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Merge pull request #127462 from dims/automated-cherry-pick-of-#127423-#127456-upstream-release-1.31
Automated cherry pick of #127423: Add some simple tests for nvidia GPU(s) #127456: Install Nvidia Daemonset in test harness for GCE
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1740b2ae7f
306
test/e2e/node/gpu.go
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306
test/e2e/node/gpu.go
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/*
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Copyright 2024 The Kubernetes Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package node
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import (
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"context"
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"os"
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"time"
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appsv1 "k8s.io/api/apps/v1"
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v1 "k8s.io/api/core/v1"
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"k8s.io/apimachinery/pkg/api/resource"
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metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
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"k8s.io/apimachinery/pkg/util/uuid"
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clientset "k8s.io/client-go/kubernetes"
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extensionsinternal "k8s.io/kubernetes/pkg/apis/extensions"
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"k8s.io/kubernetes/test/e2e/feature"
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"k8s.io/kubernetes/test/e2e/framework"
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e2edebug "k8s.io/kubernetes/test/e2e/framework/debug"
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e2egpu "k8s.io/kubernetes/test/e2e/framework/gpu"
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e2emanifest "k8s.io/kubernetes/test/e2e/framework/manifest"
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e2enode "k8s.io/kubernetes/test/e2e/framework/node"
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e2epod "k8s.io/kubernetes/test/e2e/framework/pod"
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e2eresource "k8s.io/kubernetes/test/e2e/framework/resource"
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e2eskipper "k8s.io/kubernetes/test/e2e/framework/skipper"
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e2etestfiles "k8s.io/kubernetes/test/e2e/framework/testfiles"
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admissionapi "k8s.io/pod-security-admission/api"
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"github.com/onsi/ginkgo/v2"
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"github.com/onsi/gomega"
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)
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var _ = SIGDescribe(feature.GPUDevicePlugin, "Sanity test for Nvidia Device", func() {
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f := framework.NewDefaultFramework("nvidia-gpu")
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f.NamespacePodSecurityLevel = admissionapi.LevelPrivileged
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var podClient *e2epod.PodClient
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ginkgo.BeforeEach(func() {
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e2eskipper.SkipUnlessProviderIs("aws", "gce")
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podClient = e2epod.NewPodClient(f)
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})
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f.It("should run nvidia-smi cli", func(ctx context.Context) {
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SetupEnvironmentAndSkipIfNeeded(ctx, f, f.ClientSet)
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pod := testNvidiaCLIPod()
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pod.Spec.Containers[0].Command = []string{"nvidia-smi"}
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ginkgo.By("Creating a pod that runs nvidia-smi")
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createAndValidatePod(ctx, f, podClient, pod)
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ginkgo.By("Getting logs from the pod")
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log, err := e2epod.GetPodLogs(ctx, f.ClientSet, f.Namespace.Name, pod.Name, pod.Spec.Containers[0].Name)
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framework.ExpectNoError(err)
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ginkgo.By("Checking output from nvidia-smi")
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gomega.Expect(log).To(gomega.ContainSubstring("NVIDIA-SMI"))
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gomega.Expect(log).To(gomega.ContainSubstring("Driver Version:"))
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gomega.Expect(log).To(gomega.ContainSubstring("CUDA Version:"))
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})
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f.It("should run gpu based matrix multiplication", func(ctx context.Context) {
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SetupEnvironmentAndSkipIfNeeded(ctx, f, f.ClientSet)
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pod := testMatrixMultiplicationPod()
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ginkgo.By("Creating a pod that runs matrix multiplication")
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createAndValidatePod(ctx, f, podClient, pod)
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ginkgo.By("Getting logs from the pod")
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log, err := e2epod.GetPodLogs(ctx, f.ClientSet, f.Namespace.Name, pod.Name, pod.Spec.Containers[0].Name)
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framework.ExpectNoError(err)
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ginkgo.By("Checking output from nvidia-smi")
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gomega.Expect(log).To(gomega.ContainSubstring("TensorFlow version"))
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gomega.Expect(log).To(gomega.ContainSubstring("Matrix multiplication result:"))
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gomega.Expect(log).To(gomega.ContainSubstring("Time taken for 5000x5000 matrix multiplication"))
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})
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})
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func createAndValidatePod(ctx context.Context, f *framework.Framework, podClient *e2epod.PodClient, pod *v1.Pod) {
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pod = podClient.Create(ctx, pod)
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ginkgo.By("Watching for error events or started pod")
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ev, err := podClient.WaitForErrorEventOrSuccess(ctx, pod)
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framework.ExpectNoError(err)
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gomega.Expect(ev).To(gomega.BeNil())
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ginkgo.By("Waiting for pod completion")
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err = e2epod.WaitForPodNoLongerRunningInNamespace(ctx, f.ClientSet, pod.Name, f.Namespace.Name)
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framework.ExpectNoError(err)
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pod, err = podClient.Get(ctx, pod.Name, metav1.GetOptions{})
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framework.ExpectNoError(err)
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ginkgo.By("Checking that the pod succeeded")
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gomega.Expect(pod.Status.Phase).To(gomega.Equal(v1.PodSucceeded))
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}
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func testNvidiaCLIPod() *v1.Pod {
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podName := "gpu-cli-" + string(uuid.NewUUID())
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pod := v1.Pod{
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ObjectMeta: metav1.ObjectMeta{
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Name: podName,
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Annotations: map[string]string{},
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},
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Spec: v1.PodSpec{
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Containers: []v1.Container{
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{
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Name: "nvidia-smi",
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Image: "nvidia/cuda:12.3.2-runtime-ubuntu22.04",
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Resources: v1.ResourceRequirements{
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Limits: v1.ResourceList{
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"nvidia.com/gpu": resource.MustParse("1"),
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},
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},
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},
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},
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RestartPolicy: v1.RestartPolicyNever,
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},
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}
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return &pod
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}
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func testMatrixMultiplicationPod() *v1.Pod {
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podName := "gpu-matmul-" + string(uuid.NewUUID())
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pod := v1.Pod{
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ObjectMeta: metav1.ObjectMeta{
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Name: podName,
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Annotations: map[string]string{},
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},
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Spec: v1.PodSpec{
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Containers: []v1.Container{
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{
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Name: "gpu-matmul",
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Image: "tensorflow/tensorflow:latest-gpu",
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Command: []string{
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"python",
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"-c",
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`
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import tensorflow as tf
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import time
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print("TensorFlow version:", tf.__version__)
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print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
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# Simple matrix multiplication test
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with tf.device('/GPU:0'):
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a = tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
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b = tf.constant([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
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c = tf.matmul(a, b)
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print("Matrix multiplication result:", c.numpy())
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# Performance test
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n = 5000
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start_time = time.time()
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with tf.device('/GPU:0'):
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matrix1 = tf.random.normal((n, n))
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matrix2 = tf.random.normal((n, n))
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result = tf.matmul(matrix1, matrix2)
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end_time = time.time()
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print(f"Time taken for {n}x{n} matrix multiplication: {end_time - start_time:.2f} seconds")
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`,
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},
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Resources: v1.ResourceRequirements{
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Limits: v1.ResourceList{
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"nvidia.com/gpu": resource.MustParse("1"),
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},
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},
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},
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},
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RestartPolicy: v1.RestartPolicyNever,
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},
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}
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return &pod
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}
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func SetupEnvironmentAndSkipIfNeeded(ctx context.Context, f *framework.Framework, clientSet clientset.Interface) {
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if framework.ProviderIs("gce") {
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rsgather := SetupNVIDIAGPUNode(ctx, f)
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defer func() {
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framework.Logf("Stopping ResourceUsageGather")
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constraints := make(map[string]e2edebug.ResourceConstraint)
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// For now, just gets summary. Can pass valid constraints in the future.
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summary, err := rsgather.StopAndSummarize([]int{50, 90, 100}, constraints)
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f.TestSummaries = append(f.TestSummaries, summary)
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framework.ExpectNoError(err, "getting resource usage summary")
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}()
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}
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nodes, err := e2enode.GetReadySchedulableNodes(ctx, clientSet)
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framework.ExpectNoError(err)
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capacity := 0
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allocatable := 0
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for _, node := range nodes.Items {
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val, ok := node.Status.Capacity[e2egpu.NVIDIAGPUResourceName]
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if !ok {
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continue
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}
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capacity += int(val.Value())
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val, ok = node.Status.Allocatable[e2egpu.NVIDIAGPUResourceName]
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if !ok {
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continue
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}
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allocatable += int(val.Value())
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}
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if capacity == 0 {
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e2eskipper.Skipf("%d ready nodes do not have any Nvidia GPU(s). Skipping...", len(nodes.Items))
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}
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if allocatable == 0 {
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e2eskipper.Skipf("%d ready nodes do not have any allocatable Nvidia GPU(s). Skipping...", len(nodes.Items))
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}
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}
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func areGPUsAvailableOnAllSchedulableNodes(ctx context.Context, clientSet clientset.Interface) bool {
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framework.Logf("Getting list of Nodes from API server")
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nodeList, err := clientSet.CoreV1().Nodes().List(ctx, metav1.ListOptions{})
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framework.ExpectNoError(err, "getting node list")
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for _, node := range nodeList.Items {
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if node.Spec.Unschedulable {
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continue
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}
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framework.Logf("gpuResourceName %s", e2egpu.NVIDIAGPUResourceName)
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if val, ok := node.Status.Capacity[e2egpu.NVIDIAGPUResourceName]; !ok || val.Value() == 0 {
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framework.Logf("Nvidia GPUs not available on Node: %q", node.Name)
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return false
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}
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}
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framework.Logf("Nvidia GPUs exist on all schedulable nodes")
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return true
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}
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func logOSImages(ctx context.Context, f *framework.Framework) {
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nodeList, err := f.ClientSet.CoreV1().Nodes().List(ctx, metav1.ListOptions{})
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framework.ExpectNoError(err, "getting node list")
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for _, node := range nodeList.Items {
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framework.Logf("Nodename: %v, OS Image: %v", node.Name, node.Status.NodeInfo.OSImage)
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}
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}
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const (
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// Nvidia driver installation can take upwards of 5 minutes.
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driverInstallTimeout = 10 * time.Minute
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)
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// SetupNVIDIAGPUNode install Nvidia Drivers and wait for Nvidia GPUs to be available on nodes
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func SetupNVIDIAGPUNode(ctx context.Context, f *framework.Framework) *e2edebug.ContainerResourceGatherer {
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logOSImages(ctx, f)
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var err error
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var ds *appsv1.DaemonSet
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dsYamlURLFromEnv := os.Getenv("NVIDIA_DRIVER_INSTALLER_DAEMONSET")
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if dsYamlURLFromEnv != "" {
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// Using DaemonSet from remote URL
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framework.Logf("Using remote nvidia-driver-installer daemonset manifest from %v", dsYamlURLFromEnv)
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ds, err = e2emanifest.DaemonSetFromURL(ctx, dsYamlURLFromEnv)
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framework.ExpectNoError(err, "failed get remote")
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} else {
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// Using default local DaemonSet
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framework.Logf("Using default local nvidia-driver-installer daemonset manifest.")
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data, err := e2etestfiles.Read("test/e2e/testing-manifests/scheduling/nvidia-driver-installer.yaml")
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framework.ExpectNoError(err, "failed to read local manifest for nvidia-driver-installer daemonset")
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ds, err = e2emanifest.DaemonSetFromData(data)
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framework.ExpectNoError(err, "failed to parse local manifest for nvidia-driver-installer daemonset")
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}
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ds.Namespace = f.Namespace.Name
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_, err = f.ClientSet.AppsV1().DaemonSets(f.Namespace.Name).Create(ctx, ds, metav1.CreateOptions{})
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framework.ExpectNoError(err, "failed to create nvidia-driver-installer daemonset")
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framework.Logf("Successfully created daemonset to install Nvidia drivers.")
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pods, err := e2eresource.WaitForControlledPods(ctx, f.ClientSet, ds.Namespace, ds.Name, extensionsinternal.Kind("DaemonSet"))
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framework.ExpectNoError(err, "failed to get pods controlled by the nvidia-driver-installer daemonset")
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devicepluginPods, err := e2eresource.WaitForControlledPods(ctx, f.ClientSet, "kube-system", "nvidia-gpu-device-plugin", extensionsinternal.Kind("DaemonSet"))
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if err == nil {
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framework.Logf("Adding deviceplugin addon pod.")
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pods.Items = append(pods.Items, devicepluginPods.Items...)
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}
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framework.Logf("Starting ResourceUsageGather for the created DaemonSet pods.")
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rsgather, err := e2edebug.NewResourceUsageGatherer(ctx, f.ClientSet,
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e2edebug.ResourceGathererOptions{InKubemark: false, Nodes: e2edebug.AllNodes, ResourceDataGatheringPeriod: 2 * time.Second, ProbeDuration: 2 * time.Second, PrintVerboseLogs: true}, pods)
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framework.ExpectNoError(err, "creating ResourceUsageGather for the daemonset pods")
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go rsgather.StartGatheringData(ctx)
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// Wait for Nvidia GPUs to be available on nodes
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framework.Logf("Waiting for drivers to be installed and GPUs to be available in Node Capacity...")
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gomega.Eventually(ctx, func(ctx context.Context) bool {
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return areGPUsAvailableOnAllSchedulableNodes(ctx, f.ClientSet)
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}, driverInstallTimeout, time.Second).Should(gomega.BeTrueBecause("expected GPU resources to be available within the timout"))
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return rsgather
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}
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