Productivity library for distributed and partitioned memory based on C++ Ranges.
The documentation is built from main branch on every commit and published at latest spec and latest doxygen.
CPU & SYCL (MPI) requires g++ 10 or higher, mpi, and MKL. On Ubuntu 20.04:
sudo apt install g++-10 libopenmpi-dev
SYCL (SHP) requires g++ 12 standard library. On Ubuntu 22.04:
sudo apt install g++-12
SYCL (SHP) requires a nightly build from the dpcpp open source project. If you are targeting intel gpu:
wget https://github.com/intel/llvm/releases/download/sycl-nightly%2F20221029/dpcpp-compiler.tar.gz tar zxf dpcpp-compiler.tar.gz source dpcpp_compiler/startup.sh
If you are targeting cuda:
git clone https://github.com/intel/llvm cd llvm git checkout sycl-nightly/20221029 python buildbot/configure.py --cuda
Copy startup.sh from the open source binary build, or create it at build/install/startup.sh:
export SYCL_BUNDLE_ROOT=$(realpath $(dirname "${BASH_SOURCE[0]}"))
export PATH=$SYCL_BUNDLE_ROOT/bin:$PATH
export CPATH=$SYCL_BUNDLE_ROOT/include:$CPATH
export LIBRARY_PATH=$SYCL_BUNDLE_ROOT/lib:$LIBRARY_PATH
export LD_LIBRARY_PATH=$SYCL_BUNDLE_ROOT/lib:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$SYCL_BUNDLE_ROOT/linux/lib/x64:$LD_LIBRARY_PATH
export LD_LIBRARY_PATH=$SYCL_BUNDLE_ROOT/lib/oclgpu:$LD_LIBRARY_PATH
Then:
source build/install/startup.sh
If you want to build the document or run the pre-commit checks, you must install some python packages. Create a python virtual environment and install dependencies:
python -m venv venv source venv/bin/activate pip install -r requirements.txt
Activate virtual environment:
source venv/bin/activate
Build and test examples with gcc on CPU:
CXX=g++-10 cmake -B build make -C build -j all test
Enable SYCL examples:
CXX=clang++ cmake -B build -DENABLE_SYCL=ON
Enable SYCL-MPI examples:
CXX=clang++ cmake -B build -DENABLE_SYCL_MPI=ON
See how example is run and the output:
cd build ctest -VV
Add this to your main to enable logging:
std::ofstream logfile(fmt::format("dr.{}.log", comm_rank));
dr::drlog.set_file(logfile);
If your project uses CMAKE, add the following to your
CMakeLists.txt to download the library:
find_package(MPI REQUIRED) include(FetchContent) FetchContent_Declare( dr GIT_REPOSITORY https://github.com/oneapi-src/distributed-ranges.git GIT_TAG main ) FetchContent_MakeAvailable(dr)
The above will define targets that can be included in your project:
target_link_libraries(<application> MPI::MPI_CXX DR::mpi)
If your project does not use CMAKE, then you need to download the library, and install it into a prefix:
git clone https://github.com/oneapi-src/distributed-ranges.git dr cd dr cmake -B build -DCMAKE_INSTALL_PREFIX=<prefix> make -C build install cmake -B build-fmt -DCMAKE_INSTALL_PREFIX=<prefix> build/_deps/cpp-format-src make -C build-fmt install
Use -I and -L to find headers and libs during compilation:
g++ -std=c=++20 -I <prefix>/include -L <prefix>/lib -L /opt/intel/oneapi/mpi/latest/lib/release -lfmt -lmpicxx -lmpi
Follow the standard github workflow. Fork this repo, clone your fork, make changes, commit to a new branch, push branch to your fork. Submit a PR from your fork.
The CI runs static checks and runs the test system. See pre-commit for information on failing static checks.
- Fuzz Testing
- Fuzz testing of distributed ranges APIs
- Spec Editing
- Editing the API document
- Print Type
- Print types at compile time:
- Testing
- Test system maintenance