SOFIE-ALPAKA

Kernels for heterogeneous architectures written in Alpaka (An Abstraction Library for Parallel Kernel Acceleration) for SOFIE (System for Optimised Fast Inference code Emit).

This repository does not depend on SOFIE, but these kernels will eventually go into SOFIE.

Submission for CS-433: Machine Learning; hopefully, will not stay just as a random course project, but will become a part of the actual ML code written at CERN.

Dependencies

• Alpaka (1.2.0): for heterogenous kernels; present as a git submodule in external/
• Boost (libboost-all-dev on Debian): for Alpaka
• cmake and make: for building and testing the project

Usage

Clone the repository with all the submodules (dependencies):

git clone https://github.com/Saransh-cpp/SOFIE-ALPAKA --recursive

Building kernels and tests on a threaded CPU

To build all kernels and tests in bin/:

make all

Running tests on a threaded CPU

To run all kernel tests (and build if not built before):

make test

Building kernels and tests on an NVIDIA GPU

To build all the kernels and tests in build/

cmake -S. -Bbuild
cmake --build build

where the following flags can be configured by the user:

• CUDA_BASE (default: "/usr/local/cuda-13.1"): CUDA base path
• TBB_BASE (default: "/usr"): TBB base path
• ALPAKA_BASE (default: "external/alpaka"): Alpaka base path
• CUDA_ARCH (default: "sm_75"): CUDA architecture
• CMAKE_CUDA_COMPILER (default: "/usr/local/cuda-13.1/bin/nvcc"): Cuda compiler path

Running integration tests on an NVIDIA GPU

To run SOFIE integration tests:

cd tests/sofie_integration
cmake -S. -Bbuild
cmake --build build

with the same configurable flags listed in the section above.