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C GPU Dataframe Library

License: Apache License 2.0

CMake 0.89% Shell 1.27% C++ 39.42% C 0.48% Python 24.87% Cuda 33.07%

libgdf's Introduction

libgdf: GPU Dataframes

libgdf is a C library for implementing common functionality for a GPU Data Frame. For more project details, see the wiki.

Development Setup

The following instructions are tested on Linux and OSX systems.

Compiler requirement:

  • gcc 4.8 (required to be ABI compatible with libarrow).

Get dependencies

It is recommended to setup a conda environment for the dependencies.

# create the conda environment (assuming in build directory)
$ conda env create --name libgdf_dev --file ../conda_environments/dev_py35.yml
# activate the environment
$ source activate libgdf_dev

This installs the required cmake, flatbuffers into the libgdf_dev conda environment and activates it.

For additional information, the python cffi wrapper code requires cffi and pytest. The testing code requires numba and cudatoolkit as an additional dependency. All these are installed from the previous commands.

The environment can be updated from ../conda_environments/dev_py35.yml as development includes/changes the depedencies. To do so, run:

$ conda env update --name libgdf_dev --file ../conda_environments/dev_py35.yml

Configure and build

This project uses cmake for building the C/C++ library. To configure cmake, run:

mkdir build   # create build directory for out-of-source build
cd build      # enter the build directory
cmake ..      # configure cmake

To build the C/C++ code, run make. This should produce a shared library named libgdf.so or libgdf.dylib.

Link python files into the build directory

To make development and testing more seamless, the python files and tests can be symlinked into the build directory by running make copy_python. With that, any changes to the python files are reflected in the build directory. To rebuild the libgdf, run make again.

Run tests

Currently, all tests are written in python with py.test. A make target is available to trigger the test execution. In the build directory (and with the conda environment activated), run below to exceute test:

make pytest   # this auto trigger target "copy_python"

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