fix: correct typos and grammar in developer and userguide docs

docs/developers/hami-core-design.md

@@ -4,7 +4,7 @@ title: HAMi-core design
 
 HAMi-core is a hook library designed for the CUDA environment.
 It functions as an in-container GPU resource controller and has been adopted by projects
-like [HAMi](https://github.com/HAMi-project/HAMi) and [Volcano](https://github.com/volcano-sh/devices).
+like [HAMi](https://github.com/Project-HAMi/HAMi) and [Volcano](https://github.com/volcano-sh/devices).
 
 ![HAMi-core architecture diagram showing GPU resource controller design](/img/docs/common/developers/hami-core-design/hami-arch.png)
 

docs/developers/protocol.md

@@ -29,7 +29,7 @@ hami.io/node-nvidia-register: GPU-00552014-5c87-89ac-b1a6-7b53aa24b0ec,10,32768,
 
 ```
 
-In this example, this node has two different AI devices, 2 Nvidia-V100 GPUs, and 2 Cambircon 370-X4 MLUs
+In this example, this node has two different AI devices, 2 Nvidia-V100 GPUs, and 2 Cambricon 370-X4 MLUs
 
 A device node may become unavailable due to hardware or network failure. If a node hasn't registered in the last 5 minutes, the scheduler marks it as 'unavailable'.
 

docs/developers/scheduling.md

@@ -4,7 +4,7 @@ title: Scheduler Policy
 
 ## Summary
 
-Current in a cluster with many GPU nodes, nodes are not `binpack` or `spread` when making scheduling decisions, nor are GPU cards `binpack` or `spread` when using vGPU.
+Currently, in a cluster with many GPU nodes, nodes are not `binpack` or `spread` when making scheduling decisions, nor are GPU cards `binpack` or `spread` when using vGPU.
 
 ## Proposal
 
@@ -26,12 +26,12 @@ node binpack, use one node’s GPU card whenever possible, e.g.:
   - node2: GPU having 4 GPU device
 
 - request:
-  - pod1: User 1 GPU
-  - pod2: User 1 GPU
+  - pod1: Use 1 GPU
+  - pod2: Use 1 GPU
 
 - scheduler result:
-  - pod1: scheduler to node1
-  - pod2: scheduler to node1
+  - pod1: scheduled to node1
+  - pod2: scheduled to node1
 
 #### Story 2
 
@@ -42,12 +42,12 @@ node spread, use GPU cards from different nodes as much as possible, e.g.:
   - node2: GPU having 4 GPU device
 
 - request:
-  - pod1: User 1 GPU
-  - pod2: User 1 GPU
+  - pod1: Use 1 GPU
+  - pod2: Use 1 GPU
 
 - scheduler result:
-  - pod1: scheduler to node1
-  - pod2: scheduler to node2
+  - pod1: scheduled to node1
+  - pod2: scheduled to node2
 
 #### Story 3
 
@@ -57,12 +57,12 @@ GPU binpack, use the same GPU card as much as possible, e.g.:
   - node1: GPU having 4 GPU device, they are GPU1,GPU2,GPU3,GPU4
 
 - request:
-  - pod1: User 1 GPU, gpucore is 20%, gpumem-percentage is 20%
-  - pod2: User 1 GPU, gpucore is 20%, gpumem-percentage is 20%
+  - pod1: Use 1 GPU, gpucore is 20%, gpumem-percentage is 20%
+  - pod2: Use 1 GPU, gpucore is 20%, gpumem-percentage is 20%
 
 - scheduler result:
-  - pod1: scheduler to node1, select GPU1 this device
-  - pod2: scheduler to node1, select GPU1 this device
+  - pod1: scheduled to node1, select GPU1
+  - pod2: scheduled to node1, select GPU1
 
 #### Story 4
 
@@ -72,12 +72,12 @@ GPU spread, use different GPU cards when possible, e.g.:
   - node1: GPU having 4 GPU device, they are GPU1,GPU2,GPU3,GPU4
 
 - request:
-  - pod1: User 1 GPU, gpucore is 20%, gpumem-percentage is 20%
-  - pod2: User 1 GPU, gpucore is 20%, gpumem-percentage is 20%
+  - pod1: Use 1 GPU, gpucore is 20%, gpumem-percentage is 20%
+  - pod2: Use 1 GPU, gpucore is 20%, gpumem-percentage is 20%
 
 - scheduler result:
-  - pod1: scheduler to node1, select GPU1 this device
-  - pod2: scheduler to node1, select GPU2 this device
+  - pod1: scheduled to node1, select GPU1
+  - pod2: scheduled to node1, select GPU2
 
 ## Design Details
 

docs/installation/how-to-use-volcano-vgpu.md

@@ -95,7 +95,7 @@ status:
 
 ### Running vGPU Jobs
 
-vGPU can be requested by both set "volcano.sh/vgpu-number", "volcano.sh/vgpu-cores" and "volcano.sh/vgpu-memory" in resources.limits.
+vGPU can be requested by setting `volcano.sh/vgpu-number`, `volcano.sh/vgpu-cores` and `volcano.sh/vgpu-memory` in `resources.limits`.
 
 ```shell
 cat <<EOF | kubectl apply -f -

docs/userguide/awsneuron-device/examples/allocate-neuron-device.md

@@ -1,5 +1,5 @@
 ---
-title: Allocate AWS Neuron core
+title: Allocate AWS Neuron device
 ---
 
 To allocate one or more AWS Neuron devices exclusively, use `aws.amazon.com/neuron`

docs/userguide/iluvatar-device/examples/allocate-exclusive-mr-v100.md

@@ -1,8 +1,8 @@
 ---
-title: Allocate exclusive BI-V100 device
+title: Allocate exclusive MR-V100 device
 ---
 
-To allocate multiple BI-V100 devices, you only need to assign `iluvatar.ai/BI-V150-vgpu` with no other fields required.
+To allocate multiple MR-V100 devices, you only need to assign `iluvatar.ai/MR-V100-vgpu` with no other fields required.
 
 ```yaml
 apiVersion: v1

docs/userguide/kunlunxin-device/enable-kunlunxin-vxpu.md

@@ -155,7 +155,7 @@ spec:
       resources:
         limits:
           kunlunxin.com/vxpu: 1 # requesting a VXPU
-          kunlunxin.com/vxpu-memory: 24576 # requesting a virtual XPU that requires 24576 MiB of device memorymemory
+          kunlunxin.com/vxpu-memory: 24576 # requesting a virtual XPU that requires 24576 MiB of device memory
 ```
 
 ## Device UUID Selection

docs/userguide/mthreads-device/examples/allocate-core-and-memory.md

@@ -2,7 +2,7 @@
 title: Allocate device core and memory resource
 ---
 
-To allocate a certain part of device core resource, you need only to assign the `mthreads.com/sgpu-memory` and `mthreads.com/sgpu-core` along with the number of Cambricon MLUs you requested in the container using `mthreads.com/vgpu`.
+To allocate a certain part of device core resource, you need only to assign the `mthreads.com/sgpu-memory` and `mthreads.com/sgpu-core` along with the number of Mthreads GPUs you requested in the container using `mthreads.com/vgpu`.
 
 ```yaml
 apiVersion: v1

docs/userguide/mthreads-device/examples/allocate-exclusive.md

@@ -2,7 +2,7 @@
 title: Allocate exclusive device
 ---
 
-To allocate a whole cambricon device, you need to only assign `mthreads.com/vgpu` without other fields. You can allocate multiple GPUs for a container.
+To allocate a whole Mthreads device, you need to only assign `mthreads.com/vgpu` without other fields. You can allocate multiple GPUs for a container.
 
 ```yaml
 apiVersion: v1

docs/userguide/mthreads-device/specify-device-core-usage.md

@@ -4,7 +4,7 @@ linktitle: Allocate device core usage
 ---
 
 Allocate a part of device core resources by specifying resource `mthreads.com/sgpu-core`.
-Optional, each unit of `mthreads.com/smlu-core` equals 1/16 of device cores.
+Optional, each unit of `mthreads.com/sgpu-core` equals 1/16 of device cores.
 
 ```yaml
       resources:

docs/userguide/volcano-vgpu/nvidia-gpu/examples/default-use.md

@@ -2,7 +2,7 @@
 title: Default vGPU Job
 ---
 
-vGPU can be requested by both set "volcano.sh/vgpu-number", "volcano.sh/vgpu-cores" and "volcano.sh/vgpu-memory" in resources.limits
+vGPU can be requested by setting `volcano.sh/vgpu-number`, `volcano.sh/vgpu-cores` and `volcano.sh/vgpu-memory` in `resources.limits`
 
 ```yaml
 apiVersion: v1