Replace godep with dep

vendor/k8s.io/kubernetes/pkg/kubelet/gpu/nvidia/BUILD

@@ -0,0 +1,51 @@
+package(default_visibility = ["//visibility:public"])
+
+load(
+    "@io_bazel_rules_go//go:def.bzl",
+    "go_library",
+    "go_test",
+)
+
+go_library(
+    name = "go_default_library",
+    srcs = [
+        "helpers.go",
+        "nvidia_gpu_manager.go",
+    ],
+    deps = [
+        "//pkg/kubelet/dockershim/libdocker:go_default_library",
+        "//pkg/kubelet/gpu:go_default_library",
+        "//vendor/github.com/golang/glog:go_default_library",
+        "//vendor/k8s.io/api/core/v1:go_default_library",
+        "//vendor/k8s.io/apimachinery/pkg/api/resource:go_default_library",
+        "//vendor/k8s.io/apimachinery/pkg/util/sets:go_default_library",
+    ],
+)
+
+filegroup(
+    name = "package-srcs",
+    srcs = glob(["**"]),
+    tags = ["automanaged"],
+    visibility = ["//visibility:private"],
+)
+
+filegroup(
+    name = "all-srcs",
+    srcs = [":package-srcs"],
+    tags = ["automanaged"],
+)
+
+go_test(
+    name = "go_default_test",
+    srcs = ["nvidia_gpu_manager_test.go"],
+    library = ":go_default_library",
+    deps = [
+        "//pkg/kubelet/dockershim/libdocker:go_default_library",
+        "//vendor/github.com/stretchr/testify/assert:go_default_library",
+        "//vendor/k8s.io/api/core/v1:go_default_library",
+        "//vendor/k8s.io/apimachinery/pkg/api/resource:go_default_library",
+        "//vendor/k8s.io/apimachinery/pkg/apis/meta/v1:go_default_library",
+        "//vendor/k8s.io/apimachinery/pkg/util/sets:go_default_library",
+        "//vendor/k8s.io/apimachinery/pkg/util/uuid:go_default_library",
+    ],
+)

vendor/k8s.io/kubernetes/pkg/kubelet/gpu/nvidia/helpers.go

@@ -0,0 +1,77 @@
+/*
+Copyright 2017 The Kubernetes Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+package nvidia
+
+import "k8s.io/apimachinery/pkg/util/sets"
+
+type containerToGPU map[string]sets.String
+
+// podGPUs represents a list of pod to GPU mappings.
+type podGPUs struct {
+	podGPUMapping map[string]containerToGPU
+}
+
+func newPodGPUs() *podGPUs {
+	return &podGPUs{
+		podGPUMapping: make(map[string]containerToGPU),
+	}
+}
+func (pgpu *podGPUs) pods() sets.String {
+	ret := sets.NewString()
+	for k := range pgpu.podGPUMapping {
+		ret.Insert(k)
+	}
+	return ret
+}
+
+func (pgpu *podGPUs) insert(podUID, contName string, device string) {
+	if _, exists := pgpu.podGPUMapping[podUID]; !exists {
+		pgpu.podGPUMapping[podUID] = make(containerToGPU)
+	}
+	if _, exists := pgpu.podGPUMapping[podUID][contName]; !exists {
+		pgpu.podGPUMapping[podUID][contName] = sets.NewString()
+	}
+	pgpu.podGPUMapping[podUID][contName].Insert(device)
+}
+
+func (pgpu *podGPUs) getGPUs(podUID, contName string) sets.String {
+	containers, exists := pgpu.podGPUMapping[podUID]
+	if !exists {
+		return nil
+	}
+	devices, exists := containers[contName]
+	if !exists {
+		return nil
+	}
+	return devices
+}
+
+func (pgpu *podGPUs) delete(pods []string) {
+	for _, uid := range pods {
+		delete(pgpu.podGPUMapping, uid)
+	}
+}
+
+func (pgpu *podGPUs) devices() sets.String {
+	ret := sets.NewString()
+	for _, containerToGPU := range pgpu.podGPUMapping {
+		for _, deviceSet := range containerToGPU {
+			ret = ret.Union(deviceSet)
+		}
+	}
+	return ret
+}

vendor/k8s.io/kubernetes/pkg/kubelet/gpu/nvidia/nvidia_gpu_manager.go

@@ -0,0 +1,275 @@
+/*
+Copyright 2017 The Kubernetes Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+package nvidia
+
+import (
+	"fmt"
+	"io/ioutil"
+	"os"
+	"path"
+	"regexp"
+	"strings"
+	"sync"
+
+	"github.com/golang/glog"
+
+	"k8s.io/api/core/v1"
+	"k8s.io/apimachinery/pkg/api/resource"
+	"k8s.io/apimachinery/pkg/util/sets"
+	"k8s.io/kubernetes/pkg/kubelet/dockershim/libdocker"
+	"k8s.io/kubernetes/pkg/kubelet/gpu"
+)
+
+// TODO: rework to use Nvidia's NVML, which is more complex, but also provides more fine-grained information and stats.
+const (
+	// All NVIDIA GPUs cards should be mounted with nvidiactl and nvidia-uvm
+	// If the driver installed correctly, the 2 devices will be there.
+	nvidiaCtlDevice string = "/dev/nvidiactl"
+	nvidiaUVMDevice string = "/dev/nvidia-uvm"
+	// Optional device.
+	nvidiaUVMToolsDevice string = "/dev/nvidia-uvm-tools"
+	devDirectory                = "/dev"
+	nvidiaDeviceRE              = `^nvidia[0-9]*$`
+	nvidiaFullpathRE            = `^/dev/nvidia[0-9]*$`
+)
+
+type activePodsLister interface {
+	// Returns a list of active pods on the node.
+	GetActivePods() []*v1.Pod
+}
+
+// nvidiaGPUManager manages nvidia gpu devices.
+type nvidiaGPUManager struct {
+	sync.Mutex
+	// All gpus available on the Node
+	allGPUs        sets.String
+	allocated      *podGPUs
+	defaultDevices []string
+	// The interface which could get GPU mapping from all the containers.
+	// TODO: Should make this independent of Docker in the future.
+	dockerClient     libdocker.Interface
+	activePodsLister activePodsLister
+}
+
+// NewNvidiaGPUManager returns a GPUManager that manages local Nvidia GPUs.
+// TODO: Migrate to use pod level cgroups and make it generic to all runtimes.
+func NewNvidiaGPUManager(activePodsLister activePodsLister, dockerClient libdocker.Interface) (gpu.GPUManager, error) {
+	if dockerClient == nil {
+		return nil, fmt.Errorf("invalid docker client specified")
+	}
+	return &nvidiaGPUManager{
+		allGPUs:          sets.NewString(),
+		dockerClient:     dockerClient,
+		activePodsLister: activePodsLister,
+	}, nil
+}
+
+// Initialize the GPU devices, so far only needed to discover the GPU paths.
+func (ngm *nvidiaGPUManager) Start() error {
+	if ngm.dockerClient == nil {
+		return fmt.Errorf("Invalid docker client specified in GPU Manager")
+	}
+	ngm.Lock()
+	defer ngm.Unlock()
+
+	if _, err := os.Stat(nvidiaCtlDevice); err != nil {
+		return err
+	}
+
+	if _, err := os.Stat(nvidiaUVMDevice); err != nil {
+		return err
+	}
+	ngm.defaultDevices = []string{nvidiaCtlDevice, nvidiaUVMDevice}
+	_, err := os.Stat(nvidiaUVMToolsDevice)
+	if !os.IsNotExist(err) {
+		ngm.defaultDevices = append(ngm.defaultDevices, nvidiaUVMToolsDevice)
+	}
+
+	if err := ngm.discoverGPUs(); err != nil {
+		return err
+	}
+
+	// We ignore errors when identifying allocated GPUs because it is possible that the runtime interfaces may be not be logically up.
+	return nil
+}
+
+// Get how many GPU cards we have.
+func (ngm *nvidiaGPUManager) Capacity() v1.ResourceList {
+	gpus := resource.NewQuantity(int64(len(ngm.allGPUs)), resource.DecimalSI)
+	return v1.ResourceList{
+		v1.ResourceNvidiaGPU: *gpus,
+	}
+}
+
+// AllocateGPUs returns `num` GPUs if available, error otherwise.
+// Allocation is made thread safe using the following logic.
+// A list of all GPUs allocated is maintained along with their respective Pod UIDs.
+// It is expected that the list of active pods will not return any false positives.
+// As part of initialization or allocation, the list of GPUs in use will be computed once.
+// Whenever an allocation happens, the list of GPUs allocated is updated based on the list of currently active pods.
+// GPUs allocated to terminated pods are freed up lazily as part of allocation.
+// GPUs are allocated based on the internal list of allocatedGPUs.
+// It is not safe to generate a list of GPUs in use by inspecting active containers because of the delay between GPU allocation and container creation.
+// A GPU allocated to a container might be re-allocated to a subsequent container because the original container wasn't started quick enough.
+// The current algorithm scans containers only once and then uses a list of active pods to track GPU usage.
+// This is a sub-optimal solution and a better alternative would be that of using pod level cgroups instead.
+// GPUs allocated to containers should be reflected in pod level device cgroups before completing allocations.
+// The pod level cgroups will then serve as a checkpoint of GPUs in use.
+func (ngm *nvidiaGPUManager) AllocateGPU(pod *v1.Pod, container *v1.Container) ([]string, error) {
+	gpusNeeded := container.Resources.Limits.NvidiaGPU().Value()
+	if gpusNeeded == 0 {
+		return []string{}, nil
+	}
+	ngm.Lock()
+	defer ngm.Unlock()
+	if ngm.allocated == nil {
+		// Initialization is not complete. Try now. Failures can no longer be tolerated.
+		ngm.allocated = ngm.gpusInUse()
+	} else {
+		// update internal list of GPUs in use prior to allocating new GPUs.
+		ngm.updateAllocatedGPUs()
+	}
+	// Check if GPUs have already been allocated. If so return them right away.
+	// This can happen if a container restarts for example.
+	if devices := ngm.allocated.getGPUs(string(pod.UID), container.Name); devices != nil {
+		glog.V(2).Infof("Found pre-allocated GPUs for container %q in Pod %q: %v", container.Name, pod.UID, devices.List())
+		return append(devices.List(), ngm.defaultDevices...), nil
+	}
+	// Get GPU devices in use.
+	devicesInUse := ngm.allocated.devices()
+	glog.V(5).Infof("gpus in use: %v", devicesInUse.List())
+	// Get a list of available GPUs.
+	available := ngm.allGPUs.Difference(devicesInUse)
+	glog.V(5).Infof("gpus available: %v", available.List())
+	if int64(available.Len()) < gpusNeeded {
+		return nil, fmt.Errorf("requested number of GPUs unavailable. Requested: %d, Available: %d", gpusNeeded, available.Len())
+	}
+	ret := available.UnsortedList()[:gpusNeeded]
+	for _, device := range ret {
+		// Update internal allocated GPU cache.
+		ngm.allocated.insert(string(pod.UID), container.Name, device)
+	}
+	// Add standard devices files that needs to be exposed.
+	ret = append(ret, ngm.defaultDevices...)
+
+	return ret, nil
+}
+
+// updateAllocatedGPUs updates the list of GPUs in use.
+// It gets a list of active pods and then frees any GPUs that are bound to terminated pods.
+// Returns error on failure.
+func (ngm *nvidiaGPUManager) updateAllocatedGPUs() {
+	activePods := ngm.activePodsLister.GetActivePods()
+	activePodUids := sets.NewString()
+	for _, pod := range activePods {
+		activePodUids.Insert(string(pod.UID))
+	}
+	allocatedPodUids := ngm.allocated.pods()
+	podsToBeRemoved := allocatedPodUids.Difference(activePodUids)
+	glog.V(5).Infof("pods to be removed: %v", podsToBeRemoved.List())
+	ngm.allocated.delete(podsToBeRemoved.List())
+}
+
+// discoverGPUs identifies allGPUs NVIDIA GPU devices available on the local node by walking `/dev` directory.
+// TODO: Without NVML support we only can check whether there has GPU devices, but
+// could not give a health check or get more information like GPU cores, memory, or
+// family name. Need to support NVML in the future. But we do not need NVML until
+// we want more features, features like schedule containers according to GPU family
+// name.
+func (ngm *nvidiaGPUManager) discoverGPUs() error {
+	reg := regexp.MustCompile(nvidiaDeviceRE)
+	files, err := ioutil.ReadDir(devDirectory)
+	if err != nil {
+		return err
+	}
+	for _, f := range files {
+		if f.IsDir() {
+			continue
+		}
+		if reg.MatchString(f.Name()) {
+			glog.V(2).Infof("Found Nvidia GPU %q", f.Name())
+			ngm.allGPUs.Insert(path.Join(devDirectory, f.Name()))
+		}
+	}
+
+	return nil
+}
+
+// gpusInUse returns a list of GPUs in use along with the respective pods that are using it.
+func (ngm *nvidiaGPUManager) gpusInUse() *podGPUs {
+	pods := ngm.activePodsLister.GetActivePods()
+	type containerIdentifier struct {
+		id   string
+		name string
+	}
+	type podContainers struct {
+		uid        string
+		containers []containerIdentifier
+	}
+	// List of containers to inspect.
+	podContainersToInspect := []podContainers{}
+	for _, pod := range pods {
+		containers := sets.NewString()
+		for _, container := range pod.Spec.Containers {
+			// GPUs are expected to be specified only in limits.
+			if !container.Resources.Limits.NvidiaGPU().IsZero() {
+				containers.Insert(container.Name)
+			}
+		}
+		// If no GPUs were requested skip this pod.
+		if containers.Len() == 0 {
+			continue
+		}
+		// TODO: If kubelet restarts right after allocating a GPU to a pod, the container might not have started yet and so container status might not be available yet.
+		// Use an internal checkpoint instead or try using the CRI if its checkpoint is reliable.
+		var containersToInspect []containerIdentifier
+		for _, container := range pod.Status.ContainerStatuses {
+			if containers.Has(container.Name) {
+				containersToInspect = append(containersToInspect, containerIdentifier{strings.Replace(container.ContainerID, "docker://", "", 1), container.Name})
+			}
+		}
+		// add the pod and its containers that need to be inspected.
+		podContainersToInspect = append(podContainersToInspect, podContainers{string(pod.UID), containersToInspect})
+	}
+	ret := newPodGPUs()
+	for _, podContainer := range podContainersToInspect {
+		for _, containerIdentifier := range podContainer.containers {
+			containerJSON, err := ngm.dockerClient.InspectContainer(containerIdentifier.id)
+			if err != nil {
+				glog.V(3).Infof("Failed to inspect container %q in pod %q while attempting to reconcile nvidia gpus in use", containerIdentifier.id, podContainer.uid)
+				continue
+			}
+
+			devices := containerJSON.HostConfig.Devices
+			if devices == nil {
+				continue
+			}
+
+			for _, device := range devices {
+				if isValidPath(device.PathOnHost) {
+					glog.V(4).Infof("Nvidia GPU %q is in use by Docker Container: %q", device.PathOnHost, containerJSON.ID)
+					ret.insert(podContainer.uid, containerIdentifier.name, device.PathOnHost)
+				}
+			}
+		}
+	}
+	return ret
+}
+
+func isValidPath(path string) bool {
+	return regexp.MustCompile(nvidiaFullpathRE).MatchString(path)
+}

vendor/k8s.io/kubernetes/pkg/kubelet/gpu/nvidia/nvidia_gpu_manager_test.go

@@ -0,0 +1,211 @@
+/*
+Copyright 2017 The Kubernetes Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+*/
+
+package nvidia
+
+import (
+	"os"
+	"reflect"
+	"testing"
+
+	"github.com/stretchr/testify/assert"
+
+	"k8s.io/api/core/v1"
+	"k8s.io/apimachinery/pkg/api/resource"
+	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
+	"k8s.io/apimachinery/pkg/util/sets"
+	"k8s.io/apimachinery/pkg/util/uuid"
+	"k8s.io/kubernetes/pkg/kubelet/dockershim/libdocker"
+)
+
+type testActivePodsLister struct {
+	activePods []*v1.Pod
+}
+
+func (tapl *testActivePodsLister) GetActivePods() []*v1.Pod {
+	return tapl.activePods
+}
+
+func makeTestPod(numContainers, gpusPerContainer int) *v1.Pod {
+	quantity := resource.NewQuantity(int64(gpusPerContainer), resource.DecimalSI)
+	resources := v1.ResourceRequirements{
+		Limits: v1.ResourceList{
+			v1.ResourceNvidiaGPU: *quantity,
+		},
+	}
+	pod := &v1.Pod{
+		ObjectMeta: metav1.ObjectMeta{
+			UID: uuid.NewUUID(),
+		},
+		Spec: v1.PodSpec{
+			Containers: []v1.Container{},
+		},
+	}
+	for ; numContainers > 0; numContainers-- {
+		pod.Spec.Containers = append(pod.Spec.Containers, v1.Container{
+			Name:      string(uuid.NewUUID()),
+			Resources: resources,
+		})
+	}
+	return pod
+}
+
+func TestNewNvidiaGPUManager(t *testing.T) {
+	podLister := &testActivePodsLister{}
+
+	// Expects nil GPUManager and an error with nil dockerClient.
+	testGpuManager1, err := NewNvidiaGPUManager(podLister, nil)
+	as := assert.New(t)
+	as.Nil(testGpuManager1)
+	as.NotNil(err)
+
+	// Expects a GPUManager to be created with non-nil dockerClient.
+	fakeDocker := libdocker.NewFakeDockerClient()
+	testGpuManager2, err := NewNvidiaGPUManager(podLister, fakeDocker)
+	as.NotNil(testGpuManager2)
+	as.Nil(err)
+
+	// Expects zero capacity without any GPUs.
+	gpuCapacity := testGpuManager2.Capacity()
+	as.Equal(len(gpuCapacity), 1)
+	rgpu := gpuCapacity[v1.ResourceNvidiaGPU]
+	as.Equal(rgpu.Value(), int64(0))
+
+	err2 := testGpuManager2.Start()
+	if !os.IsNotExist(err2) {
+		gpus := reflect.ValueOf(testGpuManager2).Elem().FieldByName("allGPUs").Len()
+		as.NotZero(gpus)
+	}
+}
+
+func TestMultiContainerPodGPUAllocation(t *testing.T) {
+	podLister := &testActivePodsLister{}
+
+	testGpuManager := &nvidiaGPUManager{
+		activePodsLister: podLister,
+		allGPUs:          sets.NewString("/dev/nvidia0", "/dev/nvidia1"),
+		allocated:        newPodGPUs(),
+	}
+
+	// Expect that no devices are in use.
+	gpusInUse := testGpuManager.gpusInUse()
+	as := assert.New(t)
+	as.Equal(len(gpusInUse.devices()), 0)
+
+	// Allocated GPUs for a pod with two containers.
+	pod := makeTestPod(2, 1)
+	// Allocate for the first container.
+	devices1, err := testGpuManager.AllocateGPU(pod, &pod.Spec.Containers[0])
+	as.Nil(err)
+	as.Equal(len(devices1), 1)
+
+	podLister.activePods = append(podLister.activePods, pod)
+	// Allocate for the second container.
+	devices2, err := testGpuManager.AllocateGPU(pod, &pod.Spec.Containers[1])
+	as.Nil(err)
+	as.Equal(len(devices2), 1)
+
+	as.NotEqual(devices1, devices2, "expected containers to get different devices")
+
+	// further allocations should fail.
+	newPod := makeTestPod(2, 1)
+	devices1, err = testGpuManager.AllocateGPU(newPod, &newPod.Spec.Containers[0])
+	as.NotNil(err, "expected gpu allocation to fail. got: %v", devices1)
+
+	// Now terminate the original pod and observe that GPU allocation for new pod succeeds.
+	podLister.activePods = podLister.activePods[:0]
+
+	devices1, err = testGpuManager.AllocateGPU(newPod, &newPod.Spec.Containers[0])
+	as.Nil(err)
+	as.Equal(len(devices1), 1)
+
+	podLister.activePods = append(podLister.activePods, newPod)
+
+	devices2, err = testGpuManager.AllocateGPU(newPod, &newPod.Spec.Containers[1])
+	as.Nil(err)
+	as.Equal(len(devices2), 1)
+
+	as.NotEqual(devices1, devices2, "expected containers to get different devices")
+}
+
+func TestMultiPodGPUAllocation(t *testing.T) {
+	podLister := &testActivePodsLister{}
+
+	testGpuManager := &nvidiaGPUManager{
+		activePodsLister: podLister,
+		allGPUs:          sets.NewString("/dev/nvidia0", "/dev/nvidia1"),
+		allocated:        newPodGPUs(),
+	}
+
+	// Expect that no devices are in use.
+	gpusInUse := testGpuManager.gpusInUse()
+	as := assert.New(t)
+	as.Equal(len(gpusInUse.devices()), 0)
+
+	// Allocated GPUs for a pod with two containers.
+	podA := makeTestPod(1, 1)
+	// Allocate for the first container.
+	devicesA, err := testGpuManager.AllocateGPU(podA, &podA.Spec.Containers[0])
+	as.Nil(err)
+	as.Equal(len(devicesA), 1)
+
+	podLister.activePods = append(podLister.activePods, podA)
+
+	// further allocations should fail.
+	podB := makeTestPod(1, 1)
+	// Allocate for the first container.
+	devicesB, err := testGpuManager.AllocateGPU(podB, &podB.Spec.Containers[0])
+	as.Nil(err)
+	as.Equal(len(devicesB), 1)
+	as.NotEqual(devicesA, devicesB, "expected pods to get different devices")
+}
+
+func TestPodContainerRestart(t *testing.T) {
+	podLister := &testActivePodsLister{}
+
+	testGpuManager := &nvidiaGPUManager{
+		activePodsLister: podLister,
+		allGPUs:          sets.NewString("/dev/nvidia0", "/dev/nvidia1"),
+		allocated:        newPodGPUs(),
+		defaultDevices:   []string{"/dev/nvidia-smi"},
+	}
+
+	// Expect that no devices are in use.
+	gpusInUse := testGpuManager.gpusInUse()
+	as := assert.New(t)
+	as.Equal(len(gpusInUse.devices()), 0)
+
+	// Make a pod with one containers that requests two GPUs.
+	podA := makeTestPod(1, 2)
+	// Allocate GPUs
+	devicesA, err := testGpuManager.AllocateGPU(podA, &podA.Spec.Containers[0])
+	as.Nil(err)
+	as.Equal(len(devicesA), 3)
+
+	podLister.activePods = append(podLister.activePods, podA)
+
+	// further allocations should fail.
+	podB := makeTestPod(1, 1)
+	_, err = testGpuManager.AllocateGPU(podB, &podB.Spec.Containers[0])
+	as.NotNil(err)
+
+	// Allcate GPU for existing Pod A.
+	// The same gpus must be returned.
+	devicesAretry, err := testGpuManager.AllocateGPU(podA, &podA.Spec.Containers[0])
+	as.Nil(err)
+	as.Equal(len(devicesA), 3)
+	as.True(sets.NewString(devicesA...).Equal(sets.NewString(devicesAretry...)))
+}