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Joint Inference
Motivation
Inference on the edge can get a shorter latency and a higher throughput, and inference on the cloud can get better inference precision.
The collaborative inference technology detects hard samples on the edge and sends them to the cloud for inference.
In this way, simple samples inference on the edge ensures latency and throughput, while hard samples inference on the cloud improves the overall precision.
Goals
- Joint inference improves the inference precision without significantly reducing the time and throughput.
Proposal
We propose using Kubernetes Custom Resource Definitions (CRDs) to describe
the joint inference specification/status and a controller to synchronize these updates between edge and cloud.
Use Cases
-
User can create a joint inference service with providing a training script,
specifying the aggregation algorithm, configuring training hyper parameters,
configuring training datasets. -
Users can get the joint inference status, including the counts of inference at the edge/cloud.
Design Details
CRD API Group and Version
The JointInferenceService CRD will be namespace-scoped.
The tables below summarize the group, kind and API version details for the CRD.
- JointInferenceService
| Field | Description |
|---|---|
| Group | neptune.io |
| APIVersion | v1alpha1 |
| Kind | JointInferenceService |
Joint inference CRD
Below is the CustomResourceDefinition yaml for JointInferenceService:
apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
name: jointinferenceservices.neptune.io
spec:
group: neptune.io
names:
kind: JointInferenceService
plural: jointinferenceservices
shortNames:
- jointinferenceservice
- jis
scope: Namespaced
versions:
- name: v1alpha1
subresources:
# status enables the status subresource.
status: {}
served: true
storage: true
schema:
openAPIV3Schema:
type: object
properties:
spec:
type: object
required:
- edgeWorker
- cloudWorker
properties:
edgeWorker:
type: object
required:
- name
- model
- nodeName
- hardExampleAlgorithm
- workerSpec
properties:
name:
type: string
model:
type: object
required:
- name
properties:
name:
type: string
nodeName:
type: string
hardExampleAlgorithm:
type: object
required:
- name
properties:
name:
type: string
workerSpec:
type: object
required:
- scriptDir
- scriptBootFile
- frameworkType
- frameworkVersion
properties:
scriptDir:
type: string
scriptBootFile:
type: string
frameworkType:
type: string
frameworkVersion:
type: string
parameters:
type: array
items:
type: object
required:
- key
- value
properties:
key:
type: string
value:
type: string
cloudWorker:
type: object
required:
- name
- model
- nodeName
- workerSpec
properties:
name:
type: string
model:
type: object
required:
- name
properties:
name:
type: string
nodeName:
type: string
workerSpec:
type: object
required:
- scriptDir
- scriptBootFile
- frameworkType
- frameworkVersion
properties:
scriptDir:
type: string
scriptBootFile:
type: string
frameworkType:
type: string
frameworkVersion:
type: string
parameters:
type: array
items:
type: object
required:
- key
- value
properties:
key:
type: string
value:
type: string
status:
type: object
properties:
conditions:
type: array
items:
type: object
properties:
type:
type: string
status:
type: string
lastHeartbeatTime:
type: string
format: date-time
lastTransitionTime:
type: string
format: date-time
reason:
type: string
message:
type: string
startTime:
type: string
format: date-time
active:
type: integer
failed:
type: integer
metrics:
type: array
items:
type: object
properties:
key:
type: string
value:
type: string
additionalPrinterColumns:
- name: status
type: string
description: The status of the jointinference service
jsonPath: ".status.conditions[-1].type"
- name: active
type: integer
description: The number of active worker
jsonPath: ".status.active"
- name: failed
type: integer
description: The number of failed worker
jsonPath: ".status.failed"
- name: Age
type: date
jsonPath: .metadata.creationTimestamp
Joint inference type definition
package v1alpha1
import (
v1 "k8s.io/api/core/v1"
metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
)
// +genclient
// +k8s:deepcopy-gen:interfaces=k8s.io/apimachinery/pkg/runtime.Object
// JointInferenceService describes the data that a jointinferenceservice resource should have
type JointInferenceService struct {
metav1.TypeMeta `json:",inline"`
metav1.ObjectMeta `json:"metadata"`
Spec JointInferenceServiceSpec `json:"spec"`
Status JointInferenceServiceStatus `json:"status,omitempty"`
}
// JointInferenceServiceSpec is a description of a jointinferenceservice
type JointInferenceServiceSpec struct {
EdgeWorker EdgeWorker `json:"edgeWorker"`
CloudWorker CloudWorker `json:"cloudWorker"`
}
// EdgeWorker describes the data a edge worker should have
type EdgeWorker struct {
Name string `json:"name"`
Model SmallModel `json:"model"`
NodeName string `json:"nodeName"`
HardExampleAlgorithm HardExampleAlgorithm `json:"hardExampleAlgorithm"`
WorkerSpec CommonWorkerSpec `json:"workerSpec"`
}
// CloudWorker describes the data a cloud worker should have
type CloudWorker struct {
Name string `json:"name"`
Model BigModel `json:"model"`
NodeName string `json:"nodeName"`
WorkerSpec CommonWorkerSpec `json:"workerSpec"`
}
type SmallModel struct {
Name string `json:"name"`
}
type BigModel struct {
Name string `json:"name"`
}
type HardExampleAlgorithm struct {
Name string `json:"name"`
}
// +k8s:deepcopy-gen:interfaces=k8s.io/apimachinery/pkg/runtime.Object
// JointInferenceServiceList is a list of JointInferenceServices.
type JointInferenceServiceList struct {
metav1.TypeMeta `json:",inline"`
metav1.ListMeta `json:"metadata"`
Items []JointInferenceService `json:"items"`
}
// JointInferenceServiceStatus represents the current state of a joint inference service.
type JointInferenceServiceStatus struct {
// The latest available observations of a joint inference service's current state.
// +optional
Conditions []JointInferenceServiceCondition `json:"conditions,omitempty"`
// Represents time when the service was acknowledged by the service controller.
// It is not guaranteed to be set in happens-before order across separate operations.
// It is represented in RFC3339 form and is in UTC.
// +optional
StartTime *metav1.Time `json:"startTime,omitempty"`
// The number of actively running workers.
// +optional
Active int32 `json:"active"`
// The number of workers which reached to Failed.
// +optional
Failed int32 `json:"failed"`
// Metrics of the joint inference service.
Metrics []Metric `json:"metrics,omitempty"`
}
type JointInferenceServiceConditionType string
// These are valid conditions of a service.
const (
// JointInferenceServiceCondPending means the service has been accepted by the system,
// but one or more of the workers has not been started.
JointInferenceServiceCondPending JointInferenceServiceConditionType = "Pending"
// JointInferenceServiceCondFailed means the service has failed its execution.
JointInferenceServiceCondFailed JointInferenceServiceConditionType = "Failed"
// JointInferenceServiceReady means the service has been ready.
JointInferenceServiceCondRunning JointInferenceServiceConditionType = "Running"
)
// JointInferenceServiceCondition describes current state of a service.
type JointInferenceServiceCondition struct {
// Type of service condition, Complete or Failed.
Type JointInferenceServiceConditionType `json:"type"`
// Status of the condition, one of True, False, Unknown.
Status v1.ConditionStatus `json:"status"`
// Last time the condition was checked.
// +optional
LastHeartbeatTime metav1.Time `json:"lastHeartbeatTime,omitempty"`
// Last time the condition transit from one status to another.
// +optional
LastTransitionTime metav1.Time `json:"lastTransitionTime,omitempty"`
// (brief) reason for the condition's last transition.
// +optional
Reason string `json:"reason,omitempty"`
// Human readable message indicating details about last transition.
// +optional
Message string `json:"message,omitempty"`
}
Validation
Open API v3 Schema based validation can be used to guard against bad requests.
Invalid values for fields ( example string value for a boolean field etc) can be validated using this.
Here is a list of validations we need to support :
- The
datasetspecified in the crd should exist in k8s. - The
modelspecified in the crd should exist in k8s. - The edgenode name specified in the crd should exist in k8s.
joint inference sample
apiVersion: neptune.io/v1alpha1
kind: JointInferenceService
metadata:
name: helmet-detection-demo
namespace: default
spec:
edgeWorker:
name: "edgeworker"
model:
name: "small-model"
nodeName: "edge0"
hardExampleAlgorithm:
name: "IBT"
workerSpec:
scriptDir: "/code"
scriptBootFile: "edge_inference.py"
frameworkType: "tensorflow"
frameworkVersion: "1.18"
parameters:
- key: "nms_threshold"
value: "0.6"
cloudWorker:
name: "work"
model:
name: "big-model"
nodeName: "solar-corona-cloud"
workerSpec:
scriptDir: "/code"
scriptBootFile: "cloud_inference.py"
frameworkType: "tensorflow"
frameworkVersion: "1.18"
parameters:
- key: "nms_threshold"
value: "0.6"
Controller Design
The joint inference controller starts three separate goroutines called upstream, downstream and joint-inferencecontroller. These are not separate controllers as such but named here for clarity.
- joint inference: watch the updates of joint-inference-task crds, and create the workers to complete the task.
- downstream: synchronize the joint-inference updates from the cloud to the edge node.
- upstream: synchronize the joint-inference updates from the edge to the cloud node.
Joint Inference Controller
The joint-inference controller watches for the updates of joint-inference tasks and the corresponding pods against the K8S API server.
Updates are categorized below along with the possible actions:
| Update Type | Action |
|---|---|
| New Joint-inference-service Created | Create the cloud/edge worker |
| Joint-inference-service Deleted | NA. These workers will be deleted by GM. |
| The corresponding pod created/running/completed/failed | Update the status of joint-inference task. |
Downstream Controller
The downstream controller watches for joint-inference updates against the K8S API server.
Updates are categorized below along with the possible actions that the downstream controller can take:
| Update Type | Action |
|---|---|
| New Joint-inference-service Created | Sends the task information to LCs. |
| Joint-inference-service Deleted | The controller sends the delete event to LCs. |
Upstream Controller
The upstream controller watches for joint-inference-task updates from the edge node and applies these updates against the API server in the cloud.
Updates are categorized below along with the possible actions that the upstream controller can take:
| Update Type | Action |
|---|---|
| Joint-inference-service Reported State Updated | The controller appends the reported status of the Joint-inference-service in the cloud. |
Details of api between GM(cloud) and LC(edge)
-
GM(downstream controller) syncs the task info to LC:
// POST <namespace>/neptune/downstream/jointinferenceservices/<name>/insert // body same to the task crd of k8s api, omitted here. -
LC uploads the task status which reported by the worker to GM(upstream controller):
// POST <namespace>/neptune/upstream/jointinferenceservices/<name>/status // JoinInferenceServiceStatus defines status that send to GlobalManager type JoinInferenceServiceStatus struct { Phase string `json:"phase"` Status string `json:"status"` Output *Output `json:"output"` } // Output defines task output information type Output struct { Models []Model `json:"models"` TaskInfo *TaskInfo `json:"taskInfo"` } // Model defines the model information type Model struct { Format string `json:"format"` URL string `json:"url"` } // TaskInfo defines the task information type TaskInfo struct { InferenceNumber int `json:"inferenceNumber"` HardExampleNumber int `json:"hardExampleNumber"` UploadCloudRatio float64 `json:"uploadCloudRatio"` StartTime string `json:"startTime"` CurrentTime string `json:"currentTime"` }
Details of api between Worker(edge) and LC(edge)
-
Worker sends inference info to LC in same edge node:
// POST /neptune/workers/<worker-name>/info{ "name": "worker-name", "namespace": "default", "ownerName": "jointinferenceservice-name", "ownerKind": "jointinferenceservice", "kind": "inference", "status": "completed/failed/running", "taskInfo": { "inferenceNumber": 1000, "hardExampleNumber": 100, "uploadCloudRatio": 0.1, "startTime": "2020-11-03T08:39:22.517Z", "updateTime": "2020-11-03T08:50:22.517Z" } }
Flow of Joint Inference
- The flow of joint inference service creation:
Workers Communication
