docs: initial tooling for container matrices

* Use Alberto's workstation for bandwidth. * Extract the broad swath of data from the NGC containers. * List container size in GB. Yay! * Create RST tables from the data. * Create one page for each container.
NVIDIA-Merlin · Apr 3, 2022 · 94f230c · 94f230c
1 parent 186b214
commit 94f230c
Show file tree

Hide file tree

Showing 17 changed files with 653 additions and 14 deletions.
diff --git a/docs/README.md b/docs/README.md
@@ -2,7 +2,7 @@
 
 This folder contains the scripts necessary to build the repository
 documentation. You can view the documentation at
-<https://nvidia-merlin.github.io/Merlin/main/Introduction.html>.
+<https://nvidia-merlin.github.io/Merlin/main/README.html>.
 
 ## Contributing to Docs
 

diff --git a/docs/requirements-doc.txt b/docs/requirements-doc.txt
@@ -10,6 +10,9 @@ sphinx-multiversion
 recommonmark>=0.6
 nbsphinx>=0.6
 
+# smx
+mergedeep==1.3.4
+
 # packages necessary to run tests and push PRs
 # assumes requirements for nvtabular logic are already installed
 

diff --git a/docs/source/containers.rst b/docs/source/containers.rst
@@ -4,33 +4,53 @@ Merlin Containers
 Merlin and the Merlin component libraries are available in Docker containers from the NVIDIA GPU Cloud (NCG) catalog.
 Access the catalog of containers at http://ngc.nvidia.com/catalog/containers.
 
+Training Containers
+--------------------
+
 The following table identifies the container names, catalog URL, and key Merlin components.
 
 .. list-table::
    :widths: 25 50 25
    :header-rows: 1
 
-   * - Container Name
+   * - Training Container
      - NGC Catalog URL
      - Key Merlin Components
-   * - merlin-tensorflow-inference
-     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow-inference
-     - NVTabular, Tensorflow, and Triton Inference Server
-   * - merlin-pytorch-inference
-     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-pytorch-inference
-     - NVTabular, PyTorch, and Triton Inference Server
-   * - merlin-inference
-     - https://ngc.nvidia.com/catalog/containers/nvidia:merlin:merlin-inference
-     - NVTabular, HugeCTR, and Triton Inference Server
    * - merlin-training
-     - https://ngc.nvidia.com/catalog/containers/nvidia:merlin:merlin-training
+     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-training
      - NVTabular and HugeCTR
    * - merlin-tensorflow-training
-     - https://ngc.nvidia.com/catalog/containers/nvidia:merlin:merlin-tensorflow-training
+     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow-training
      - NVTabular, TensorFlow, and HugeCTR Tensorflow Embedding plugin
    * - merlin-pytorch-training
-     - https://ngc.nvidia.com/catalog/containers/nvidia:merlin:merlin-pytorch-training
+     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-pytorch-training
      - NVTabular and PyTorch
 
 To use these containers, you must install the `NVIDIA Container Toolkit <https://github.com/NVIDIA/nvidia-docker>`_ to provide GPU support for Docker.
 You can use the NGC links referenced in the preceding table for more information about how to launch and run these containers.
+
+
+Inference Containers
+--------------------
+
+The following table identifies the container names, catalog URL, and key Merlin components.
+
+.. list-table::
+   :widths: 25 50 25
+   :header-rows: 1
+
+   * - Inference Container
+     - NGC Catalog URL
+     - Key Merlin Components
+   * - merlin-inference
+     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-inference
+     - NVTabular, HugeCTR, and Triton Inference Server
+   * - merlin-tensorflow-inference
+     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-tensorflow-inference
+     - NVTabular, Tensorflow, and Triton Inference Server
+   * - merlin-pytorch-inference
+     - https://catalog.ngc.nvidia.com/orgs/nvidia/teams/merlin/containers/merlin-pytorch-inference
+     - NVTabular, PyTorch, and Triton Inference Server
+
+To use these containers, you must install the `NVIDIA Container Toolkit <https://github.com/NVIDIA/nvidia-docker>`_ to provide GPU support for Docker.
+You can use the NGC links referenced in the preceding table for more information about how to launch and run these containers.
diff --git a/docs/source/generated/nvcr.io-nvidia-merlin-merlin-inference.rst b/docs/source/generated/nvcr.io-nvidia-merlin-merlin-inference.rst
diff --git a/docs/source/generated/nvcr.io-nvidia-merlin-merlin-pytorch-inference.rst b/docs/source/generated/nvcr.io-nvidia-merlin-merlin-pytorch-inference.rst
@@ -0,0 +1,94 @@
+.. table::
+   :align: left
+
+   ==============================  =================================================================================  
+   Container Release               Release 22.03                                                                      
+   ==============================  =================================================================================  
+   **DGX**                                                                                                          
+   -----------------------------------------------------------------------------------------------------------------
+   **DGX System**                  * DGX-1                                                                          
+
+                                   * DGX-2                                                                          
+
+                                   * DGX A100                                                                       
+
+                                   * DGX Station                                                                    
+
+   **Operating System**            Ubuntu 20.04.3 LTS                                                               
+
+   **NVIDIA Certified Systems**                                                                                     
+   -----------------------------------------------------------------------------------------------------------------
+   **NVIDIA Driver**               NVIDIA Driver version 465.19.01                                                  
+
+                                   or later is required.  However,                                                  
+
+                                   if you're running on Data Center                                                 
+
+                                   GPUs (formerly Tesla) such as T4,                                                
+
+                                   you can use any of the following                                                 
+
+                                   NVIDIA Driver versions:                                                          
+
+
+
+                                   * 418.40 (or later R418)                                                         
+
+                                   * 440.33 (or later R440)                                                         
+
+                                   * 450.51 (or later R450)                                                         
+
+                                   * 460.27 (or later R460)                                                         
+
+
+
+                                   **Note**: The CUDA Driver                                                        
+
+                                   Compatability Package does not                                                   
+
+                                   support all drivers.                                                             
+
+   **GPU Model**                   * `NVIDIA Ampere GPU Architecture <https://www.nvidia.com/en-us/geforce/turing>`_
+
+                                   * `Turing <https://www.nvidia.com/en-us/geforce/turing/>`_                       
+
+                                   * `Volta <https://www.nvidia.com/en-us/data-center/volta-gpu-architecture/>`_    
+
+                                   * `Pascal <https://www.nvidia.com/en-us/data-center/pascal-gpu-architecture/>`_  
+
+   **Base Container Image**                                                                                         
+   -----------------------------------------------------------------------------------------------------------------
+   **Container Operating System**  Ubuntu 20.04.3 LTS                                                               
+
+   **Base Container**              Triton version 22.02                                                             
+
+   **CUDA**                        11.6.0.021                                                                       
+
+   **RMM**                         21.12.00                                                                         
+
+   **cuDF**                        21.12.02                                                                         
+
+   **cuDNN**                       8.3.2.44+cuda11.5                                                                
+
+   **Merlin Core**                 v0.1.1+3.gee1d59d                                                                
+
+   **Merlin Models**               Not applicable                                                                   
+
+   **Merlin Systems**              Not applicable                                                                   
+
+   **NVTabular**                   0.11.0                                                                           
+
+   **Transformers4Rec**            0.1.6                                                                            
+
+   **HugeCTR**                     Not applicable                                                                   
+
+   **SM**                          Not applicable                                                                   
+
+   **PyTorch**                     Not applicable                                                                   
+
+   **Triton Inference Server**     2.19.0                                                                           
+
+   **Size**                        9.72 GB                                                                          
+
+   ==============================  =================================================================================  
+