DPPL proof-of-concept backend for NUMBA to support compilation for Intel CPU and GPU architectures. The present implementation of DPPL is based on OpenCL 2.1, but is likely to change in the future to rely on Sycl/DPC++ or Intel Level-0 driver API.

• Bash : In the system and not as default Shell
• Tar : To extract files
• Git : To fetch required dependencies listed below
• C/C++ compiler : To build the dependencies
• Cmake : For managing build process of dependencies
• Python3 : Version 3 is required
• Conda or miniconda : Can be found at https://docs.conda.io/en/latest/miniconda.html
• OpenCL 2.1 driver : DPPL currently works for both Intel GPUs and CPUs is a correct OpenCL driver version is found on the system.

Note. To use the GPU users should be added to "video" user group on Linux systems.

• NUMBA v0.50 : The DPPL backend has only been tested for NUMBA v0.50. The included install script downloads and applies the DDPy patch to the correct NUMBA version.
• LLVM-SPIRV translator: Used for SPIRV generation from LLVM IR.
• LLVMDEV : To support LLVM IR generation.
• Others : All existing dependecies for NUMBA, such as llvmlite, also apply to DPPL.

Make sure the following dependencies of NUMBA-PyDPPL are installed in your conda environemtn:

• llvmlite =0.33
• pydppl =0.2
• spirv-tools
• llvm-spirv
• llvmdev

Make sure the dependencies are installed with consistent version of LLVM 10.

NUMBA-PyDPPL also depend on PyDPPL backend. It can be found here. Please run build_for_develop.sh to install PyDPPL backend in development mode or install PyDPPL from package.

After all the dependencies are installed please run build_for_develop.sh to get a local installation of NUMBA-PyDPPL.

To make sure the installation was successful, try running the examples and the test suite:

$PATH_TO_NUMBA-PyDPPL/numba/dppl/examples/

To run the test suite execute the following:

`bash python -m numba.runtests numba.dppl.tests `

Refer the HowTo.rst guide for an overview of the programming semantics, examples, supported functionalities, and known issues.

• Installing while Intel OneAPI basekit is actvated have shown to throw error

while installation of NUMBA-PyDPPL because of incompatible TBB interface, one way around that is to temporaily move env variable TBBROOT to something else*

Please use https://github.com/IntelPython/numba/issues to report issues and bugs.