Change:
} <ins> func TestGetDeviceRunContainerOptions(t *testing.T) { res1 := TestResource{ resourceName:     "domain1.com/resource1", resourceQuantity: *resource.NewQuantity(int64(2), resource.DecimalSI), devs:             checkpoint.DevicesPerNUMA{0: []string{"dev1", "dev2"}}, topology:         true, } res2 := TestResource{ resourceName:     "domain2.com/resource2", resourceQuantity: *resource.NewQuantity(int64(1), resource.DecimalSI), devs:             checkpoint.DevicesPerNUMA{0: []string{"dev3", "dev4"}}, topology:         false, } testResources := make([]TestResource, 2) testResources = append(testResources, res1) testResources = append(testResources, res2) podsStub := activePodsStub{ activePods: []*v1.Pod{}, } as := require.New(t) tmpDir, err := ioutil.TempDir("", "checkpoint") as.Nil(err) defer os.RemoveAll(tmpDir) testManager, err := getTestManager(tmpDir, podsStub.getActivePods, testResources) as.Nil(err) pod1 := makePod(v1.ResourceList{ v1.ResourceName(res1.resourceName): res1.resourceQuantity, v1.ResourceName(res2.resourceName): res2.resourceQuantity, }) pod2 := makePod(v1.ResourceList{ v1.ResourceName(res2.resourceName): res2.resourceQuantity, }) activePods := []*v1.Pod{pod1, pod2} podsStub.updateActivePods(activePods) err = testManager.Allocate(pod1, &pod1.Spec.Containers[0]) as.Nil(err) err = testManager.Allocate(pod2, &pod2.Spec.Containers[0]) as.Nil(err) // when pod is in activePods, GetDeviceRunContainerOptions should return runContainerOpts, err := testManager.GetDeviceRunContainerOptions(pod1, &pod1.Spec.Containers[0]) as.Nil(err) as.Equal(len(runContainerOpts.Devices), 3) as.Equal(len(runContainerOpts.Mounts), 2) as.Equal(len(runContainerOpts.Envs), 2) activePods = []*v1.Pod{pod2} podsStub.updateActivePods(activePods) testManager.UpdateAllocatedDevices() // when pod is removed from activePods,G etDeviceRunContainerOptions should return error runContainerOpts, err = testManager.GetDeviceRunContainerOptions(pod1, &pod1.Spec.Containers[0]) as.Nil(err) as.Nil(runContainerOpts) } </ins> func TestInitContainerDeviceAllocation(t *testing.T) { // Requesting to create a pod that requests resourceName1 in init containers and normal containers // should succeed with devices allocated to init containers reallocated to normal containers.

Discussion:
<!-- Please use this template while reporting a bug and provide as much info as possible. Not doing so may result in your bug not being addressed in a timely manner. Thanks! If the matter is security related, please disclose it privately via --Pod worker panic when trying to re-allocating the device plugin resource during the node restart. The issue is potentially caused by an un-matching pod id. The map will be later used in an , which caused panic. ( func by itself is not thread-safe) Stack trace: DeviceManager Allocate() should be able to handle such race safely. Customer reported issue after upgrading to 1.18+. This is the new behavior introduced since 1.18+ from . Kubernetes version (use ): Cloud provider or hardware configuration: OS (e.g: ): Kernel (e.g. ): Install tools: Network plugin and version (if this is a network-related bug): Others:
/sig node
/assign looking into the issue
I think your PR is related to this issue.
/unassign seems pretty relatable to PR cc
/triage accepted /priority critical-urgent
/remove-priority critical-urgent I don't think this is a release blocker at this point given the history reading through ; we can fix this in a cherry-pick.
Hi all, We are the GCP/GKE customer from which this issue originates. I can provide more information: it happened multiple times on our production cluster since we upgraded to 1.18 it happens in 2 scenarios: when GCP has a "host maintenance" event on our VMs with GPU (they don't support VM live migrations when GPU are involved), it forces a VM reboot: when multiple pods on that k8s node request a GPU prior to the reboot, we sometimes get the kubelet panic on node restart. when GKE upgrades our node-pools: new nodes (fresh VMs) get multiple scheduled pods requesting a GPU, sometimes leading to the kubelet panic. =this happens outside of our control The end result is a Pod scheduled on a node, but with no container ever created: our production workload is effectively broken until we manually delete the stuck pods. More details about our device usage: we use a of the each node has one GPU, and our device plugin declares N devices per real GPU; nvidia/cuda supports multi processing so it effectively shares the GPU among N pods/containers.

(our workload is memory-gpu bound, and uses <1/Nth of the gpu memory each, so no conflict) it worked great for almost 3 years now, with N=8
/cc
Now that we have confirmation that it occurs in live cluster I will take a closer look later this week.
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The Kubernetes project currently lacks enough contributors to adequately respond to all issues and PRs. This bot triages issues and PRs according to the following rules: After 90d of inactivity, is applied After 30d of inactivity since was applied, is applied After 30d of inactivity since was applied, the issue is closed You can: Mark this issue or PR as fresh with Mark this issue or PR as rotten with Close this issue or PR with Offer to help out with [Issue Triage][1] Please send feedback to sig-contributor-experience at . /lifecycle stale [1]:
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