[Docs] Removed name from Node groups examples; plus few minor edits

mkdocs/docs/concepts/tasks.md

@@ -223,10 +223,10 @@ the index of the node within that group.
 
 Currently, only `resources`, `commands`, and `ports` can be configured per node group. [`groups`](../reference/dstack.yml/task.md#groups) and top-level `nodes` are mutually exclusive.Support for other properties is coming soon.
 
-??? info "Prefill/decode example"
-    Node groups can mix CPU and GPU roles. This SGLang prefill/decode split uses a CPU
+??? info "PD disaggregation"
+    While PD disaggregaton is mostly used with [services](services.md#pd-disaggregation), it also possible to run it as tasks. The example below runs  a CPU
     router (`groups[0]`, the master) and GPU workers. `startup_order: workers-first`
-    starts prefill and decode before the router.
+    instructs `dstack` to start prefill and decode workers before the router.
 
     <div editor-title=".dstack.yml">
 
@@ -241,8 +241,7 @@ Currently, only `resources`, `commands`, and `ports` can be configured per node
     startup_order: workers-first
     groups:
       # Router (CPU) — master node; wires prefill + decode by IP
-      - name: router
-        nodes: 1
+      - nodes: 1
         commands:
           - pip install smg
           - |
@@ -259,8 +258,7 @@ Currently, only `resources`, `commands`, and `ports` can be configured per node
         resources:
           cpu: 4
 
-      - name: prefill
-        nodes: 1
+      - nodes: 1
         commands:
           - |
             python -m sglang.launch_server \
@@ -272,8 +270,7 @@ Currently, only `resources`, `commands`, and `ports` can be configured per node
         resources:
           gpu: H200
 
-      - name: decode
-        nodes: 1
+      - nodes: 1
         commands:
           - |
             python -m sglang.launch_server \
@@ -287,9 +284,8 @@ Currently, only `resources`, `commands`, and `ports` can be configured per node
 
     </div>
 
-!!! info "Examples"
-    See the [Ray+RAGEN](../examples/training/ray-ragen.md) example for running a Ray cluster,
-    and the [NCCL/RCCL tests](../examples/clusters/nccl-rccl-tests.md) example for running `mpirun` with node groups.
+> See the [Ray+RAGEN](../examples/training/ray-ragen.md) example for running a Ray cluster,
+and the [NCCL/RCCL tests](../examples/clusters/nccl-rccl-tests.md) example for running `mpirun` with node groups.
 
 ### Resources
 

mkdocs/docs/examples/clusters/nccl-rccl-tests.md

@@ -29,8 +29,7 @@ Here's an example of a task that runs AllReduce test on 2 nodes, each with 4 GPU
       - NCCL_DEBUG=INFO
 
     groups:
-      - name: master # The name property is optional
-        nodes: 1
+      - nodes: 1
         commands:
           - |
             mpirun \
@@ -44,8 +43,7 @@ Here's an example of a task that runs AllReduce test on 2 nodes, each with 4 GPU
           gpu: nvidia:1..8
           shm_size: 16GB
 
-      - name: workers
-        nodes: 1
+      - nodes: 1
         commands:
           - sleep infinity
         resources:
@@ -83,8 +81,7 @@ Here's an example of a task that runs AllReduce test on 2 nodes, each with 4 GPU
       - OPEN_MPI_HOME=/usr/lib/x86_64-linux-gnu/openmpi
 
     groups:
-      - name: master # The name property is optional
-        nodes: 1
+      - nodes: 1
         commands:
           # Setup MPI and build RCCL tests
           - apt-get install -y git libopenmpi-dev openmpi-bin
@@ -110,8 +107,7 @@ Here's an example of a task that runs AllReduce test on 2 nodes, each with 4 GPU
         resources:
           gpu: MI300X:8
 
-      - name: workers
-        nodes: 1
+      - nodes: 1
         commands:
           # Setup MPI and build RCCL tests
           - apt-get install -y git libopenmpi-dev openmpi-bin

mkdocs/docs/examples/training/ray-ragen.md

@@ -30,8 +30,7 @@ env:
   - WANDB_API_KEY
 
 groups:
-  - name: head # The name property is optional
-    nodes: 1
+  - nodes: 1
     commands:
       - wget -O miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
       - bash miniconda.sh -b -p /workflow/miniconda
@@ -52,8 +51,7 @@ groups:
       gpu: 80GB:8
       shm_size: 128GB
 
-  - name: workers
-    nodes: 1
+  - nodes: 1
     commands:
       - wget -O miniconda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
       - bash miniconda.sh -b -p /workflow/miniconda