Building MatX

Requirements

• CUDA 11.4

• g++ 9.0 or above

Unit tests

pybind11 source build and installed Python3 includes (python3-dev package)

Multi GPU

NvSHMEM

Building

While the MatX library does not require compiling, building unit tests, benchmarks, or examples must be compiled. To build all components, issue the standard cmake build commands in a cloned repo:

mkdir build && cd build
cmake ..
make -j

Unit tests and examples are built by default. Documentation building is disabled by default. To disable specific builds, use the cmake properties with the OFF flag: BUILD_EXAMPLES BUILD_TESTS For example, to disable unit test building:

mkdir build && cd build
cmake -DBUILD_TESTS=OFF ..
make -j

To build documentation use the cmake flag -DBUILD_DOCS=ON

Unit tests

MatX contains a suite of unit tests to test functionality of the primitive functions, plus other signal processing pipelines. Due to the nature of certain unit tests, the amount of data used as input and output for comparison can get quite large, and as a result, test vectors are generated dynamically using Python. Version 2.6.2 of the pybind11 library is required to be built and installed before building the MatX unit tests. Once built, the MatX build system will try to find pybind11 in common installation directories. If it cannot be found, it may be specified manually by passing the pybind11_DIR CMake parameter:

cmake -Dpybind11_DIR=/matx_libs/pybind11

To run the unit tests, from the cmake build directory run:

make -j test

This will execute all unit tests defined. If you wish to execute a subset of tests, or run with different options, you may run test/matx_test directly with parameters defined by Google Test (https://github.com/google/googletest). To run matx_test directly, you must be inside the build/test directory for the correct paths to be set. For example, to run only tests with the name FFT:

cd build/test
./matx_test --gtest_filter="*FFT*"

Benchmarks

MatX uses the NVBench software for the benchmarking framework. To run the benchmarks, you must have NVBench downloaded from https://github.com/NVIDIA/nvbench. When specifying the CMake parameters benchmarks can be enabled by:

cmake .. -DNVBENCH_DIR=/my/nvbench/dir -DBUILD_BENCHMARKS=ON

NVBench has a small library that will be compiled on the first make run. A binary called matx_bench will be produced inside of build/bench, and all parameters to the binary can be found in the NVBench documentation.

Multi-GPU Support

MatX examples and unit tests can be compiled with multi-GPU support using the NVSHMEM library. NVSHMEM must be compiled and/or installed before building MatX with multi-GPU support. The build system will look in common locations for NVSHMEM libraries and include files, but the installation directory can be overridden on the cmake configuration:

cmake -DMULTI_GPU=ON -DNVSHMEM_DIR=/usr/local/nvshmem ..

If nvshmem is detected properly, you will see a message similar to the following during cmake:

-- Found Nvshmem: /usr/local/nvshmem/lib/libnvshmem.a