This script allows you to build and setup the DPC++ compiler, oneMKL and oneDNN with Nvidia GPUs support.

1. If needed, set $DPCPP_HOME and $CUDA_ROOT in the script.
2. Run the script with ./build.sh.

Everything will be installed to $DPCPP_HOME/deploy.

To build with testing support and run the tests for DPC++, oneMKL, oneTBB, oneDNN and Lapack, run: DPCPP_TESTS=ON ./build.sh

If you want to build libc++, use CC=clang-X CXX=clang++-X with another version of clang, gcc won't compile the libc as the asm syntax is not the same. Using this clang/dpc++ won't work either, there's a bug. Then link with -stdlib=libc++.

Once everything was built, add the first four exports of the script in your environment or add them in your shell's config file.

1. Use the following selector:

class CUDADeviceSelector : public sycl::device_selector {
public:
    int operator()(const sycl::device &device) const override {
        return device.get_platform().get_backend() == sycl::backend::ext_oneapi_cuda ? 1 : -1;
    }
};

2. Build with -fsycl -fsycl-targets=nvptx64-nvidia-cuda
3. For oneMKL, link with: -lonemkl_blas_cublas -lonemkl

You can also install Intel's openCL driver (intel-oneapi-runtime-opencl) so you can target your CPU with -fsycl-targets=spir64_x86_64-unknown-unknown-sycldevice. For the setup see here .

• Even though the latest version of CUDA seems to work with DPC++, we need to use CUDA 10.2 as oneMKL uses cuBLAS 10.2. On RHEL: cuda-10-2 libcublas-devel-10-2. For the setup see: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#pre-installation-actions.
• libatomic
• to be able to target Intel's CPUs with openCL.
• ninja-build cmake libxml2-devel ... and other "build essentials" required for building a compiler.
• libcudnn8 libcudnn8-devel for oneDNN.
• gcc-gfortran or another Fortran compiler for NETLIB Lapack.
• hwloc-devel for oneTBB
• mpfr-devel when building libcxx

• CLion integration: you need to add cidr.compiler.clang.fsycl=true in the registry of CLion see
• oneMKL does not support testing when building for both cuBLAS and cuRAND
• for oneMKL with cuda you should use the namespace oneapi::mkl::blas::column_major:: as cuBLAS is column_major.

• OpenCL Headers+Loaders: https://github.com/KhronosGroup/OpenCL-Headers.git , https://github.com/KhronosGroup/OpenCL-ICD-Loader.git
• DPC++ Compiler: https://github.com/intel/llvm.git
• NETLIB Lapack: https://github.com/Reference-LAPACK/lapack.git
• oneTBB: https://github.com/oneapi-src/oneTBB.git
• oneMKL: https://github.com/oneapi-src/oneMKL.git
• oneDNN: https://github.com/oneapi-src/oneDNN.git