Continue publishing fixes

.github/workflows/docker_images.yml

@@ -494,9 +494,7 @@ jobs:
 
           platform_tag=${{ needs.metadata.outputs.platform_tag }}
           cuda_major=`echo ${{ inputs.cuda_version }} | cut -d . -f1`
-          if [ "$cuda_major" == "11" ]; then
-            deprecation_notice="**Note**: Support for CUDA 11 will be removed in future releases. Please update to CUDA 12."
-          fi
+          deprecation_notice=""
           image_tag=${platform_tag:+$platform_tag-}${cuda_major:+cu${cuda_major}-}
           if ${{ github.event.pull_request.number != '' }} || [ -n "$(echo ${{ github.ref_name }} | grep pull-request/)" ]; then
             pr_number=`echo ${{ github.ref_name }} | grep -o [0-9]*`

.github/workflows/publishing.yml

@@ -964,24 +964,15 @@ jobs:
           dpkg -i cuda-keyring_1.1-1_all.deb
           cuda_version_suffix="$(echo ${{ matrix.cuda_version }} | tr . -)"
           apt-get update
-          if [ $(echo ${{ matrix.cuda_version }} | cut -d . -f1) -gt 11 ]; then
-            apt-get install -y --no-install-recommends \
-            cuda-cudart-$cuda_version_suffix \
-            cuda-nvrtc-$cuda_version_suffix \
-            libnvjitlink-$cuda_version_suffix \
-            libcurand-$cuda_version_suffix \
-            libcublas-$cuda_version_suffix \
-            libcusparse-$cuda_version_suffix \
-            libcusolver-$cuda_version_suffix
-          else
-            apt-get install -y --no-install-recommends \
-            cuda-cudart-$cuda_version_suffix \
-            cuda-nvrtc-$cuda_version_suffix \
-            libcurand-$cuda_version_suffix \
-            libcublas-$cuda_version_suffix \
-            libcusparse-$cuda_version_suffix \
-            libcusolver-$cuda_version_suffix
-          fi
+          apt-get install -y --no-install-recommends \
+          cuda-cudart-$cuda_version_suffix \
+          cuda-cudart-dev-$cuda_version_suffix \
+          cuda-nvrtc-$cuda_version_suffix \
+          libnvjitlink-$cuda_version_suffix \
+          libcurand-$cuda_version_suffix \
+          libcublas-$cuda_version_suffix \
+          libcusparse-$cuda_version_suffix \
+          libcusolver-$cuda_version_suffix
 
       - name: Runtime dependencies (dnf)
         if: startsWith(matrix.os_image, 'redhat')
@@ -1048,7 +1039,7 @@ jobs:
     strategy:
       matrix:
         platform: ['amd64-gpu-a100', 'arm64-gpu-a100']
-        cuda_major: ['', '11', '12']
+        cuda_major: ['', '12', '13']
       fail-fast: false
 
     runs-on: linux-${{ matrix.platform }}-latest-1
@@ -1086,20 +1077,22 @@ jobs:
           # These simple steps are only expected to work for
           # test cases that don't require MPI.
           # Create clean python3 environment.
-          apt-get update && apt-get install -y --no-install-recommends python3 python3-pip
-          mkdir -p /tmp/packages && mv /tmp/wheels/* /tmp/packages && rmdir /tmp/wheels
+          apt-get update && apt-get install -y --no-install-recommends python3 python3-pip python3-venv
 
-          python3 -m pip install pypiserver
-          server=`find / -name pypi-server -executable -type f`
-          $server run -p 8080 /tmp/packages & 
+          # Make a place for local wheels
+          mkdir -p /tmp/packages && mv /tmp/wheels/* /tmp/packages && rmdir /tmp/wheels
 
+          # Create and activate virtual environment
+          python3 -m venv /opt/cudaq-venv
+          source /opt/cudaq-venv/bin/activate
+
           if [ -n "${{ matrix.cuda_major }}" ]; then
             pip install cuda-quantum-cu${{ matrix.cuda_major }}==${{ needs.assets.outputs.cudaq_version }} -v \
-              --extra-index-url http://localhost:8080 
+              --find-links "file:///tmp/packages"
           else
             pip install --upgrade pip
             pip install cudaq==${{ needs.assets.outputs.cudaq_version }} -v \
-              --extra-index-url http://localhost:8080 \
+              --find-links "file:///tmp/packages" \
             2>&1 | tee /tmp/install.out
 
             if [ -z "$(cat /tmp/install.out | grep -o 'Autodetection succeeded')" ]; then 

.github/workflows/python_metapackages.yml

@@ -60,7 +60,7 @@ jobs:
             package_name=cudaq
             cuda_version_requirement="12.x or 13.x"
             cuda_version_conda=12.4.0 # only used as example in the install script
-            deprecation_notice="**Note**: Support for CUDA 11 will be removed in future releases. Please update to CUDA 12."
+            deprecation_notice=""
             cat python/README.md.in > python/metapackages/README.md
             for variable in package_name cuda_version_requirement cuda_version_conda deprecation_notice; do
               sed -i "s/.{{[ ]*$variable[ ]*}}/${!variable}/g" python/metapackages/README.md

.licenserc.yaml

@@ -41,6 +41,7 @@ header:
     - 'include/cudaq/Optimizer/CodeGen/OptUtils.h'
     - 'lib/Optimizer/CodeGen/OptUtils.cpp'
     - 'runtime/cudaq/algorithms/optimizers/nlopt/nlopt-src'
+    - 'python/metapackages/MANIFEST.in'
 
   comment: on-failure
 

docker/build/assets.Dockerfile

@@ -164,7 +164,8 @@ RUN source /cuda-quantum/scripts/configure_build.sh && \
 
 ## [Python support]
 FROM prereqs AS python_build
-ADD "pyproject.toml" /cuda-quantum/pyproject.toml
+# Bring all possible templates into the image, then pick the exact one
+ADD pyproject.toml.cu* /cuda-quantum/
 ADD "python" /cuda-quantum/python
 ADD "cmake" /cuda-quantum/cmake
 ADD "include" /cuda-quantum/include
@@ -186,22 +187,13 @@ RUN dnf install -y --nobest --setopt=install_weak_deps=False ${PYTHON}-devel &&
     ${PYTHON} -m ensurepip --upgrade && \
     ${PYTHON} -m pip install numpy build auditwheel patchelf
 
-RUN cd /cuda-quantum && source scripts/configure_build.sh && \
-    if [ "${CUDA_VERSION#12.}" != "${CUDA_VERSION}" ]; then \
-        cublas_version=12.0 && \
-        cusolver_version=11.4 && \
-        cuda_runtime_version=12.0 && \
-        cuda_nvrtc_version=12.0 && \
-        cupy_version=13.4.1 && \
-        sed -i "s/-cu13/-cu12/g" pyproject.toml && \
-        sed -i "s/-cuda13/-cuda12/g" pyproject.toml && \
-        sed -i -E "s/cupy-cuda[0-9]+x/cupy-cuda12x/g" pyproject.toml && \
-        sed -i -E "s/(cupy-cuda[0-9]+x? ~= )[0-9\.]*/\1${cupy_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cublas-cu[0-9]* ~= )[0-9\.]*/\1${cublas_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cusolver-cu[0-9]* ~= )[0-9\.]*/\1${cusolver_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cuda-nvrtc-cu[0-9]* ~= )[0-9\.]*/\1${cuda_nvrtc_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cuda-runtime-cu[0-9]* ~= )[0-9\.]*/\1${cuda_runtime_version}/g" pyproject.toml; \
-    fi && \
+RUN cd /cuda-quantum && \
+    . scripts/configure_build.sh && \
+    case "${CUDA_VERSION%%.*}" in \
+      12) cp pyproject.toml.cu12 pyproject.toml || true ;; \
+      13) cp pyproject.toml.cu13 pyproject.toml || true ;; \
+      *)  echo "Unsupported CUDA_VERSION=${CUDA_VERSION}"; exit 1 ;; \
+    esac && \
     # Needed to retrigger the LLVM build, since the MLIR Python bindings
     # are not built in the prereqs stage.
     rm -rf "${LLVM_INSTALL_PREFIX}" && \

docker/release/cudaq.ext.Dockerfile

@@ -49,6 +49,9 @@ RUN if [ -x "$(command -v pip)" ]; then \
             pip install --no-cache-dir mpi4py~=3.1; \
         fi; \
     fi
+RUN cuda_version_suffix=$(echo ${CUDA_VERSION} | tr . -) && \
+    pip install nvidia-curand-cu${cuda_version_suffix}
+
 # Make sure that apt-get remains updated at the end!;
 # If we don't do that, then apt-get will get confused when some CUDA
 # components are already installed but not all of them.

docker/release/cudaq.wheel.Dockerfile

@@ -37,23 +37,14 @@ RUN echo "Building MLIR bindings for python${python_version}" && \
     LLVM_CMAKE_CACHE=/cmake/caches/LLVM.cmake LLVM_SOURCE=/llvm-project \
     bash /scripts/build_llvm.sh -c Release -v 
 
-# Patch the pyproject.toml file to change the CUDA version if needed
-RUN cd cuda-quantum && sed -i "s/README.md.in/README.md/g" pyproject.toml && \
-    if [ "${CUDA_VERSION#12.}" != "${CUDA_VERSION}" ]; then \
-        cublas_version=12.0 && \
-        cusolver_version=11.4 && \
-        cuda_runtime_version=12.0 && \
-        cuda_nvrtc_version=12.0 && \
-        cupy_version=13.4.1 && \
-        sed -i "s/-cu13/-cu12/g" pyproject.toml && \
-        sed -i "s/-cuda13/-cuda12/g" pyproject.toml && \
-        sed -i -E "s/cupy-cuda[0-9]+x/cupy-cuda12x/g" pyproject.toml && \
-        sed -i -E "s/(cupy-cuda[0-9]+x? ~= )[0-9\.]*/\1${cupy_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cublas-cu[0-9]* ~= )[0-9\.]*/\1${cublas_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cusolver-cu[0-9]* ~= )[0-9\.]*/\1${cusolver_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cuda-nvrtc-cu[0-9]* ~= )[0-9\.]*/\1${cuda_nvrtc_version}/g" pyproject.toml && \
-        sed -i -E "s/(nvidia-cuda-runtime-cu[0-9]* ~= )[0-9\.]*/\1${cuda_runtime_version}/g" pyproject.toml; \
-    fi
+# Configure the build based on the CUDA version
+RUN cd /cuda-quantum && \
+    . scripts/configure_build.sh && \
+    case "${CUDA_VERSION%%.*}" in \
+      12) cp pyproject.toml.cu12 pyproject.toml || true ;; \
+      13) cp pyproject.toml.cu13 pyproject.toml || true ;; \
+      *)  echo "Unsupported CUDA_VERSION=${CUDA_VERSION}"; exit 1 ;; \
+    esac
 
 # Create the README
 RUN cd cuda-quantum && cat python/README.md.in > python/README.md && \

docs/sphinx/applications/python/hybrid_quantum_neural_networks.ipynb

@@ -34,7 +34,7 @@
    "source": [
     "# Install the relevant packages.\n",
     "\n",
-    "!pip install matplotlib==3.8.4 torch==2.0.1+cu118 torchvision==0.15.2+cu118 scikit-learn==1.4.2 -q --extra-index-url https://download.pytorch.org/whl/cu118"
+    "!pip install matplotlib==3.8.4 torch==2.9.0+cu126 torchvision==0.24.0+cu126 scikit-learn==1.4.2 -q --extra-index-url https://download.pytorch.org/whl/cu126"
    ]
   },
   {

docs/sphinx/using/install/data_center_install.rst

@@ -255,8 +255,8 @@ Python-specific tools:
 
 .. note::
 
-  The wheel build by default is configured to depend on CUDA 12. To build a wheel for CUDA 11, 
-  you need to adjust the dependencies and project name in the `pyproject.toml` file. 
+  The wheel build by default is configured to depend on CUDA 13. To build a wheel for CUDA 12, 
+  you need to copy the `pyproject.toml.cu12` file as `pyproject.toml`. 
 
 From within the folder where you cloned the CUDA-Q repository, run the following
 command to build the CUDA-Q Python wheel:

docs/sphinx/using/install/local_installation.rst

@@ -834,10 +834,10 @@ by running the command
 .. note::
 
   Please check if you have an existing installation of the `cuda-quantum`, 
-  `cudaq-quantum-cu11`, or `cuda-quantum-cu12` package, 
+  `cudaq-quantum-cu12`, or `cuda-quantum-cu13` package, 
   and uninstall it prior to installing `cudaq`. The `cudaq` package supersedes the
   `cuda-quantum` package and will install a suitable binary distribution (either 
-  `cuda-quantum-cu11` or `cuda-quantum-cu12`) for your system. Multiple versions 
+  `cuda-quantum-cu12` or `cuda-quantum-cu13`) for your system. Multiple versions 
   of a CUDA-Q binary distribution will conflict with each other and not work properly.
 
 If you previously installed the CUDA-Q pre-built binaries, you should first uninstall your 
@@ -892,9 +892,11 @@ The following table summarizes the required components.
     * - NVIDIA GPU with Compute Capability
       - 7.5+
     * - CUDA
-      - 12.x (Driver 525.60.13+), 13.x (Driver 580.65.06+)
-
-Detailed information about supported drivers for different CUDA versions and be found `here <https://docs.nvidia.com/deploy/cuda-compatibility/>`__.
+      - • 12.x (Driver 525.60.13+) – For GPUs that support CUDA Forward Compatibility  
+        • 12.6+ (Driver 560.35.05+) – For all GPUs with supported architecture  
+        • 13.x (Driver 580.65.06+)
+
+Detailed information about supported drivers for different CUDA versions and be found `here <https://docs.nvidia.com/deploy/cuda-compatibility/>`__. For more information on GPU forward capabilities, please refer to `this page <https://docs.nvidia.com/deploy/cuda-compatibility/forward-compatibility.html>`__.
 
 .. note::
 

docs/sphinx/using/quick_start.rst

@@ -42,7 +42,7 @@ Install CUDA-Q
 
    To develop CUDA-Q applications using C++, please make sure you have a C++ toolchain installed
    that supports C++20, for example `g++` version 11 or newer.
-   Download the `install_cuda_quantum` file for your processor architecture and CUDA version (`_cu11` suffix for CUDA 11 and `_cu12` suffix for CUDA 12) 
+   Download the `install_cuda_quantum` file for your processor architecture and CUDA version (`_cu12` suffix for CUDA 12 and `_cu13` suffix for CUDA 13) 
    from the assets of the respective `GitHub release <https://github.com/NVIDIA/cuda-quantum/releases>`__; 
    that is, the file with the `aarch64` extension for ARM processors, and the one with `x86_64` for, e.g., Intel and AMD processors.
 

pyproject.toml

@@ -0,0 +1 @@
+pyproject.toml.cu13