bash - -c - | /scripts/container_entry.sh daemon & export POSTFIX=$(hostname | cut -d . -f 2-) export WORKERS_BASENAME=$(hostname | cut -d . -f 1 | rev | cut -d - -f 2- | rev ) export NODE_RANK=$JOB_COMPLETION_INDEX for i in `seq 0 $(($N_NODES-1))`; do OTHER=<span class="katex"><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8333em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="mord mathnormal" style="margin-right:0.00773em;">OR</span><span class="mord mathnormal" style="margin-right:0.07153em;">K</span><span class="mord mathnormal" style="margin-right:0.00773em;">ER</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3283em;"><span style="top:-2.55em;margin-left:-0.0576em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.05017em;">B</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.10903em;">SEN</span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.05764em;">ME</span></span><span class="mord">−</span></span></span></span>{i}.${POSTFIX} until ssh -p 222 -o StrictHostKeyChecking=no $OTHER hostname; do sleep 10 done echo ${OTHER} port=222 slots=8 | tee -a /tmp/hostfile; done if [[ "${NODE_RANK}" -eq "0" ]]; then /scripts/run-allgather.sh 8 eth1,eth2,eth3,eth4 1M 512M ${N_NODES} else while ping -c 1 <span class="katex"><span class="katex-html" aria-hidden="true"><span class="base"><span class="strut" style="height:0.8333em;vertical-align:-0.15em;"></span><span class="mord"><span class="mord mathnormal" style="margin-right:0.13889em;">W</span><span class="mord mathnormal" style="margin-right:0.00773em;">OR</span><span class="mord mathnormal" style="margin-right:0.07153em;">K</span><span class="mord mathnormal" style="margin-right:0.00773em;">ER</span><span class="mord"><span class="mord mathnormal" style="margin-right:0.05764em;">S</span><span class="msupsub"><span class="vlist-t vlist-t2"><span class="vlist-r"><span class="vlist" style="height:0.3283em;"><span style="top:-2.55em;margin-left:-0.0576em;margin-right:0.05em;"><span class="pstrut" style="height:2.7em;"></span><span class="sizing reset-size6 size3 mtight"><span class="mord mathnormal mtight" style="margin-right:0.05017em;">B</span></span></span></span><span class="vlist-s"></span></span><span class="vlist-r"><span class="vlist" style="height:0.15em;"><span></span></span></span></span></span></span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.10903em;">SEN</span><span class="mord mathnormal">A</span><span class="mord mathnormal" style="margin-right:0.05764em;">ME</span></span><span class="mspace" style="margin-right:0.2222em;"></span><span class="mbin">−</span><span class="mspace" style="margin-right:0.2222em;"></span></span><span class="base"><span class="strut" style="height:0.6444em;"></span><span class="mord">0.</span></span></span></span>{POSTFIX}; do sleep 5 done fi exit 0 volumeMounts: - name: nvidia mountPath: /usr/local/nvidia - name: tcpx-socket mountPath: /tmp - name: libraries mountPath: /usr/local/nvidia/lib64 - name: shared-memory mountPath: /dev/shm resources: limits: cpu: "200" memory: "1800Gi" nvidia.com/gpu: 8 requests: cpu: "200" memory: "1800Gi" nvidia.com/gpu: 8Aplique o manifesto:
kubectl apply -f nccl-jobset-test.yamlVerifique se a carga de trabalho foi admitida e atingiu o estado
Completed.Busque registros do pod correspondente a
nccl-ag-worker-0-0-.*para conferir os resultados:kubectl logs $(kubectl get pods -o go-template='{{range .items}}{{.metadata.name}}{{"\n"}}{{end}}' | grep nccl-ag-worker-0-0)
A seguir
- Coletar e entender registros de NCCL para solução de problemas para entender as saídas de teste e resolver problemas.
- Saiba como resolver problemas de performance lenta.