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Add some simple tests for nvidia GPU(s)
Signed-off-by: Davanum Srinivas <davanum@gmail.com>
This commit is contained in:
Davanum Srinivas
parent
aae6745a67
commit
f4cd6ec052
206
test/e2e/node/gpu.go
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206
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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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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"k8s.io/kubernetes/test/e2e/feature"
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"k8s.io/kubernetes/test/e2e/framework"
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e2egpu "k8s.io/kubernetes/test/e2e/framework/gpu"
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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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e2eskipper "k8s.io/kubernetes/test/e2e/framework/skipper"
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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")
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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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checkEnvironmentAndSkipIfNeeded(ctx, 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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checkEnvironmentAndSkipIfNeeded(ctx, 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 checkEnvironmentAndSkipIfNeeded(ctx context.Context, clientSet clientset.Interface) {
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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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