Use CUDA math wheels

ci/build_wheel.sh

@@ -16,10 +16,26 @@ rapids-generate-version > ./VERSION
 
 cd "${package_dir}"
 
+case "${RAPIDS_CUDA_VERSION}" in
+  12.*)
+    EXCLUDE_ARGS=(
+      --exclude "libcublas.so.12"
+      --exclude "libcublasLt.so.12"
+      --exclude "libcurand.so.10"
+      --exclude "libcusolver.so.11"
+      --exclude "libcusparse.so.12"
+      --exclude "libnvJitLink.so.12"
+    )
+  ;;
+  11.*)
+    EXCLUDE_ARGS=()
+  ;;
+esac
+
 # Hardcode the output dir
 python -m pip wheel . -w dist -vvv --no-deps --disable-pip-version-check
 
 mkdir -p final_dist
-python -m auditwheel repair -w final_dist dist/*
+python -m auditwheel repair -w final_dist "${EXCLUDE_ARGS[@]}" dist/*
 
 RAPIDS_PY_WHEEL_NAME="${underscore_package_name}_${RAPIDS_PY_CUDA_SUFFIX}" rapids-upload-wheels-to-s3 final_dist

ci/build_wheel_cuvs.sh

@@ -3,7 +3,16 @@
 
 set -euo pipefail
 
+case "${RAPIDS_CUDA_VERSION}" in
+  12.*)
+    EXTRA_CMAKE_ARGS=";-DUSE_CUDA_MATH_WHEELS=ON"
+  ;;
+  11.*)
+    EXTRA_CMAKE_ARGS=";-DUSE_CUDA_MATH_WHEELS=OFF"
+  ;;
+esac
+
 # Set up skbuild options. Enable sccache in skbuild config options
-export SKBUILD_CMAKE_ARGS="-DDETECT_CONDA_ENV=OFF -DFIND_CUVS_CPP=OFF"
+export SKBUILD_CMAKE_ARGS="-DDETECT_CONDA_ENV=OFF;-DFIND_CUVS_CPP=OFF${EXTRA_CMAKE_ARGS}"
 
 ci/build_wheel.sh cuvs python/cuvs

dependencies.yaml

@@ -78,6 +78,7 @@ files:
     extras:
       table: project
     includes:
+      - cuda
       - run_py_cuvs
   py_test_py_cuvs:
     output: pyproject
@@ -310,6 +311,24 @@ dependencies:
               - *libcusolver114
               - *libcusparse_dev114
               - *libcusparse114
+      - output_types: pyproject
+        matrices:
+          - matrix:
+              cuda: "12.*"
+            packages:
+              - nvidia-cublas-cu12
+              - nvidia-curand-cu12
+              - nvidia-cusolver-cu12
+              - nvidia-cusparse-cu12
+          - matrix:
+              cuda: "11.*"
+            packages:
+          - matrix:
+            packages:
+              - nvidia-cublas
+              - nvidia-curand
+              - nvidia-cusolver
+              - nvidia-cusparse
 
   cupy:
     common:

python/cuvs/CMakeLists.txt

@@ -37,6 +37,7 @@ project(
 option(FIND_CUVS_CPP "Search for existing CUVS C++ installations before defaulting to local files"
        OFF
 )
+option(USE_CUDA_MATH_WHEELS "Use the CUDA math wheels instead of the system libraries" OFF)
 
 message(
   "CUVS_PY: Searching for existing cuVS C/C++ installations before defaulting to local files: ${FIND_CUVS_CPP}"
@@ -62,6 +63,8 @@ else()
 endif()
 
 if(NOT cuvs_FOUND)
+  find_package(CUDAToolkit REQUIRED)
+
   set(BUILD_TESTS OFF)
   set(BUILD_C_LIBRARY ON)
 
@@ -70,8 +73,26 @@ if(NOT cuvs_FOUND)
   set(CUDA_STATIC_MATH_LIBRARIES ON)
   set(CUVS_USE_RAFT_STATIC ON)
 
+  if(CUDAToolkit_VERSION VERSION_GREATER_EQUAL 12.0)
+    set(CUDA_STATIC_MATH_LIBRARIES OFF)
+  elseif(USE_CUDA_MATH_WHEELS)
+    message(FATAL_ERROR "Cannot use CUDA math wheels with CUDA < 12.0")
+  endif()
+
   add_subdirectory(../../cpp cuvs-cpp EXCLUDE_FROM_ALL)
 
+  if(NOT CUDA_STATIC_MATH_LIBRARIES AND USE_CUDA_MATH_WHEELS)
+    set(rpaths
+      "$ORIGIN/../nvidia/cublas/lib"
+      "$ORIGIN/../nvidia/curand/lib"
+      "$ORIGIN/../nvidia/cusolver/lib"
+      "$ORIGIN/../nvidia/cusparse/lib"
+      "$ORIGIN/../nvidia/nvjitlink/lib"
+    )
+    set_property(TARGET cuvs PROPERTY INSTALL_RPATH ${rpaths} APPEND)
+    set_property(TARGET cuvs_c PROPERTY INSTALL_RPATH ${rpaths} APPEND)
+  endif()
+
   set(cython_lib_dir cuvs)
   install(TARGETS cuvs cuvs_c DESTINATION ${cython_lib_dir})
 endif()

python/cuvs/pyproject.toml

@@ -33,6 +33,10 @@ requires-python = ">=3.9"
 dependencies = [
     "cuda-python",
     "numpy>=1.23,<2.0a0",
+    "nvidia-cublas",
+    "nvidia-curand",
+    "nvidia-cusolver",
+    "nvidia-cusparse",
     "pylibraft==24.10.*,>=0.0.0a0",
 ] # This list was generated by `rapids-dependency-file-generator`. To make changes, edit ../../dependencies.yaml and run `rapids-dependency-file-generator`.
 classifiers = [