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Delete in-tree support for NVIDIA GPUs.

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This removes the alpha Accelerators feature gate which was deprecated in 1.10.
The alternative feature DevicePlugins went beta in 1.10.
This commit is contained in:
Rohit Agarwal
2018-03-21 13:56:51 -07:00
parent 1f69c34478
commit 87dda3375b
38 changed files with 42 additions and 1315 deletions
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9
pkg/scheduler/algorithm/predicates/predicates.go
View File

@@ -682,10 +682,6 @@ func GetResourceRequest(pod *v1.Pod) *schedulercache.Resource {
if cpu := rQuantity.MilliValue(); cpu > result.MilliCPU {
result.MilliCPU = cpu
}
case v1.ResourceNvidiaGPU:
if gpu := rQuantity.Value(); gpu > result.NvidiaGPU {
result.NvidiaGPU = gpu
}
default:
if v1helper.IsScalarResourceName(rName) {
value := rQuantity.Value()
@@ -734,7 +730,6 @@ func PodFitsResources(pod *v1.Pod, meta algorithm.PredicateMetadata, nodeInfo *s
}
if podRequest.MilliCPU == 0 &&
podRequest.Memory == 0 &&
podRequest.NvidiaGPU == 0 &&
podRequest.EphemeralStorage == 0 &&
len(podRequest.ScalarResources) == 0 {
return len(predicateFails) == 0, predicateFails, nil
@@ -747,10 +742,6 @@ func PodFitsResources(pod *v1.Pod, meta algorithm.PredicateMetadata, nodeInfo *s
if allocatable.Memory < podRequest.Memory+nodeInfo.RequestedResource().Memory {
predicateFails = append(predicateFails, NewInsufficientResourceError(v1.ResourceMemory, podRequest.Memory, nodeInfo.RequestedResource().Memory, allocatable.Memory))
}
if allocatable.NvidiaGPU < podRequest.NvidiaGPU+nodeInfo.RequestedResource().NvidiaGPU {
predicateFails = append(predicateFails, NewInsufficientResourceError(v1.ResourceNvidiaGPU, podRequest.NvidiaGPU, nodeInfo.RequestedResource().NvidiaGPU, allocatable.NvidiaGPU))
}
if allocatable.EphemeralStorage < podRequest.EphemeralStorage+nodeInfo.RequestedResource().EphemeralStorage {
predicateFails = append(predicateFails, NewInsufficientResourceError(v1.ResourceEphemeralStorage, podRequest.EphemeralStorage, nodeInfo.RequestedResource().EphemeralStorage, allocatable.EphemeralStorage))
}

50
pkg/scheduler/algorithm/predicates/predicates_test.go
View File

@@ -44,13 +44,12 @@ var (
hugePageResourceA = v1helper.HugePageResourceName(resource.MustParse("2Mi"))
)
func makeResources(milliCPU, memory, nvidiaGPUs, pods, extendedA, storage, hugePageA int64) v1.NodeResources {
func makeResources(milliCPU, memory, pods, extendedA, storage, hugePageA int64) v1.NodeResources {
return v1.NodeResources{
Capacity: v1.ResourceList{
v1.ResourceCPU: *resource.NewMilliQuantity(milliCPU, resource.DecimalSI),
v1.ResourceMemory: *resource.NewQuantity(memory, resource.BinarySI),
v1.ResourcePods: *resource.NewQuantity(pods, resource.DecimalSI),
v1.ResourceNvidiaGPU: *resource.NewQuantity(nvidiaGPUs, resource.DecimalSI),
extendedResourceA: *resource.NewQuantity(extendedA, resource.DecimalSI),
v1.ResourceEphemeralStorage: *resource.NewQuantity(storage, resource.BinarySI),
hugePageResourceA: *resource.NewQuantity(hugePageA, resource.BinarySI),
@@ -58,12 +57,11 @@ func makeResources(milliCPU, memory, nvidiaGPUs, pods, extendedA, storage, hugeP
}
}
func makeAllocatableResources(milliCPU, memory, nvidiaGPUs, pods, extendedA, storage, hugePageA int64) v1.ResourceList {
func makeAllocatableResources(milliCPU, memory, pods, extendedA, storage, hugePageA int64) v1.ResourceList {
return v1.ResourceList{
v1.ResourceCPU: *resource.NewMilliQuantity(milliCPU, resource.DecimalSI),
v1.ResourceMemory: *resource.NewQuantity(memory, resource.BinarySI),
v1.ResourcePods: *resource.NewQuantity(pods, resource.DecimalSI),
v1.ResourceNvidiaGPU: *resource.NewQuantity(nvidiaGPUs, resource.DecimalSI),
extendedResourceA: *resource.NewQuantity(extendedA, resource.DecimalSI),
v1.ResourceEphemeralStorage: *resource.NewQuantity(storage, resource.BinarySI),
hugePageResourceA: *resource.NewQuantity(hugePageA, resource.BinarySI),
@@ -357,7 +355,7 @@ func TestPodFitsResources(t *testing.T) {
}
for _, test := range enoughPodsTests {
node := v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 0, 32, 5, 20, 5).Capacity, Allocatable: makeAllocatableResources(10, 20, 0, 32, 5, 20, 5)}}
node := v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 32, 5, 20, 5).Capacity, Allocatable: makeAllocatableResources(10, 20, 32, 5, 20, 5)}}
test.nodeInfo.SetNode(&node)
RegisterPredicateMetadataProducerWithExtendedResourceOptions(test.ignoredExtendedResources)
meta := PredicateMetadata(test.pod, nil)
@@ -414,7 +412,7 @@ func TestPodFitsResources(t *testing.T) {
},
}
for _, test := range notEnoughPodsTests {
node := v1.Node{Status: v1.NodeStatus{Capacity: v1.ResourceList{}, Allocatable: makeAllocatableResources(10, 20, 0, 1, 0, 0, 0)}}
node := v1.Node{Status: v1.NodeStatus{Capacity: v1.ResourceList{}, Allocatable: makeAllocatableResources(10, 20, 1, 0, 0, 0)}}
test.nodeInfo.SetNode(&node)
fits, reasons, err := PodFitsResources(test.pod, PredicateMetadata(test.pod, nil), test.nodeInfo)
if err != nil {
@@ -472,7 +470,7 @@ func TestPodFitsResources(t *testing.T) {
}
for _, test := range storagePodsTests {
node := v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 0, 32, 5, 20, 5).Capacity, Allocatable: makeAllocatableResources(10, 20, 0, 32, 5, 20, 5)}}
node := v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 32, 5, 20, 5).Capacity, Allocatable: makeAllocatableResources(10, 20, 32, 5, 20, 5)}}
test.nodeInfo.SetNode(&node)
fits, reasons, err := PodFitsResources(test.pod, PredicateMetadata(test.pod, nil), test.nodeInfo)
if err != nil {
@@ -2062,7 +2060,7 @@ func TestRunGeneralPredicates(t *testing.T) {
newResourcePod(schedulercache.Resource{MilliCPU: 9, Memory: 19})),
node: &v1.Node{
ObjectMeta: metav1.ObjectMeta{Name: "machine1"},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 0, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 0, 32, 0, 0, 0)},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 32, 0, 0, 0)},
},
fits: true,
wErr: nil,
@@ -2074,7 +2072,7 @@ func TestRunGeneralPredicates(t *testing.T) {
newResourcePod(schedulercache.Resource{MilliCPU: 5, Memory: 19})),
node: &v1.Node{
ObjectMeta: metav1.ObjectMeta{Name: "machine1"},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 0, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 0, 32, 0, 0, 0)},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 32, 0, 0, 0)},
},
fits: false,
wErr: nil,
@@ -2084,34 +2082,6 @@ func TestRunGeneralPredicates(t *testing.T) {
},
test: "not enough cpu and memory resource",
},
{
pod: &v1.Pod{},
nodeInfo: schedulercache.NewNodeInfo(
newResourcePod(schedulercache.Resource{MilliCPU: 9, Memory: 19})),
node: &v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 1, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 1, 32, 0, 0, 0)}},
fits: true,
wErr: nil,
test: "no resources/port/host requested always fits on GPU machine",
},
{
pod: newResourcePod(schedulercache.Resource{MilliCPU: 3, Memory: 1, NvidiaGPU: 1}),
nodeInfo: schedulercache.NewNodeInfo(
newResourcePod(schedulercache.Resource{MilliCPU: 5, Memory: 10, NvidiaGPU: 1})),
node: &v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 1, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 1, 32, 0, 0, 0)}},
fits: false,
wErr: nil,
reasons: []algorithm.PredicateFailureReason{NewInsufficientResourceError(v1.ResourceNvidiaGPU, 1, 1, 1)},
test: "not enough GPU resource",
},
{
pod: newResourcePod(schedulercache.Resource{MilliCPU: 3, Memory: 1, NvidiaGPU: 1}),
nodeInfo: schedulercache.NewNodeInfo(
newResourcePod(schedulercache.Resource{MilliCPU: 5, Memory: 10, NvidiaGPU: 0})),
node: &v1.Node{Status: v1.NodeStatus{Capacity: makeResources(10, 20, 1, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 1, 32, 0, 0, 0)}},
fits: true,
wErr: nil,
test: "enough GPU resource",
},
{
pod: &v1.Pod{
Spec: v1.PodSpec{
@@ -2121,7 +2091,7 @@ func TestRunGeneralPredicates(t *testing.T) {
nodeInfo: schedulercache.NewNodeInfo(),
node: &v1.Node{
ObjectMeta: metav1.ObjectMeta{Name: "machine1"},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 0, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 0, 32, 0, 0, 0)},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 32, 0, 0, 0)},
},
fits: false,
wErr: nil,
@@ -2133,7 +2103,7 @@ func TestRunGeneralPredicates(t *testing.T) {
nodeInfo: schedulercache.NewNodeInfo(newPodWithPort(123)),
node: &v1.Node{
ObjectMeta: metav1.ObjectMeta{Name: "machine1"},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 0, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 0, 32, 0, 0, 0)},
Status: v1.NodeStatus{Capacity: makeResources(10, 20, 32, 0, 0, 0).Capacity, Allocatable: makeAllocatableResources(10, 20, 32, 0, 0, 0)},
},
fits: false,
wErr: nil,
@@ -3443,7 +3413,7 @@ func TestPodSchedulesOnNodeWithMemoryPressureCondition(t *testing.T) {
ImagePullPolicy: "Always",
// at least one requirement -> burstable pod
Resources: v1.ResourceRequirements{
Requests: makeAllocatableResources(100, 100, 100, 100, 0, 0, 0),
Requests: makeAllocatableResources(100, 100, 100, 0, 0, 0),
},
},
},

4
pkg/scheduler/algorithm/priorities/resource_limits.go
View File

@@ -109,10 +109,6 @@ func getResourceLimits(pod *v1.Pod) *schedulercache.Resource {
if ephemeralStorage := rQuantity.Value(); ephemeralStorage > result.EphemeralStorage {
result.EphemeralStorage = ephemeralStorage
}
case v1.ResourceNvidiaGPU:
if gpu := rQuantity.Value(); gpu > result.NvidiaGPU {
result.NvidiaGPU = gpu
}
default:
if v1helper.IsScalarResourceName(rName) {
value := rQuantity.Value()