Revert CUDA 12 SOCP install path

Author: jgoldberg-nvidia

README.md

@@ -95,10 +95,10 @@ source $HOME/.local/bin/env  # (sh, bash, zsh)
 # source $HOME/.local/bin/env.fish  # (fish)
 
 # Install with CUDA-specific dependencies
-uv sync --extra cuda12 # required for the cuOpt SOCP/QCQP preview until CUDA 13 26.8 wheels are published
+uv sync --extra cuda13 # this container image has cuda13
 
 # Optional: Install development tools
-uv sync --extra cuda12 --extra dev
+uv sync --extra cuda13 --extra dev
 
 # Create a Jupyter kernel for this environment
 uv run python -m ipykernel install --user --name=portfolio-opt --display-name "Portfolio Optimization"
@@ -107,13 +107,13 @@ uv run python -m ipykernel install --user --name=portfolio-opt --display-name "P
 uv run jupyter lab --no-browser --NotebookApp.token=''
 ```
 
-**Note:** The SOCP/QCQP demo currently needs the `cuda12` extra because the CUDA 13 cuML/cuOpt 26.8 wheels are not published yet. The `cuda13` extra remains available for non-SOCP GPU workflows on the latest published CUDA 13 cuML/cuOpt packages. The `uv sync` command automatically creates a virtual environment and installs all dependencies from `uv.lock`.
+**Note:** If you use a different container image than the suggested one above, during uv sync, please use the `--extra cuda12` or `--extra cuda13` flag to install the GPU packages (cuOpt, cuML) matching your container's CUDA version. The `uv sync` command automatically creates a virtual environment and installs all dependencies from `uv.lock`.
 
 **Tip:** To check your CUDA version, run `nvidia-smi` and look for "CUDA Version" in the output.
 
 **Important Notes:**
 - If you encounter "No space left on device" errors, set `UV_CACHE_DIR` to an alternate cache location: `export UV_CACHE_DIR=/path/to/cache/directory`
-- The `cuda12` and `cuda13` extras are mutually exclusive; use `cuda12` for the SOCP/QCQP preview until CUDA 13 26.8 wheels are published
+- The `cuda12` and `cuda13` extras are mutually exclusive - install only one based on your system's CUDA version
 - If you plan to run the Streamlit demo from this container, include `-p 8501:8501` when starting Docker. Docker port mappings cannot be added to an already-running container; restart the container with the port published if it was omitted.
 
 #### Using the Jupyter Kernel

demo/README_streamlit.md

@@ -21,7 +21,7 @@ Use `uv` for the current cuFOLIO dependency set:
 
 ```bash
 # From the repository root
-uv sync --extra cuda12        # required for SOCP/QCQP preview today
+uv sync --extra cuda13        # or: uv sync --extra cuda12
 uv pip install -r demo/requirements.txt
 uv run python -c 'from cufolio.utils import download_data; download_data("data/stock_data", datasets=["sp500"])'
 uv run streamlit run demo/rebalancing_streamlit_app.py --server.address 0.0.0.0 --server.port 8501
@@ -32,7 +32,7 @@ For a standard virtual environment:
 ```bash
 python3 -m venv .venv
 source .venv/bin/activate
-pip install -e ".[cuda12]"       # required for SOCP/QCQP preview today
+pip install -e ".[cuda13]"       # or .[cuda12], or plain -e . for CPU-only setup
 pip install -r demo/requirements.txt
 python -c 'from cufolio.utils import download_data; download_data("data/stock_data", datasets=["sp500"])'
 streamlit run demo/rebalancing_streamlit_app.py --server.address 0.0.0.0 --server.port 8501
@@ -45,7 +45,7 @@ Open `http://localhost:8501` for local runs. On a remote GPU instance, forward o
 - Python 3.11+
 - Streamlit, Plotly, and Squarify from `demo/requirements.txt`
 - CVXPY and cuFOLIO core dependencies from `pyproject.toml`
-- Optional: NVIDIA GPU + `cuda12` extra for the cuOpt SOCP/QCQP preview; `cuda13` uses the latest published CUDA 13 packages but does not carry the 26.8 SOCP package line yet
+- Optional: NVIDIA GPU + CUDA with the matching `cuda12` or `cuda13` extra for cuOpt acceleration
 
 ## Troubleshooting
 
@@ -57,4 +57,4 @@ Open `http://localhost:8501` for local runs. On a remote GPU instance, forward o
 uv run python -c 'from cufolio.utils import download_data; download_data("data/stock_data", datasets=["sp500"])'
 ```
 
-**GPU Solver Unavailable**: The UI can still boot without a GPU, but the full GTC comparison and SOCP preview need cuOpt. Install the `cuda12` extra for the SOCP/QCQP preview and run on an NVIDIA GPU instance.
+**GPU Solver Unavailable**: The UI can still boot without a GPU, but the full GTC comparison and SOCP preview need cuOpt. Install the matching CUDA extra and run on an NVIDIA GPU instance.

pyproject.toml

@@ -25,8 +25,8 @@ cuda12 = [
     "cuopt-cu12==26.8.*",
 ]
 cuda13 = [
-    "cuml-cu13==26.4.*",
-    "cuopt-cu13==26.4.*",
+    "cuml-cu13==26.8.*",
+    "cuopt-cu13==26.8.*",
 ]
 
 [tool.ruff]