Project-HAMi · hami-robot · Nov 3, 2025 · Oct 24, 2025 · Oct 24, 2025 · Oct 24, 2025
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -87,7 +87,7 @@
 - add ut for ascend by ([@shijinye](https://github.com/shijinye)) in [#664](https://github.com/Project-HAMi/HAMi/pull/664)
 - optimization map init in test by ([@lengrongfu](https://github.com/lengrongfu)) in [#678](https://github.com/Project-HAMi/HAMi/pull/678)
 - Optimize monitor by ([@for800000](https://github.com/for800000)) in [#683](https://github.com/Project-HAMi/HAMi/pull/683)
-- fix code lint faild by ([@lengrongfu](https://github.com/lengrongfu)) in [#685](https://github.com/Project-HAMi/HAMi/pull/685)
+- fix code lint failed by ([@lengrongfu](https://github.com/lengrongfu)) in [#685](https://github.com/Project-HAMi/HAMi/pull/685)
 - fix(helm): Add NODE_NAME env var to the vgpu-monitor container from spec.nodeName by ([@Nimbus318](https://github.com/Nimbus318)) in [#687](https://github.com/Project-HAMi/HAMi/pull/687)
 - fix vGPUmonitor deviceidx is always 0 by ([@lengrongfu](https://github.com/lengrongfu)) in [#684](https://github.com/Project-HAMi/HAMi/pull/684)
 - add ut for pkg/scheduler/event.go by ([@Penguin-zlh](https://github.com/Penguin-zlh)) in [#688](https://github.com/Project-HAMi/HAMi/pull/688)

diff --git a/blog/2024-12-31-post/index.md b/blog/2024-12-31-post/index.md
@@ -1600,7 +1600,7 @@ type DevicePluginServer interface {
  // Plugin can run device specific operations and instruct Kubelet
  // of the steps to make the Device available in the container
  Allocate(context.Context, *AllocateRequest) (*AllocateResponse, error)
- // PreStartContainer is called, if indicated by Device Plugin during registeration phase,
+ // PreStartContainer is called, if indicated by Device Plugin during registration phase,
  // before each container start. Device plugin can run device specific operations
  // such as resetting the device before making devices available to the container
  PreStartContainer(context.Context, *PreStartContainerRequest) (*PreStartContainerResponse, error)
@@ -1678,7 +1678,7 @@ func (plugin *NvidiaDevicePlugin) WatchAndRegister() {
  errorSleepInterval := time.Second * 5
  successSleepInterval := time.Second * 30
  for {
-  err := plugin.RegistrInAnnotation()
+  err := plugin.RegisterInAnnotation()
   if err != nil {
    klog.Errorf("Failed to register annotation: %v", err)
    klog.Infof("Retrying in %v seconds...", errorSleepInterval)
@@ -1692,7 +1692,7 @@ func (plugin *NvidiaDevicePlugin) WatchAndRegister() {
 ```
 
 ```golang
-func (plugin *NvidiaDevicePlugin) RegistrInAnnotation() error {
+func (plugin *NvidiaDevicePlugin) RegisterInAnnotation() error {
  devices := plugin.getAPIDevices()
  klog.InfoS("start working on the devices", "devices", devices)
  annos := make(map[string]string)

diff --git a/changelog/source/v2.5.0.md b/changelog/source/v2.5.0.md
@@ -66,7 +66,7 @@ authors:
 - add ut for ascend by ([@shijinye](https://github.com/shijinye)) in [#664](https://github.com/Project-HAMi/HAMi/pull/664)
 - optimization map init in test by ([@lengrongfu](https://github.com/lengrongfu)) in [#678](https://github.com/Project-HAMi/HAMi/pull/678)
 - Optimize monitor by ([@for800000](https://github.com/for800000)) in [#683](https://github.com/Project-HAMi/HAMi/pull/683)
-- fix code lint faild by ([@lengrongfu](https://github.com/lengrongfu)) in [#685](https://github.com/Project-HAMi/HAMi/pull/685)
+- fix code lint failed by ([@lengrongfu](https://github.com/lengrongfu)) in [#685](https://github.com/Project-HAMi/HAMi/pull/685)
 - fix(helm): Add NODE_NAME env var to the vgpu-monitor container from spec.nodeName by ([@Nimbus318](https://github.com/Nimbus318)) in [#687](https://github.com/Project-HAMi/HAMi/pull/687)
 - fix vGPUmonitor deviceidx is always 0 by ([@lengrongfu](https://github.com/lengrongfu)) in [#684](https://github.com/Project-HAMi/HAMi/pull/684)
 - add ut for pkg/scheduler/event.go by ([@Penguin-zlh](https://github.com/Penguin-zlh)) in [#688](https://github.com/Project-HAMi/HAMi/pull/688)
@@ -160,4 +160,4 @@ authors:
 - phoenixwu0229 ([@phoenixwu0229](https://github.com/phoenixwu0229))
 - chinaran ([@chinaran](https://github.com/chinaran))
 
-**Full Changelog**: https://github.com/Project-HAMi/HAMi/compare/v2.4.1...v2.5.0
+**Full Changelog**: https://github.com/Project-HAMi/HAMi/compare/v2.4.1...v2.5.0
diff --git a/docs/contributor/contributers.md → docs/contributor/contributors.md b/docs/contributor/contributers.md → docs/contributor/contributors.md
diff --git a/docs/contributor/goverance.md → docs/contributor/governance.md b/docs/contributor/goverance.md → docs/contributor/governance.md
@@ -1,5 +1,5 @@
 ---
-title: Goverance
+title: Governance
 ---
 
 Heterogeneous AI Computing Virtualization Middleware (HAMi), formerly known as k8s-vGPU-scheduler, is an "all-in-one" tools designed to manage Heterogeneous AI Computing Devices in a k8s cluster

diff --git a/docs/contributor/ladder.md b/docs/contributor/ladder.md
@@ -1,5 +1,5 @@
 ---
-title: Contributer Ladder
+title: Contributor Ladder
 ---
 
 This docs different ways to get involved and level up within the project. You can see different roles within the project in the contributor roles.

diff --git a/docs/developers/Dynamic-mig.md b/docs/developers/Dynamic-mig.md
@@ -19,7 +19,7 @@ HAMi is done by using [hami-core](https://github.com/Project-HAMi/HAMi-core), wh
 - CPU, Mem, and GPU combined schedule
 - GPU dynamic slice: Hami-core and MIG
 - Support node-level binpack and spread by GPU memory, CPU and Mem
-- A unified vGPU Pool different virtualization technics
+- A unified vGPU Pool different virtualization techniques
 - Tasks can choose to use MIG, use HAMi-core, or use both.
 
 ### Config maps
@@ -104,7 +104,7 @@ data:
 
 ## Examples
 
-Dynamic mig is compatable with hami tasks, as the example below: 
+Dynamic mig is compatible with hami tasks, as the example below: 
 Just Setting `nvidia.com/gpu` and `nvidia.com/gpumem`.
 
 ```yaml
@@ -149,7 +149,7 @@ The Procedure of a vGPU task which uses dynamic-mig is shown below:
 
 <img src="https://github.com/Project-HAMi/HAMi/blob/master/docs/develop/imgs/hami-dynamic-mig-procedure.png?raw=true" width = "800" /> 
 
-Note that after submited a task, deviceshare plugin will iterate over templates defined in configMap `hami-scheduler-device`, and find the first available template to fit. You can always change the content of that configMap, and restart vc-scheduler to customize.
+Note that after submitted a task, deviceshare plugin will iterate over templates defined in configMap `hami-scheduler-device`, and find the first available template to fit. You can always change the content of that configMap, and restart vc-scheduler to customize.
 
 If you submit the example on an empty A100-PCIE-40GB node, then it will select a GPU and choose MIG template below:
 

diff --git a/docs/developers/protocol.md b/docs/developers/protocol.md
@@ -12,10 +12,10 @@ HAMi needs to know the spec of each AI devices in the cluster in order to schedu
 
 ```
 hami.io/node-handshake-\{device-type\}: Reported_\{device_node_current_timestamp\}
-hami.io/node-\{deivce-type\}-register: \{Device 1\}:\{Device2\}:...:\{Device N\}
+hami.io/node-\{device-type\}-register: \{Device 1\}:\{Device2\}:...:\{Device N\}
 ```
 
-The definiation of each device is in the following format:
+The definition of each device is in the following format:
 ```
 \{Device UUID\},\{device split count\},\{device memory limit\},\{device core limit\},\{device type\},\{device numa\},\{healthy\}
 ```

diff --git a/docs/developers/scheduling.md b/docs/developers/scheduling.md
@@ -82,7 +82,7 @@ GPU spread, use different GPU cards when possible, egs:
 
 ### Node-scheduler-policy
 
-![node-shceduler-policy-demo.png](../resources/node-shceduler-policy-demo.png)
+![node-scheduler-policy-demo.png](../resources/node-scheduler-policy-demo.png)
 
 #### Binpack
 
@@ -166,4 +166,4 @@ GPU1 Score: ((20+10)/100 + (1000+2000)/8000)) * 10 = 6.75
 GPU2 Score: ((20+70)/100 + (1000+6000)/8000)) * 10 = 17.75
 ```
 
-So, in `Spread` policy we can select `GPU1`.
+So, in `Spread` policy we can select `GPU1`.
diff --git a/docs/get-started/deploy-with-helm.md b/docs/get-started/deploy-with-helm.md
@@ -160,7 +160,7 @@ spec:
           nvidia.com/gpumem: 10240 # Each vGPU contains 10240m device memory （Optional,Integer）
 ```
 
-#### 2. Verify in container resouce control {#verify-in-container-resouce-control}
+#### 2. Verify in container resource control {#verify-in-container-resource-control}
 
 Execute the following query command:
 

diff --git a/docs/installation/how-to-use-volcano-vgpu.md b/docs/installation/how-to-use-volcano-vgpu.md
@@ -113,7 +113,7 @@ spec:
       resources:
         limits:
           volcano.sh/vgpu-number: 2 # requesting 2 gpu cards
-          volcano.sh/vgpu-memory: 3000 # (optinal)each vGPU uses 3G device memory
+          volcano.sh/vgpu-memory: 3000 # (optional)each vGPU uses 3G device memory
           volcano.sh/vgpu-cores: 50 # (optional)each vGPU uses 50% core
 EOF
 ```

diff --git a/docs/installation/offline-installation.md b/docs/installation/offline-installation.md
@@ -21,8 +21,8 @@ Load the images, tag them with your internal registry, and push them to your reg
 docker load -i {HAMi_image}.tar
 docker tag projecthami/hami:{HAMi version} {your_inner_registry}/hami:{HAMi version}
 docker push {your_inner_registry}/hami:{HAMi version}
-docker tag docker.io/jettech/kube-webhook-certgen:v1.5.2 {your inner_regisry}/kube-webhook-certgen:v1.5.2
-docker push {your inner_regisry}/kube-webhook-certgen:v1.5.2
+docker tag docker.io/jettech/kube-webhook-certgen:v1.5.2 {your inner_registry}/kube-webhook-certgen:v1.5.2
+docker push {your inner_registry}/kube-webhook-certgen:v1.5.2
 docker tag liangjw/kube-webhook-certgen:v1.1.1 {your_inner_registry}/kube-webhook-certgen:v1.1.1
 docker tag registry.cn-hangzhou.aliyuncs.com/google_containers/kube-scheduler:{your kubernetes version} {your_inner_registry}/kube-scheduler:{your kubernetes version}
 docker push {your_inner_registry}/kube-scheduler:{your kubernetes version}
@@ -31,7 +31,7 @@ docker push {your_inner_registry}/kube-scheduler:{your kubernetes version}
 ## Prepare HAMi chart
 
 Download the charts folder from [github](https://github.com/Project-HAMi/HAMi/tree/master/charts),
-place it into $\{CHART_PATH\} inside cluser, then edit the following fields in $\{CHART_PATH\}/hami/values.yaml.
+place it into $\{CHART_PATH\} inside cluster, then edit the following fields in $\{CHART_PATH\}/hami/values.yaml.
 
 ```yaml
 scheduler:

diff --git a/docs/key-features/device-resource-isolation.md b/docs/key-features/device-resource-isolation.md
@@ -2,7 +2,7 @@
 title: Device resource isolation
 ---
 
-A simple demostration for device isolation:
+A simple demonstration for device isolation:
 A task with the following resources.
 
 ```

diff --git a/docs/releases.md b/docs/releases.md
@@ -79,7 +79,7 @@ Hence, if an issue is important it is important to advocate its priority early i
 
 <!-- ### Release Artifacts
 
-The HAMi container images are availble at `dockerHub`. 
+The HAMi container images are available at `dockerHub`. 
 You can visit `https://hub.docker.com/r/karmada/<component_name>` to see the details of images.
 For example, [here](https://hub.docker.com/r/karmada/karmada-controller-manager) for karmada-controller-manager.
 

diff --git a/docs/resources/installation/install-binary/generate_cert/generate_ca.sh b/docs/resources/installation/install-binary/generate_cert/generate_ca.sh
@@ -1,6 +1,6 @@
 #!/bin/bash
 
-# genererate front-proxy-ca, server-ca
+# generate front-proxy-ca, server-ca
 
 set -e
 set -o pipefail

diff --git a/docs/resources/installation/install-binary/generate_cert/generate_etcd.sh b/docs/resources/installation/install-binary/generate_cert/generate_etcd.sh
@@ -1,6 +1,6 @@
 #!/bin/bash
 
-# genererate CA & leaf certificates of etcd.
+# generate CA & leaf certificates of etcd.
 
 set -e
 set -o pipefail

diff --git a/.../resources/node-shceduler-policy-demo.png → .../resources/node-scheduler-policy-demo.png b/.../resources/node-shceduler-policy-demo.png → .../resources/node-scheduler-policy-demo.png
diff --git a/docs/userguide/Enflame-device/enable-enflame-gcu-sharing.md b/docs/userguide/Enflame-device/enable-enflame-gcu-sharing.md
@@ -24,7 +24,7 @@ title: Enable Enflame GPU Sharing
 
 ## Enabling GCU-sharing Support
 
-* Deploy gcushare-device-plugin on enflame nodes (Please consult your device provider to aquire its package and document)
+* Deploy gcushare-device-plugin on enflame nodes (Please consult your device provider to acquire its package and document)
 
 > **NOTICE:** *Install only gpushare-device-plugin, don't install gpu-scheduler-plugin package.*
 

diff --git a/docs/userguide/Hygon-device/enable-hygon-dcu-sharing.md b/docs/userguide/Hygon-device/enable-hygon-dcu-sharing.md
@@ -78,4 +78,4 @@ Launch your DCU tasks like you usually do
 
 1. DCU-sharing in init container is not supported, pods with "hygon.com/dcumem" in init container will never be scheduled.
 
-2. Only one vdcu can be aquired per container. If you want to mount multiple dcu devices, then you shouldn't set `hygon.com/dcumem` or `hygon.com/dcucores`
+2. Only one vdcu can be acquired per container. If you want to mount multiple dcu devices, then you shouldn't set `hygon.com/dcumem` or `hygon.com/dcucores`
diff --git a/docs/userguide/Iluvatar-device/enable-illuvatar-gpu-sharing.md b/docs/userguide/Iluvatar-device/enable-illuvatar-gpu-sharing.md
@@ -23,7 +23,7 @@ title: Enable Illuvatar GPU Sharing
 
 ## Enabling GPU-sharing Support
 
-* Deploy gpu-manager on iluvatar nodes (Please consult your device provider to aquire its package and document)
+* Deploy gpu-manager on iluvatar nodes (Please consult your device provider to acquire its package and document)
 
 > **NOTICE:** *Install only gpu-manager, don't install gpu-admission package.*
 

diff --git a/docs/userguide/Metax-device/Metax-GPU/enable-metax-gpu-schedule.md b/docs/userguide/Metax-device/Metax-GPU/enable-metax-gpu-schedule.md
@@ -40,7 +40,7 @@ the GPU device plugin (gpu-device) handles fine-grained allocation based on the
 
 ## Enabling topo-awareness scheduling
 
-* Deploy Metax GPU Extensions on metax nodes (Please consult your device provider to aquire its package and document)
+* Deploy Metax GPU Extensions on metax nodes (Please consult your device provider to acquire its package and document)
 
 * Deploy HAMi according to README.md
 

diff --git a/docs/userguide/Metax-device/Metax-GPU/examples/allocate-binpack.md b/docs/userguide/Metax-device/Metax-GPU/examples/allocate-binpack.md
@@ -2,7 +2,7 @@
 title: Binpack schedule policy
 ---
 
-To allocate metax device with mininum damage to topology, you need to only assign `metax-tech.com/gpu` with annotations `hami.io/node-scheduler-policy: "binpack"`.
+To allocate metax device with minimum damage to topology, you need to only assign `metax-tech.com/gpu` with annotations `hami.io/node-scheduler-policy: "binpack"`.
 
 ```yaml
 apiVersion: v1

diff --git a/docs/userguide/Metax-device/Metax-GPU/specify-binpack-task.md b/docs/userguide/Metax-device/Metax-GPU/specify-binpack-task.md
@@ -2,7 +2,7 @@
 title: Binpack schedule policy
 ---
 
-To allocate metax device with mininum damage to topology, you need to only assign `metax-tech.com/gpu` with annotations `hami.io/node-scheduler-policy: "binpack"`.
+To allocate metax device with minimum damage to topology, you need to only assign `metax-tech.com/gpu` with annotations `hami.io/node-scheduler-policy: "binpack"`.
 
 ```yaml
 metadata:

diff --git a/docs/userguide/Mthreads-device/enable-mthreads-gpu-sharing.md b/docs/userguide/Mthreads-device/enable-mthreads-gpu-sharing.md
@@ -29,7 +29,7 @@ title: Enable Mthreads GPU sharing
 
 ## Enabling GPU-sharing Support
 
-* Deploy MT-CloudNative Toolkit on mthreads nodes (Please consult your device provider to aquire its package and document)
+* Deploy MT-CloudNative Toolkit on mthreads nodes (Please consult your device provider to acquire its package and document)
 
 > **NOTICE:** *You can remove mt-mutating-webhook and mt-gpu-scheduler after installation(optional).*
 

diff --git a/docs/userguide/NVIDIA-device/examples/specify-card-type-to-use.md b/docs/userguide/NVIDIA-device/examples/specify-card-type-to-use.md
@@ -24,4 +24,4 @@ spec:
           nvidia.com/gpu: 2 # requesting 2 vGPUs
 ```
 
-> **NOTICE:** * You can assign this task to multiple GPU types, use comma to seperate,In this example, we want to run this job on A100 or V100*
+> **NOTICE:** * You can assign this task to multiple GPU types, use comma to separate,In this example, we want to run this job on A100 or V100*
diff --git a/docs/userguide/NVIDIA-device/specify-device-type-to-use.md b/docs/userguide/NVIDIA-device/specify-device-type-to-use.md
@@ -11,13 +11,13 @@ For example, a task with the following annotation will be assigned to A100 or V1
 ```yaml
 metadata:
   annotations:
-    nvidia.com/use-gputype: "A100,V100" # Specify the card type for this job, use comma to seperate, will not launch job on non-specified card
+    nvidia.com/use-gputype: "A100,V100" # Specify the card type for this job, use comma to separate, will not launch job on non-specified card
 ```
 
 A task may use `nvidia.com/nouse-gputype` to evade certain type of GPU. In this following example, that job won't be assigned to 1080(include 1080Ti) or 2080(include 2080Ti) type of card. 
 
 ```yaml
 metadata:
   annotations:
-    nvidia.com/nouse-gputype: "1080,2080" # Specify the blacklist card type for this job, use comma to seperate, will not launch job on specified card
+    nvidia.com/nouse-gputype: "1080,2080" # Specify the blacklist card type for this job, use comma to separate, will not launch job on specified card
 ```
diff --git a/docs/userguide/monitoring/real-time-device-usage.md b/docs/userguide/monitoring/real-time-device-usage.md
@@ -14,9 +14,9 @@ It contains the following metrics:
 
 | Metrics  | Description | Example |
 |----------|-------------|---------|
-| Device_memory_desc_of_container | Container device meory real-time usage | `{context="0",ctrname="2-1-3-pod-1",data="0",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",module="0",offset="0",podname="2-1-3-pod-1",podnamespace="default",vdeviceid="0",zone="vGPU"}` 0 |
+| Device_memory_desc_of_container | Container device memory real-time usage | `{context="0",ctrname="2-1-3-pod-1",data="0",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",module="0",offset="0",podname="2-1-3-pod-1",podnamespace="default",vdeviceid="0",zone="vGPU"}` 0 |
 | Device_utilization_desc_of_container | Container device real-time utilization | `{ctrname="2-1-3-pod-1",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",podname="2-1-3-pod-1",podnamespace="default",vdeviceid="0",zone="vGPU"}` 0 |
 | HostCoreUtilization | GPU real-time utilization on host | `{deviceidx="0",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",zone="vGPU"}` 0 |
 | HostGPUMemoryUsage | GPU real-time device memory usage on host | `{deviceidx="0",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",zone="vGPU"}` 2.87244288e+08 |
 | vGPU_device_memory_limit_in_bytes | device limit for a certain container | `{ctrname="2-1-3-pod-1",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",podname="2-1-3-pod-1",podnamespace="default",vdeviceid="0",zone="vGPU"}` 2.62144e+09 |
-| vGPU_device_memory_usage_in_bytes | device usage for a certain container | `{ctrname="2-1-3-pod-1",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",podname="2-1-3-pod-1",podnamespace="default",vdeviceid="0",zone="vGPU"}` 0 |
+| vGPU_device_memory_usage_in_bytes | device usage for a certain container | `{ctrname="2-1-3-pod-1",deviceuuid="GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec",podname="2-1-3-pod-1",podnamespace="default",vdeviceid="0",zone="vGPU"}` 0 |
diff --git a/docs/userguide/volcano-vgpu/NVIDIA-GPU/examples/use_exclusive_gpu.md b/docs/userguide/volcano-vgpu/NVIDIA-GPU/examples/use_exclusive_gpu.md
@@ -4,7 +4,7 @@ title: Exclusive gpu usage
 
 ## Job description
 
-To allocate an exlusive GPU, you need only assign `volcano.sh/vgpu-number` without any other `volcano.sh/xxx` fields, as the example below:
+To allocate an exclusive GPU, you need only assign `volcano.sh/vgpu-number` without any other `volcano.sh/xxx` fields, as the example below:
 
 ```yaml
 apiVersion: v1

diff --git a/docs/userguide/volcano-vgpu/NVIDIA-GPU/how-to-use-volcano-vgpu.md b/docs/userguide/volcano-vgpu/NVIDIA-GPU/how-to-use-volcano-vgpu.md
@@ -113,7 +113,7 @@ spec:
       resources:
         limits:
           volcano.sh/vgpu-number: 2 # requesting 2 gpu cards
-          volcano.sh/vgpu-memory: 3000 # (optinal)each vGPU uses 3G device memory
+          volcano.sh/vgpu-memory: 3000 # (optional)each vGPU uses 3G device memory
           volcano.sh/vgpu-cores: 50 # (optional)each vGPU uses 50% core  
 EOF
 ```
Original file line number	Diff line number	Diff line change
Expand Up		@@ -78,4 +78,4 @@ Launch your DCU tasks like you usually do

		1. DCU-sharing in init container is not supported, pods with "hygon.com/dcumem" in init container will never be scheduled.

		2. Only one vdcu can be aquired per container. If you want to mount multiple dcu devices, then you shouldn't set `hygon.com/dcumem` or `hygon.com/dcucores`
		2. Only one vdcu can be acquired per container. If you want to mount multiple dcu devices, then you shouldn't set `hygon.com/dcumem` or `hygon.com/dcucores`