[review] Open source nvgraph in cugraph repository

.gitmodules

@@ -0,0 +1,12 @@
+[submodule "cpp/nvgraph/cpp/thirdparty/cnmem"]
+	path = cpp/nvgraph/cpp/thirdparty/cnmem
+	url = https://github.com/NVIDIA/cnmem.git
+	branch = master
+[submodule "cpp/nvgraph/cpp/thirdparty/cub"]
+	path = cpp/nvgraph/cpp/thirdparty/cub
+	url = https://github.com/NVlabs/cub.git
+	branch = 1.8.0
+[submodule "cpp/nvgraph/external/cusp"]
+	path = cpp/nvgraph/external/cusp
+	url = https://github.com/cusplibrary/cusplibrary.git
+	branch = cuda9

CHANGELOG.md

@@ -7,10 +7,10 @@
 ## Improvements
 - PR #157 Removed cudatoolkit dependency in setup.py
 - PR #185 Update docs version
+- PR #194 Open source nvgraph in cugraph repository #194
 - PR #190 Added a copy option in graph creation
 - PR #196 Fix typos in readme intro
 
-
 ## Bug Fixes
 - PR #169 Disable terminal output in sssp 
 - PR #191 Fix double upload bug

README.md

@@ -192,7 +192,7 @@ conda activate cugraph_dev
 
 3) Build and install `libcugraph`. CMake depends on the `nvcc` executable being on your path or defined in `$CUDACXX`.
 
-  This project uses cmake for building the C/C++ library. To configure cmake, run:
+  This project uses cmake for building the C/C++ library. CMake will also automatically build and install nvGraph library (`$CUGRAPH_HOME/cpp/nvgraph`) which may take a few minutes. To configure cmake, run:
 
   ```bash
   # Set the localtion to cuGraph in an environment variable CUGRAPH_HOME 
@@ -320,8 +320,9 @@ unset LD_LIBRARY_PATH
 
 
 
+## nvGraph
 
-
+The nvGraph library is now open source and part of cuGraph. It can be build as a stand alone by following nvgraph's [readme](cpp/nvgraph/). 
 
 
 ------

ci/cpu/cugraph/upload-anaconda.sh

@@ -4,26 +4,18 @@
 
 set -e
 
-if [ "$BUILD_CUGRAPH" == "1" ]; then
-  if [ "$BUILD_ABI" == "1" ]; then
-    export UPLOADFILE=`conda build conda/recipes/cugraph -c rapidsai -c nvidia -c numba -c conda-forge -c defaults --python=$PYTHON --output`
-  else
-    export UPLOADFILE=`conda build conda/recipes/cugraph -c rapidsai/label/cf201901 -c nvidia/label/cf201901 -c numba -c conda-forge/label/cf201901 -c defaults --python=$PYTHON --output`
-  fi
+if [ "$UPLOAD_CUGRAPH" == "1" ]; then
+  export UPLOADFILE=`conda build conda/recipes/cugraph -c rapidsai -c nvidia -c numba -c conda-forge -c defaults --python=$PYTHON --output`
 
   SOURCE_BRANCH=master
 
   # Have to label all CUDA versions due to the compatibility to work with any CUDA
-  if [ "$LABEL_MAIN" == "1" -a "$BUILD_ABI" == "1" ]; then
+  if [ "$LABEL_MAIN" == "1" ]; then
     LABEL_OPTION="--label main --label cuda9.2 --label cuda10.0"
-  elif [ "$LABEL_MAIN" == "0" -a "$BUILD_ABI" == "1" ]; then
+  elif [ "$LABEL_MAIN" == "0" ]; then
     LABEL_OPTION="--label dev --label cuda9.2 --label cuda10.0"
-  elif [ "$LABEL_MAIN" == "1" -a "$BUILD_ABI" == "0" ]; then
-    LABEL_OPTION="--label cf201901 --label cf201901-cuda9.2 --label cf201901-cuda10.0"
-  elif [ "$LABEL_MAIN" == "0" -a "$BUILD_ABI" == "0" ]; then
-    LABEL_OPTION="--label cf201901-dev --label cf201901-cuda9.2 --label cf201901-cuda10.0"
   else
-    echo "Unknown label configuration LABEL_MAIN='$LABEL_MAIN' BUILD_ABI='$BUILD_ABI'"
+    echo "Unknown label configuration LABEL_MAIN='$LABEL_MAIN'"
     exit 1
   fi
   echo "LABEL_OPTION=${LABEL_OPTION}"
@@ -44,4 +36,7 @@ if [ "$BUILD_CUGRAPH" == "1" ]; then
   echo "Upload"
   echo ${UPLOADFILE}
   anaconda -t ${MY_UPLOAD_KEY} upload -u ${CONDA_USERNAME:-rapidsai} ${LABEL_OPTION} --force ${UPLOADFILE}
+else
+    echo "Skipping cugraph upload"
+    return 0
 fi

ci/cpu/libcugraph/upload-anaconda.sh

@@ -4,31 +4,23 @@
 
 set -e
 
-if [ "$BUILD_LIBCUGRAPH" == "1" ]; then
+if [ "$UPLOAD_LIBCUGRAPH" == "1" ]; then
   CUDA_REL=${CUDA:0:3}
   if [ "${CUDA:0:2}" == '10' ]; then
     # CUDA 10 release
     CUDA_REL=${CUDA:0:4}
   fi
 
-  if [ "$BUILD_ABI" == "1" ]; then
-    export UPLOADFILE=`conda build conda/recipes/libcugraph -c rapidsai -c nvidia -c numba -c conda-forge -c defaults --python=$PYTHON --output`
-  else
-    export UPLOADFILE=`conda build conda/recipes/libcugraph -c rapidsai/label/cf201901 -c nvidia/label/cf201901 -c numba -c conda-forge/label/cf201901 -c defaults --python=$PYTHON --output`
-  fi
+  export UPLOADFILE=`conda build conda/recipes/libcugraph -c rapidsai -c nvidia -c numba -c conda-forge -c defaults --python=$PYTHON --output`
 
   SOURCE_BRANCH=master
 
-  if [ "$LABEL_MAIN" == "1" -a "$BUILD_ABI" == "1" ]; then
+  if [ "$LABEL_MAIN" == "1" ]; then
     LABEL_OPTION="--label main --label cuda${CUDA_REL}"
-  elif [ "$LABEL_MAIN" == "0" -a "$BUILD_ABI" == "1" ]; then
+  elif [ "$LABEL_MAIN" == "0" ]; then
     LABEL_OPTION="--label dev --label cuda${CUDA_REL}"
-  elif [ "$LABEL_MAIN" == "1" -a "$BUILD_ABI" == "0" ]; then
-    LABEL_OPTION="--label cf201901 --label cf201901-cuda${CUDA_REL}"
-  elif [ "$LABEL_MAIN" == "0" -a "$BUILD_ABI" == "0" ]; then
-    LABEL_OPTION="--label cf201901-dev --label cf201901-cuda${CUDA_REL}"
   else
-    echo "Unknown label configuration LABEL_MAIN='$LABEL_MAIN' BUILD_ABI='$BUILD_ABI'"
+    echo "Unknown label configuration LABEL_MAIN='$LABEL_MAIN'"
     exit 1
   fi
   echo "LABEL_OPTION=${LABEL_OPTION}"
@@ -49,4 +41,6 @@ if [ "$BUILD_LIBCUGRAPH" == "1" ]; then
   echo "Upload"
   echo ${UPLOADFILE}
   anaconda -t ${MY_UPLOAD_KEY} upload -u ${CONDA_USERNAME:-rapidsai} ${LABEL_OPTION} --force ${UPLOADFILE}
+else
+    echo "Skipping libcugraph upload"
 fi

ci/cpu/prebuild.sh

@@ -1,15 +1,17 @@
 #!/usr/bin/env bash
 
 export BUILD_ABI=1
+export BUILD_CUGRAPH=1
+export BUILD_LIBCUGRAPH=1
 
 if [[ "$CUDA" == "9.2" ]]; then
-    export BUILD_CUGRAPH=1
+    export UPLOAD_CUGRAPH=1
 else
-    export BUILD_CUGRAPH=0
+    export UPLOAD_CUGRAPH=0
 fi
 
 if [[ "$PYTHON" == "3.6" ]]; then
-    export BUILD_LIBCUGRAPH=1
+    export UPLOAD_LIBCUGRAPH=1
 else
-    export BUILD_LIBCUGRAPH=0
+    export UPLOAD_LIBCUGRAPH=0
 fi

conda/environments/cugraph_dev.yml

@@ -7,7 +7,6 @@ channels:
 - defaults
 dependencies:
 - cudf>=0.5.1
-- nvgraph
 - scipy
 - networkx
 - python-louvain

conda/environments/cugraph_dev_cuda10.yml

@@ -7,7 +7,6 @@ channels:
 - defaults
 dependencies:
 - cudf>=0.5.1
-- nvgraph
 - scipy
 - networkx
 - python-louvain

conda/environments/cugraph_nightly.yml

@@ -8,7 +8,6 @@ channels:
 - defaults
 dependencies:
 - cudf=0.6
-- nvgraph
 - scipy
 - networkx
 - python-louvain

conda/environments/cugraph_nightly_cuda10.yml

@@ -8,7 +8,6 @@ channels:
 - defaults
 dependencies:
 - cudf=0.6
-- nvgraph
 - scipy
 - networkx
 - python-louvain

cpp/CMakeLists.txt

@@ -129,6 +129,11 @@ message(STATUS "CMAKE_CUDA_FLAGS: ${CMAKE_CUDA_FLAGS}")
 # - cmake custom modules --------------------------------------------------------------------------
 include(ConfigureGoogleTest)
 
+# speedup build time by avoiding features that are not exposed
+set(NVGRAPH_LIGHT True)
+# build nvgraph
+include(ConfigureNvgraph)
+
 ###################################################################################################
 # - Find and add different modules and supporting repos -------------------------------------------
 find_package(Boost 1.45.0 COMPONENTS system)
@@ -186,12 +191,11 @@ endif (RMM_INCLUDE AND RMM_LIBRARY)
 
 ###################################################################################################
 # - add nvgraph -----------------------------------------------------------------------------------
+
 find_path(NVGRAPH_INCLUDE "nvgraph"
-      HINTS "$ENV{NVGRAPH_ROOT}/include"
-            "$ENV{CONDA_PREFIX}/include")
-find_library(NVGRAPH_LIBRARY "nvgraph_st"
-         HINTS "$ENV{NVGRAPH_ROOT}/lib"
-               "$ENV{CONDA_PREFIX}/lib")
+      HINTS "$ENV{CONDA_PREFIX}/include")
+find_library(NVGRAPH_LIBRARY "nvgraph_rapids"
+         HINTS "$ENV{CONDA_PREFIX}/lib")
 
 add_library( nvgraph SHARED IMPORTED)
 if (NVGRAPH_INCLUDE AND NVGRAPH_LIBRARY)

cpp/cmake/Modules/ConfigureNvgraph.cmake

@@ -0,0 +1,65 @@
+set(NVGRAPH_ROOT "${CMAKE_CURRENT_SOURCE_DIR}/nvgraph")
+
+set(NVGRAPH_CMAKE_ARGS "")
+                     #" -DNVGRAPH_build_samples=ON" 
+                     #" -DCMAKE_VERBOSE_MAKEFILE=ON")
+
+if(NOT CMAKE_CXX11_ABI)
+    message(STATUS "NVGRAPH: Disabling the GLIBCXX11 ABI")
+    list(APPEND NVGRAPH_CMAKE_ARGS " -DCMAKE_C_FLAGS=-D_GLIBCXX_USE_CXX11_ABI=0")
+    list(APPEND NVGRAPH_CMAKE_ARGS " -DCMAKE_CXX_FLAGS=-D_GLIBCXX_USE_CXX11_ABI=0")
+elseif(CMAKE_CXX11_ABI)
+    message(STATUS "NVGRAPH: Enabling the GLIBCXX11 ABI")
+    list(APPEND NVGRAPH_CMAKE_ARGS " -DCMAKE_C_FLAGS=-D_GLIBCXX_USE_CXX11_ABI=1")
+    list(APPEND NVGRAPH_CMAKE_ARGS " -DCMAKE_CXX_FLAGS=-D_GLIBCXX_USE_CXX11_ABI=1")
+endif(NOT CMAKE_CXX11_ABI)
+
+#configure_file("${CMAKE_SOURCE_DIR}/cmake/Templates/Nvgraph.CMakeLists.txt.cmake"
+#               "${NVGRAPH_ROOT}/cpp/CMakeLists.txt")
+
+file(MAKE_DIRECTORY "${NVGRAPH_ROOT}/cpp/build")
+#file(MAKE_DIRECTORY "${NVGRAPH_ROOT}/install")
+
+execute_process(COMMAND ${CMAKE_COMMAND} -G ${CMAKE_GENERATOR} .. -DCMAKE_INSTALL_PREFIX=${CMAKE_INSTALL_PREFIX} -DNVGRAPH_LIGHT=${NVGRAPH_LIGHT}
+                RESULT_VARIABLE NVGRAPH_CONFIG
+                WORKING_DIRECTORY ${NVGRAPH_ROOT}/cpp/build)
+
+if(NVGRAPH_CONFIG)
+    message(FATAL_ERROR "Configuring nvgraph failed: " ${NVGRAPH_CONFIG})
+endif(NVGRAPH_CONFIG)
+
+set(PARALLEL_BUILD -j)
+if($ENV{PARALLEL_LEVEL})
+    set(NUM_JOBS $ENV{PARALLEL_LEVEL})
+    set(PARALLEL_BUILD "${PARALLEL_BUILD}${NUM_JOBS}")
+endif($ENV{PARALLEL_LEVEL})
+
+if(${NUM_JOBS})
+    if(${NUM_JOBS} EQUAL 1)
+        message(STATUS "NVGRAPH BUILD: Enabling Sequential CMake build")
+    elseif(${NUM_JOBS} GREATER 1)
+        message(STATUS "NVGRAPH BUILD: Enabling Parallel CMake build with ${NUM_JOBS} jobs")
+    endif(${NUM_JOBS} EQUAL 1)
+else()
+    message(STATUS "NVGRAPH BUILD: Enabling Parallel CMake build with all threads")
+endif(${NUM_JOBS})
+
+execute_process(COMMAND ${CMAKE_COMMAND} --build . -- ${PARALLEL_BUILD}
+                RESULT_VARIABLE NVGRAPH_BUILD
+                WORKING_DIRECTORY ${NVGRAPH_ROOT}/cpp/build)
+if(NVGRAPH_BUILD)
+    message(FATAL_ERROR "Building nvgraph failed: " ${NVGRAPH_BUILD})
+endif(NVGRAPH_BUILD)
+
+execute_process(COMMAND ${CMAKE_COMMAND} --build . --target install 
+                RESULT_VARIABLE NVGRAPH_BUILD
+                WORKING_DIRECTORY ${NVGRAPH_ROOT}/cpp/build)
+
+if(NVGRAPH_BUILD)
+    message(FATAL_ERROR "Installing nvgraph failed: " ${NVGRAPH_BUILD})
+endif(NVGRAPH_BUILD)
+
+message(STATUS "nvgraph installed under: " ${CMAKE_INSTALL_PREFIX})
+set(NVGRAPH_INCLUDE "${CMAKE_INSTALL_PREFIX}/include/nvgraph.h ${CMAKE_INSTALL_PREFIX}/include/test_opt_utils.cuh")
+set(NVGRAPH_LIBRARY "${CMAKE_INSTALL_PREFIX}/lib/libnvgraph_rapids.so")
+set(NVGRAPH_FOUND TRUE)

cpp/nvgraph/README.md

@@ -0,0 +1,103 @@
+# <div align="left"><img src="../../img/rapids_logo.png" width="90px"/>&nbsp;nvgraph - NVIDIA graph library</div>
+
+Data analytics is a growing application of high-performance computing. Many advanced data analytics problems can be couched as graph problems. In turn, many of the common graph problems today can be couched as sparse linear algebra. This is the motivation for nvGRAPH, which harnesses the power of GPUs for linear algebra to handle large graph analytics and big data analytics problems.
+
+## Development Setup
+
+### Conda{#conda}
+
+It is easy to install nvGraph using conda. You can get a minimal conda installation with [Miniconda](https://conda.io/miniconda.html) or get the full installation with [Anaconda](https://www.anaconda.com/download).
+
+Install and update nvGraph using the conda command:
+
+```bash
+# CUDA 9.2
+conda install -c nvidia nvgraph
+
+# CUDA 10.0
+conda install -c nvidia/label/cuda10.0 nvgraph 
+
+```
+
+Note: This conda installation only applies to Linux and Python versions 3.6/3.7.
+
+### Build from Source {#source}
+
+The following instructions are for developers and contributors to nvGraph OSS development. These instructions are tested on Linux Ubuntu 16.04 & 18.04. Use these instructions to build nvGraph from source and contribute to its development.  Other operating systems may be compatible, but are not currently tested.
+
+The nvGraph package is a C/C++ CUDA library. It needs to be installed in order for nvGraph to operate correctly.  
+
+The following instructions are tested on Linux systems.
+
+
+#### Prerequisites
+
+Compiler requirement:
+
+* `gcc`     version 5.4+
+* `nvcc`    version 9.2
+* `cmake`   version 3.12
+
+
+
+CUDA requirement:
+
+* CUDA 9.2+
+* NVIDIA driver 396.44+
+* Pascal architecture or better
+
+You can obtain CUDA from [https://developer.nvidia.com/cuda-downloads](https://developer.nvidia.com/cuda-downloads).
+Compiler requirements:
+
+
+#### Build and Install the C/C++ CUDA components
+
+To install cuGraph from source, ensure the dependencies are met and follow the steps below:
+
+1) Clone the repository and submodules
+
+  ```bash
+  # Set the localtion to cuGraph in an environment variable CUGRAPH_HOME 
+  export CUGRAPH_HOME=$(pwd)/cugraph
+
+  # Download the cuGraph repo
+  git clone https://github.com/rapidsai/cugraph.git $CUGRAPH_HOME
+
+  # Next load all the submodules
+  cd $CUGRAPH_HOME
+  git submodule update --init --recursive
+  ```
+
+2) Build and install `libnvgraph_rapids.so`. CMake depends on the `nvcc` executable being on your path or defined in `$CUDACXX`.
+
+  This project uses cmake for building the C/C++ library. To configure cmake, run:
+
+  ```bash
+  cd $CUGRAPH_HOME
+  cd cpp/nvgraph/cpp	# enter nvgraph's cpp directory
+  mkdir build   		# create build directory 
+  cd build     		# enter the build directory
+  cmake .. -DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX 
+
+  # now build the code
+  make -j				# "-j" starts multiple threads
+  make install		# install the libraries 
+  ```
+
+The default installation  locations are `$CMAKE_INSTALL_PREFIX/lib` and `$CMAKE_INSTALL_PREFIX/include/nvgraph` respectively.
+
+#### C++ stand alone tests
+
+```bash
+# Run the cugraph tests
+cd $CUGRAPH_HOME
+cd cpp/nvgraph/cpp/build
+gtests/NVGRAPH_TEST # this is an executable file
+```
+Other test executables require specific datasets and will result in failure if they are not present.
+## Documentation
+
+The C API documentation can be found in the [CUDA Toolkit Documentation](https://docs.nvidia.com/cuda/nvgraph/index.html).
+
+
+