cuNumeric.jl

The cuNumeric.jl package wraps the CuPyNumeric C++ API from NVIDIA to bring simple distributed computing on GPUs and CPUs to Julia! We provide a simple array abstraction, the NDArray, which supports most of the operations you would expect from a normal Julia array.

This project is in alpha and we do not commit to anything necessarily working as you would expect. The current build process requires several external dependencies which are not registered on BinaryBuilder.jl yet. The build instructions and minimum pre-requesites are as follows:

Minimum prereqs

• g++ capable of C++20
• CUDA 12.2
• Python 3.10
• Ubuntu 20.04 or RHEL 8
• Julia 1.10
• CMake 3.26.4

1. Download cuPyNumeric

conda create --name myenv 
conda activate myenv
CONDA_OVERRIDE_CUDA="12.2" \
  conda install -c conda-forge -c legate cupynumeric

2. Install Julia through JuliaUp

curl -fsSL https://install.julialang.org | sh -s -- --default-channel 1.10

This will install version 1.10 by default since that is what we have tested against. To verify 1.10 is the default run either of the following (your may need to source bashrc):

juliaup status
julia --version

If 1.10 is not your default, please set it to be the default. Newer versions of Julia are untested.

juliaup default 1.10

3. Get latest version of libcxxwrap

These commands simply download an external dependency used to wrap the CuPyNumeric C++ API.

git submodule init
git submodule update

4. Build Julia Package

This command must be run form the root of the repository. The progress of this command is piped into ./pkg/deps/build.log. It may take a few minutes to compile.

julia -e 'using Pkg; Pkg.activate("./pkg"); Pkg.resolve(); Pkg.build()'

5. Test the Julia Package

This command must be run form the root of the repository.

julia -e 'using Pkg; Pkg.activate("./pkg"); Pkg.resolve(); Pkg.test()'

With everything working, its the perfect time to checkout some of our examples!

TO-DO List of Missing Important Features

• Full slicing support
• Implement unary_reduction over arbitrary dims
• Out-parameter binary_op
• Replace as_type with Base.convert
• Integer powers (e.g x^3)
• Support Ints on methods that takes floats
• Programatic manipulation of Legate hardware config (not currently possible)
• Float32 random number generation (not possible in current C++ API)
• Normal random numbers (not possible in current C++ API)
• Add Aqua.jl to CI to ensure we didn't pirate any types
• Fix CodeCov reports
• Fix cuNumeric.jl error in CI (requires unreleased CuPyNumeric)
• Move external packages to BinaryBuilder.jl (requires Legate open source)

Custom install

Optional: You can create a file called .localenv in order to add anything to the path.

source ENV will setup the enviroment variables and source optional .localenv

sh scripts/install_cxxwrap.sh builds the Julia CXX wrapper https://github.com/JuliaInterop/libcxxwrap-julia

sh scripts/legion_redop_patch.inl patches Legion https://github.com/ejmeitz/cuNumeric.jl/blob/main/scripts/README.md

sh ./build.sh will create libcupynumericwrapper.so in $CUNUMERIC_JL_HOME/build

Contact

For technical questions, please either contact krasow(at)u.northwestern.edu OR emeitz(at)andrew.cmu.edu

If the issue is building the package, please include the build.log and env.log found in cuNumeric.jl/pkg/deps/