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AOCL Data Analytics Library

The AOCL Data Analytics Library (AOCL-DA) is a data analytics library providing optimized building blocks for data analysis. It is written with a C-compatible interface to make it as seamless as possible to integrate with the library from whichever programming language you are using. For further details on the library contents, please refer to the online help or PDF user guide.

The intended workflow for using the library is as follows:

  • load data from memory by reading CSV files or using the in-built da_datastore object

  • pre-process the data by removing missing values, standardizing, and selecting certain subsets of the data, before extracting contiguous arrays of data from the da_datastore objects

  • data processing (e.g. principal component analysis, linear model fitting, etc.)

C++ example programs can be found in the examples folder of your installation.

AOCL-DA is developed and maintained by AMD. For support or queries, you can email us on [email protected].

Building the Library

AOCL-DA is built with CMake, with supported compilers GNU and AOCC on Linux and MSVC on MS Windows.

AOCL-DA is dependent on AOCL-BLAS, AOCL-LAPACK, AOCL-Sparse and AOCL-Utils.

Building on Linux

  1. You will need to have BLAS, LAPACK, AOCL-Sparse and AOCL-Utils installed.

  2. Make sure you have set the environment variable $AOCL_ROOT to where the AOCL libraries are installed e.g. /home/username/amd/aocl/5.0.

  3. Configure cmake with any of the following options:

    • -DMEMSAN=On for memory sanitization

    • -DASAN=On for address sanitization

    • -DVALGRIND=On for valgrind use

    • -DBUILD_ILP64=On for 64-bit integer build

    • -DCMAKE_BUILD_TYPE=Debug or Release

    • -DCOVERAGE=On to build code coverage report

    • -DBUILD_EXAMPLES=On and –DBUILD_GTEST=On both of which are On by default

    • -DBUILD_SHARED_LIBS=On for a shared library build (Off by default)

    • -DARCH=<arch> to set the -march=<arch> flag, where <arch> specifies the architecture to build for, e.g. znver4

    • -DBUILD_DOC=On to build the documentation. Use cmake --build . --target doc to build all documentation formats (or doc_pdf, doc_html to build only PDF or only HTML formats)

    • -DINTERNAL_DOC=On to build the internal documentation alongside the main one

    • -DBUILD_SMP=On to build using OpenMP and threaded BLAS (On by default)

    • -DVECTORIZATION_REPORTS=On to build with vectorization reports enabled

    • -DDA_LOGGING=On to enable debug printing

    • -DBUILD_PYTHON=On to build the Python interfaces

    • -DCMAKE_AOCL_ROOT=<path to AOCL> to specify a location for AOCL libraries. This has precedence over the environment variable $AOCL_ROOT

    • -DCMAKE_INSTALL_PREFIX=<install path> to specify the install path for the library

    • Any combination of -DLAPACK_LIB, -DBLAS_LIB, -DSPARSE_LIB, -DUTILS_LIB, -DUTILS_CPUID_LIB, -DLAPACK_INCLUDE_DIR and -DBLAS_INCLUDE_DIR if you wish to override the use of AOCL_ROOT with specific choices of BLAS/LAPACK/Sparse libraries and include directories. Care should be taken if you do this as there will be no checks for the correctness of the linked libraries.

    Note that not all the options available in Release build mode.

  4. Type cmake --build . --target all (or --target doc, to build the documentation).

  5. Run the tests or examples using ctest e.g. ctest -V –R followed by a string to find a particular set of tests.

Building on MS Windows

  1. You will need either:

    • a Visual Studio installation and compatible Fortran compiler (this will allow you to build with cl or with the MSVC compatibility layer for clang (clang-cl)).
    • GCC and gfortran compilers, which are available via MinGW and MSYS2.

  2. Make sure you have set the AOCL_ROOT environment variable to your AOCL installation directory (e.g. C:\Users\username\AOCL-4.0), and update your PATH to take in the relevant BLAS and LAPACK libraries e.g. set PATH=C:\path\to\AOCL\amd-blis\lib\LP64;C:\path\to\AOCL\amd-libflame\lib\LP64;C:\path\to\AOCL\amd-sparse\lib\LP64\shared;%PATH%.

  3. Configure cmake with any of the following options:

    • -DBUILD_ILP64=On for 64-bit integer build

    • -DBUILD_EXAMPLES=On and –DBUILD_GTEST=On both of which are on by default

    • -DBUILD_SMP=On to build using OpenMP and threaded BLAS (On by default)

    • -DBUILD_SHARED_LIBS=On for a shared library build (Off by default)

    • -DARCH=<arch> to set the /arch:<arch> flag, where <arch> specifies the architecture to build for, e.g. AVX512

    • -DCMAKE_AOCL_ROOT=<path to AOCL> if you wish to specify a location for AOCL libraries without using environment variables

    • Any combination of -DLAPACK_LIB, -DBLAS_LIB, -DSPARSE_LIB, -DUTILS_LIB, -DUTILS_CPUID_LIB, -DLAPACK_INCLUDE_DIR and -DBLAS_INCLUDE_DIR if you wish to override the use of AOCL_ROOT with specific choices of BLAS/LAPACK/Sparse libraries and include directories. Care should be taken if you do this as there will be no checks for the correctness of the linked libraries.

    Note that not all the options available in Linux are available in Windows

  4. Either:

    • Open Visual Studio and load the AOCL-DA.sln file then build Debug or Release builds using the GUI, or

    • In a powershell type devenv .\AOCL-DA.sln /build "Debug" to build the solution (change to Release as appropriate)

    • If using the GNU toolchain, build using cmake and Ninja.

Building the Python interfaces

To build the Python interfaces, use -DBUILD_PYTHON=On (note that this will only work with shared library builds). You will need PyBind11, which can be installed using pip install pybind11. By default, cmake will compile the bindings but will not install them. If you set -DCMAKE_INSTALL_PREFIX=<install path> in your configure step and run cmake --build . --target install, then cmake will also create a Python wheel, aoclda-*.whl, where * depends on your system. This wheel can be installed using pip install aoclda-*.whl.

On Windows you may also need to set the CMAKE_PREFIX_PATH to point to the location of you pybind11 installation, e.g. C:\path\to\your\python-environment\site-packages\pybind11\share\cmake\pybind11. When using the bindings on Windows, the Intel Fortran runtime must be available. This can be done by setting the environment variable INTEL_FCOMPILER.