[Blog] Using SSH fleets with TensorWave's private AMD cloud

docs/assets/stylesheets/landing.css

@@ -386,7 +386,7 @@
 }
 
 .providers.tx-landing__highlights_grid {
-    grid-gap: 28px !important;
+    grid-gap: 20px !important;
 }
 
 #typed {
@@ -397,15 +397,22 @@
 
 .providers.tx-landing__highlights_grid .feature-cell h3 {
     align-content: center;
-    font-size: 1.1em;
+    font-size: 1em;
     font-weight: 600;
     padding-bottom: 0.05em;
     line-height: 25px;
 }
 
 .providers.tx-landing__highlights_grid .feature-cell {
-    row-gap: 18px;
-    padding: 26px 39px;
+    row-gap: 22px;
+    padding: 25px 30px;
+    aspect-ratio: 1.05;
+
+    @media screen and (min-width: 76.1875em) {
+        &:nth-child(1) {
+            border-top-left-radius: 3px;
+        }
+    }
 }
 
 .tx-landing__highlights_grid .feature-cell {
@@ -418,6 +425,54 @@
     flex-direction: column;
 }
 
+@media screen and (min-width: 76.1875em) {
+    .providers.tx-landing__highlights_grid .feature-cell {
+        border-radius: 0;
+        border-left: none;
+        border-bottom: none;
+    }
+
+    .nvidia.providers.tx-landing__highlights_grid .feature-cell {
+        &:nth-child(1), &:nth-child(6), &:nth-child(11) {
+            border-left: 0.5px dotted rgba(0, 0, 0, 0.75);
+        }
+
+        &:nth-child(n+7) {
+            border-bottom: 0.5px dotted rgba(0, 0, 0, 0.75);
+        }
+
+        &:nth-child(5) {
+            border-top-right-radius: 3px;
+        }
+
+        &:nth-child(5), &:nth-child(11) {
+            border-bottom-right-radius: 3px;
+        }
+
+        &:nth-child(11) {
+            border-bottom-left-radius: 3px;
+        }
+
+        &:nth-child(10) {
+            border-bottom-right-radius: 3px;
+        }
+    }
+}
+
+:is(.amd).providers.tx-landing__highlights_grid .feature-cell {
+    &:nth-child(1) {
+        border-left: 0.5px dotted rgba(0, 0, 0, 0.75);
+        border-bottom-left-radius: 3px;
+    }
+
+    border-bottom: 0.5px dotted rgba(0, 0, 0, 0.75);
+
+    &:nth-child(3) {
+        border-top-right-radius: 3px;
+        border-bottom-right-radius: 3px;
+    }
+}
+
 .providers.tx-landing__highlights_grid.other .feature-cell {
     column-gap: 15px;
     flex-direction: row;
@@ -436,6 +491,13 @@
         grid-template-columns: repeat(4, 1fr) !important;
     }
 
+    .providers.tx-landing__highlights_grid {
+        grid-gap: 0px !important;
+        border: none;
+
+        grid-template-columns: repeat(5, 1fr) !important;
+    }
+
     .tx-landing__highlights_grid .feature-cell {
     }
 }
@@ -444,9 +506,9 @@
     background: -webkit-linear-gradient(45deg, rgba(0, 42, 255, 0.005), rgba(0, 42, 255, 0.005), rgba(225, 101, 254, 0.01));
 }
 
-.tx-landing__highlights_grid .feature-cell:hover {
+/*.tx-landing__highlights_grid .feature-cell:hover {
     background: -webkit-linear-gradient(45deg, rgba(0, 42, 255, 0.03), rgba(0, 42, 255, 0.03), rgba(225, 101, 254, 0.05));
-}
+}*/
 
 .tx-landing__highlights_grid .feature-cell strong {
     font-weight: 500;

docs/blog/posts/amd-on-tensorwave.md

@@ -0,0 +1,243 @@
+---
+title: Using SSH fleets with TensorWave's private AMD cloud
+date: 2025-03-11
+description: "This tutorial walks you through how dstack can be used with TensorWave's private AMD cloud using SSH fleets."  
+slug: amd-on-tensorwave
+image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-tensorwave-v2.png?raw=true
+categories:
+  - Fleets
+  - AMD
+  - Private clouds
+---
+
+# Using SSH fleets with TensorWave's private AMD cloud 
+
+Since last month, when we introduced support for private clouds and data centers, it has become easier to use `dstack`
+to orchestrate AI containers with any AI cloud vendor, whether they provide on-demand compute or reserved clusters.
+
+In this tutorial, we’ll walk you through how `dstack` can be used with
+[TensorWave :material-arrow-top-right-thin:{ .external }](https://tensorwave.com/){:target="_blank"} using 
+[SSH fleets](../../docs/concepts/fleets.md#ssh).
+
+<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-tensorwave-v2.png?raw=true" width="630"/>
+
+<!-- more -->
+
+TensorWave is a cloud provider specializing in large-scale AMD GPU clusters for both
+training and inference.
+
+Before following this tutorial, ensure you have access to a cluster. You’ll see the cluster and its nodes in your
+TensorWave dashboard.
+
+<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-tensorwave-ui.png?raw=true" width="750"/>
+
+## Creating a fleet
+
+??? info "Prerequisites"
+    Once `dstack` is [installed](https://dstack.ai/docs/installation), create a project repo folder and run `dstack init`.
+
+    <div class="termy">
+
+    ```shell
+    $ mkdir tensorwave-demo && cd tensorwave-demo
+    $ dstack init
+    ```
+
+    </div>
+
+Now, define an SSH fleet configuration by listing the IP addresses of each node in the cluster, 
+along with the SSH user and SSH key configured for each host.
+
+<div editor-title="fleet.dstack.yml">
+
+```yaml
+type: fleet
+name: my-tensorwave-fleet
+
+placement: cluster
+
+ssh_config:
+  user: dstack
+  identity_file: ~/.ssh/id_rsa
+  hosts:
+    - hostname: 64.139.222.107
+      blocks: auto
+    - hostname: 64.139.222.108
+      blocks: auto
+```
+
+</div>
+
+You can set `blocks` to `auto` if you want to run concurrent workloads on each instance.
+Otherwise, you can omit this property.
+
+Once the configuration is ready, apply it using `dstack apply`:
+
+<div class="termy">
+
+```shell
+$ dstack apply -f fleet.dstack.yml
+
+Provisioning...
+---> 100%
+
+ FLEET                INSTANCE  RESOURCES         STATUS     CREATED 
+ my-tensorwave-fleet  0         8xMI300X (192GB)  0/8 busy   3 mins ago      
+                      1         8xMI300X (192GB)  0/8 busy   3 mins ago    
+
+```
+
+</div>
+
+`dstack` will automatically connect to each host, detect the hardware, install dependencies, and make them ready for
+workloads.
+
+## Running workloads
+
+Once the fleet is created, you can use `dstack` to run workloads.
+
+### Dev environments
+
+A dev environment lets you access an instance through your desktop IDE.
+
+<div editor-title=".dstack.yml"> 
+
+```yaml
+type: dev-environment
+name: vscode
+
+image: rocm/pytorch:rocm6.3.3_ubuntu22.04_py3.10_pytorch_release_2.4.0
+ide: vscode
+
+resources:
+  gpu: MI300X:8
+```
+
+</div>
+
+Apply the configuration via [`dstack apply`](../../docs/reference/cli/dstack/apply.md):
+
+<div class="termy">
+
+```shell
+$ dstack apply -f .dstack.yml
+
+Submit the run `vscode`? [y/n]: y
+
+Launching `vscode`...
+---> 100%
+
+To open in VS Code Desktop, use this link:
+  vscode://vscode-remote/ssh-remote+vscode/workflow
+```
+
+</div>
+
+Open the link to access the dev environment using your desktop IDE.
+
+### Tasks
+
+A task allows you to schedule a job or run a web app. Tasks can be distributed and support port forwarding.
+
+Below is a distributed training task configuration: 
+
+<div editor-title="train.dstack.yml"> 
+
+```yaml
+type: task
+name: train-distrib
+
+nodes: 2
+
+image: rocm/pytorch:rocm6.3.3_ubuntu22.04_py3.10_pytorch_release_2.4.0
+commands:
+  - pip install torch
+  - export NCCL_IB_GID_INDEX=3
+  - export NCCL_NET_GDR_LEVEL=0
+  - torchrun --nproc_per_node=8 --nnodes=2 --node_rank=$DSTACK_NODE_RANK --master_port=29600 --master_addr=$DSTACK_MASTER_NODE_IP test/tensorwave/multinode.py 5000 50
+
+resources:
+  gpu: MI300X:8
+```
+
+</div>
+
+Run the configuration via [`dstack apply`](../../docs/reference/cli/dstack/apply.md):
+
+<div class="termy">
+
+```shell
+$ dstack apply -f train.dstack.yml
+
+Submit the run `streamlit`? [y/n]: y
+
+Provisioning `train-distrib`...
+---> 100%
+```
+
+</div>
+
+`dstack` automatically runs the container on each node while passing 
+[system environment variables](../../docs/concepts/tasks.md#system-environment-variables)
+which you can use with `torchrun`, `accelerate`, or other distributed frameworks.
+
+### Services
+
+A service allows you to deploy a model or any web app as a scalable and secure endpoint.
+
+Create the following configuration file inside the repo:
+
+<div editor-title="deepseek.dstack.yml"> 
+
+```yaml
+type: service
+name: deepseek-r1-sglang
+
+image: rocm/sglang-staging:20250212
+env:
+  - MODEL_ID=deepseek-ai/DeepSeek-R1
+  - HSA_NO_SCRATCH_RECLAIM=1
+commands:
+  - python3 -m sglang.launch_server --model-path $MODEL_ID --port 8000 --tp 8 --trust-remote-code 
+port: 8000
+model: deepseek-ai/DeepSeek-R1
+
+resources:
+  gpu: mi300x:8
+
+volumes:
+  - /root/.cache/huggingface:/root/.cache/huggingface
+```
+
+</div>
+
+Run the configuration via [`dstack apply`](../../docs/reference/cli/dstack/apply.md):
+
+<div class="termy">
+
+```shell
+$ dstack apply -f deepseek.dstack.yml
+
+Submit the run `deepseek-r1-sglang`? [y/n]: y
+
+Provisioning `deepseek-r1-sglang`...
+---> 100%
+
+Service is published at: 
+  http://localhost:3000/proxy/services/main/deepseek-r1-sglang/
+Model deepseek-ai/DeepSeek-R1 is published at:
+  http://localhost:3000/proxy/models/main/
+```
+
+</div>
+
+## See it in action
+
+Want to see how it works? Check out the video below:
+
+<iframe width="750" height="520" src="https://www.youtube.com/embed/b1vAgm5fCfE?si=qw2gYHkMjERohdad&rel=0" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
+
+!!! info "What's next?"
+    1. See [SSH fleets](../../docs/concepts/fleets.md#ssh) 
+    2. Read about [dev environments](../../docs/concepts/dev-environments.md), [tasks](../../docs/concepts/tasks.md), and [services](../../docs/concepts/services.md)
+    3. Join [Discord :material-arrow-top-right-thin:{ .external }](https://discord.gg/u8SmfwPpMd)

docs/overrides/main.html

@@ -132,7 +132,7 @@
                     <a href="https://discord.gg/u8SmfwPpMd" target="_blank" class="tx-footer__section-link external">Discord</a>
                     <a href="https://github.com/dstackai/dstack/" target="_blank" class="tx-footer__section-link external">GitHub</a>
                     <a href="https://github.com/dstackai/dstack/blob/master/CONTRIBUTING.md" target="_blank" class="tx-footer__section-link external">Contributing</a>
-                    <a href="/developers#ambassador-program" class="tx-footer__section-link">Ambassador program</a>
+                    <!--<a href="/developers#ambassador-program" class="tx-footer__section-link">Ambassador program</a>-->
                 </div>
 
                 <div class="tx-footer__section">