*** Intel® Scalable Dataframe Compiler***

Intel Scalable Dataframe Compiler (Intel® SDC) scales analytics/ML codes in Python to bare-metal cluster/cloud performance automatically. It compiles a subset of Python (Pandas/Numpy) to efficient parallel binaries with MPI, requiring only minimal code changes. Intel SDC is orders of magnitude faster than alternatives like Apache Spark.

Intel SDC's documentation can be found here.

conda install -c intel -c intel/label/test sdc

Here is a Pi calculation example in Intel SDC:

import sdc
import numpy as np
import time

@sdc.jit
def calc_pi(n):
    t1 = time.time()
    x = 2 * np.random.ranf(n) - 1
    y = 2 * np.random.ranf(n) - 1
    pi = 4 * np.sum(x**2 + y**2 < 1) / n
    print("Execution time:", time.time()-t1, "\nresult:", pi)
    return pi

calc_pi(2 * 10**8)

Save this in a file named pi.py and run (on 8 cores):

mpiexec -n 8 python pi.py

This should demonstrate about 100x speedup compared to regular Python version without @sdc.jit and mpiexec.

These academic papers describe the underlying methods in Intel SDC:

• HPAT paper at ICS'17
• HPAT at HotOS'17
• HiFrames on arxiv

Building Intel® SDC from Source on Linux ----------------------------------

We use Anaconda distribution of Python for setting up Intel SDC build environment.

If you do not have conda, we recommend using Miniconda3:

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
chmod +x miniconda.sh
./miniconda.sh -b
export PATH=$HOME/miniconda3/bin:$PATH

It is possible to build Intel SDC via conda-build or setuptools. Follow one of the cases below to install Intel SDC and its dependencies on Linux.

Building on Linux with conda-build ~~~~~~~~~~~~~~~~~~~~~~~~~ :

PYVER=<3.6 or 3.7>
conda create -n CBLD python=$PYVER conda-build
source activate CBLD
git clone https://github.com/IntelPython/sdc
cd sdc
# build Intel SDC
conda build --python $PYVER --override-channels -c numba -c conda-forge -c defaults buildscripts/sdc-conda-recipe

PYVER=<3.6 or 3.7>
conda create -n SDC -q -y -c numba -c conda-forge -c defaults numba mpich pyarrow=0.15.0 arrow-cpp=0.15.0 gcc_linux-64 gxx_linux-64 gfortran_linux-64 scipy pandas boost python=$PYVER
source activate SDC
git clone https://github.com/IntelPython/sdc
cd sdc
# build SDC
python setup.py install

In case of issues, reinstalling in a new conda environment is recommended.

Building Intel® SDC from Source on Windows ------------------------------------

Building Intel® SDC on Windows requires Build Tools for Visual Studio 2019 (with component MSVC v140 - VS 2015 C++ build tools (v14.00)):

• Install Build Tools for Visual Studio 2019 (with component MSVC v140 - VS 2015 C++ build tools (v14.00)).
• Install Miniconda for Windows.
• Start 'Anaconda prompt'

It is possible to build Intel SDC via conda-build or setuptools. Follow one of the cases below to install Intel SDC and its dependencies on Windows.

set PYVER=<3.6 or 3.7>
conda create -n CBLD -q -y python=%PYVER% conda-build conda-verify vc vs2015_runtime vs2015_win-64
conda activate CBLD
git clone https://github.com/IntelPython/sdc.git
cd sdc
conda build --python %PYVER% --override-channels -c numba -c defaults -c intel buildscripts\sdc-conda-recipe

conda create -n SDC -c numba -c defaults -c intel -c conda-forge python=<3.6 or 3.7> numba impi-devel pyarrow=0.15.0 arrow-cpp=0.15.0 scipy pandas boost
conda activate SDC
git clone https://github.com/IntelPython/sdc.git
cd sdc
set INCLUDE=%INCLUDE%;%CONDA_PREFIX%\Library\include
set LIB=%LIB%;%CONDA_PREFIX%\Library\lib
%CONDA_PREFIX%\Library\bin\mpivars.bat quiet
python setup.py install

• If the cl compiler throws the error fatal error LNK1158: cannot run 'rc.exe', add Windows Kits to your PATH (e.g. C:\Program Files (x86)\Windows Kits\8.0\bin\x86).
• Some errors can be mitigated by set DISTUTILS_USE_SDK=1.
• For setting up Visual Studio, one might need go to registry at HKEY_LOCAL_MACHINE\SOFTWARE\WOW6432Node\Microsoft\VisualStudio\SxS\VS7, and add a string value named 14.0 whose data is C:\Program Files (x86)\Microsoft Visual Studio 14.0\.
• Sometimes if the conda version or visual studio version being used are not latest then building Intel SDC can throw some vague error about a keyword used in a file. So make sure you are using the latest versions.

conda install h5py
python sdc/tests/gen_test_data.py
python -m unittest