Sketching-based Distributed Matrix Computations for Machine Learning
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CMake CMAKE KISSFFT_SOURCE_FILES removed Nov 21, 2016
algorithms Accelerated linear regresion adapted to use KissFFT Nov 11, 2016
capi CMAKE KISSFFT_SOURCE_FILES removed Nov 21, 2016
conda removed xdata feature Jan 16, 2017
examples ${KISSFFT_SOURCE_FILES} removed form CMAke fiels Dec 7, 2016
nla Updating... still need to be tested Nov 22, 2016
notebooks running libskylark in softlayer cloud clusters Feb 6, 2017
python-skylark marked as version 0.20 Dec 22, 2016
script Merge branch 'travis-doc-deploy' Jan 30, 2017
sketch #if SKYLARK_HAVE_KISSFFT added to sketch files Nov 16, 2016
tests travis: add build scripts Aug 29, 2016
utility Throwing exception when applying DCT III Dec 7, 2016
vagrant Elemental 0.87.4 Nov 26, 2016
.gitignore cpp examples: Fixing the c++ examples (Cmake, kernel_regression...) Sep 6, 2016
CLA.txt Adding CLA file Dec 25, 2014
CMakeLists.txt add contributing doc Nov 19, 2015
LICENSE restructure readme, bump year Jan 19, 2016 README: add travis build status Aug 30, 2016 SKYLARK_HAVE_KISSFFT variable defined in Nov 2, 2016


Build Status

This is a distribution of libSkylark: an open source software library for distributed randomized numerical linear algebra with applications to machine learning and statistical data analysis.

Note that this software stack is currently under development, its features are still experimental.

Join the slack channel for questions and feedback.

Getting Started

Please see the docs for compile and installation instructions.


Instructions for contributing to libSkylark can be found in


(c) IBM Corporation, 2016 This program and the accompanying materials are made available under the terms of the Apache License, Version 2.0 which is available at


This project is supported from the XDATA program of the Defense Advanced Research Projects Agency (DARPA), administered through Air Force Research Laboratory.