docs: added pre-requisite for GPU and CUDA (#340)

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# Summary
Added language to enhance pre-requisite for GPU and CUDA and warning for
macOS users.

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Ensure that the following pass:

- [ ] `make format && make check` or via prek validation.
- [ ] `make test` passes locally
- [ ] `make test-e2e` passes locally
- [ ] `make test-ci-container` passes locally (recommended)
- [ ] GPU CI status check passes -- comment `/sync` on this PR to
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## Pre-Merge Checklist

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- [ ] New or updated tests for any fix or new behavior
- [ ] Updated documentation for new features and behaviors, including
docstrings for API docs.

## Other Notes

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- Closes #<issue>

---------

Signed-off-by: Sean Yang <seayang@nvidia.com>
Signed-off-by: seayang-nv <seayang@nvidia.com>
Co-authored-by: Kendrick Boyd <kendrickb@nvidia.com>

Author: seayang-nv

README.md

@@ -8,9 +8,10 @@ Read detailed usage below, or jump to the documentation with [Getting Started](h
 
 ### Prerequisites
 
-- Python 3.11–3.13 (we pin a specific 3.11.x in `.python-version` for local/dev bootstrap; any 3.11, 3.12, or 3.13 interpreter works. Python 3.14+ is **not** supported because ray, a transitive dependency of vLLM, does not yet publish `cp314` wheels)
+- Python 3.11–3.13 (we pin a specific 3.11.x in `.python-version` for local/dev bootstrap; any 3.11, 3.12, or 3.13 interpreter works. Python 3.14+ is NOT supported because ray, a transitive dependency of vLLM, does not yet publish `cp314` wheels)
 - [uv](https://docs.astral.sh/uv/) - Python package manager (>=0.9.14, <0.11.0)
 - NVIDIA GPU (A100 or larger) for training and generation
+- Linux only -- macOS, Windows, and Apple Silicon are not supported for training or generation. A CPU-only install is available for development and configuration validation.
 
 ### Installation
 

docs/index.md

@@ -17,6 +17,9 @@ NeMo Safe Synthesizer creates private, safe versions of sensitive tabular datase
 - Comprehensive evaluation -- Privacy and quality metrics in an in-depth HTML report
 - Flexible interfaces -- CLI for scripting, Python SDK for programmatic workflows, YAML configuration
 
+!!! info "System Requirements"
+    NeMo Safe Synthesizer requires a Linux machine with an NVIDIA GPU (A100 80GB+ recommended) and CUDA 12.8+ to run the training and generation pipeline. macOS, Windows, and Apple Silicon are not supported for pipeline execution. A CPU-only install is available for development and configuration validation -- see [Getting Started](user-guide/getting-started.md#install-the-package).
+
 ## Next Steps
 
 <div class="grid cards" markdown>

docs/tutorials/differential-privacy.ipynb

@@ -14,7 +14,7 @@
         "\n",
         "### 🖥️ Prerequisites\n",
         "\n",
-        "This notebook requires a GPU. We recommend an H100; minimum A100."
+        "This notebook requires a Linux machine with an NVIDIA GPU (H100 recommended, A100 minimum) and CUDA 12.8+. It will not run on macOS, Windows, or Apple Silicon."
       ]
     },
     {

docs/tutorials/safe-synthesizer-101.ipynb

@@ -16,7 +16,7 @@
         "\n",
         "### 🖥️ Prerequisites\n",
         "\n",
-        "This notebook requires a GPU. We recommend an H100; minimum A100."
+        "This notebook requires a Linux machine with an NVIDIA GPU (H100 recommended, A100 minimum) and CUDA 12.8+. It will not run on macOS, Windows, or Apple Silicon."
       ]
     },
     {

docs/user-guide/getting-started.md

@@ -15,9 +15,15 @@ does at each stage.
 ### Prerequisites
 
 - Python 3.11–3.13 (dev tooling currently pins 3.11 via `.python-version` in the repo root; Python 3.14+ is **not** supported — see [Troubleshooting](troubleshooting.md#python-314-is-not-supported))
-- CUDA runtime 12.8
+- CUDA runtime 12.8+
 - NVIDIA GPU (A100 or larger) for training and generation
 
+!!! failure "Linux only -- macOS, Windows, and Apple Silicon are not supported"
+    NeMo Safe Synthesizer requires a Linux machine with an NVIDIA GPU and CUDA 12.8+
+    to run the training and generation pipeline. The [CPU install tab below](#install-the-package)
+    is for development and configuration validation only -- it cannot train models or
+    generate synthetic data.
+
 ### Install the Package
 
 The CUDA and CPU extras depend on packages (PyTorch, FlashInfer) hosted on