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<!DOCTYPE html>
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<li class="toctree-l1"><a class="reference internal" href="index.html">SmallK</a></li>
<li class="toctree-l1"><a class="reference internal" href="pages_about.html">1. About</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_about.html#distributed-versions">1.1. Distributed Versions</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_about.html#ground-truth-data-for-graph-clustering-and-community-detection">1.2. Ground truth data for graph clustering and community detection</a></li>
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<li class="toctree-l1"><a class="reference internal" href="pages_introduction.html">2. Introduction</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_introduction.html#background">2.1. Background</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_introduction.html#constrained-low-rank-approximations-and-nmf">2.2. Constrained low rank approximations and NMF</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_introduction.html#smallk-overview">2.3. SmallK Overview</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_introduction.html#prerequisites">2.4. Prerequisites</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_quickstartInstall.html#vagrant-virtual-machine">3.1. Vagrant Virtual Machine</a></li>
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<li class="toctree-l1"><a class="reference internal" href="pages_quickstartSmallkAPI.html">4. Quickstart - Smallk API</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_quickstartSmallkAPI.html#introduction">4.1. Introduction</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_quickstartSmallkAPI.html#c-project-setup">4.2. C++ Project Setup</a></li>
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<li class="toctree-l3"><a class="reference internal" href="pages_quickstartSmallkAPI.html#nmf-initialization">4.4.3. NMF Initialization</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_quickstartSmallkAPI.html#hierarchical-clustering">4.5. Hierarchical Clustering</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_quickstartSmallkAPI.html#disclaimer">4.7. Disclaimer</a></li>
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<li class="toctree-l3"><a class="reference internal" href="pages_installation.html#id1">5.1.1. Elemental</a><ul>
<li class="toctree-l4"><a class="reference internal" href="pages_installation.html#how-to-install-elemental-on-macosx">5.1.1.1. How to Install Elemental on MacOSX</a><ul>
<li class="toctree-l5"><a class="reference internal" href="pages_installation.html#osx-install-the-latest-gnu-compilers">5.1.1.1.1. OSX:Install the latest GNU compilers</a></li>
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<li class="toctree-l5"><a class="reference internal" href="pages_installation.html#linux-install-the-latest-gnu-compilers">5.1.1.2.1. Linux:Install the latest GNU compilers</a></li>
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<li class="toctree-l3"><a class="reference internal" href="pages_installation.html#obtain-the-source-code">5.2.1. Obtain the Source Code</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_installation.html#build-the-smallk-library">5.2.2. Build the SmallK library</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_installation.html#install-the-smallk-library">5.2.3. Install the SmallK library</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_installation.html#check-the-build-and-installation">5.2.4. Check the build and installation</a></li>
</ul>
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<li class="toctree-l2"><a class="reference internal" href="pages_installation.html#build-and-installation-of-pysmallk-shared-library">5.3. Build and Installation of pysmallk shared library</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_installation.html#matrix-file-formats">5.4. Matrix file formats</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_installation.html#disclaimer">5.5. Disclaimer</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_installation.html#contact-info">5.6. Contact Info</a></li>
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<li class="toctree-l1"><a class="reference internal" href="pages_commandLineTools.html">6. Command Line Tools</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_commandLineTools.html#introduction">6.1. Introduction</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_commandLineTools.html#preprocessor">6.2. Preprocessor</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#overview">6.2.1. Overview</a></li>
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<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#command-line-options">6.2.3. Command Line Options</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#sample-runs">6.2.4. Sample Runs</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_commandLineTools.html#matrixgen">6.3. Matrixgen</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id1">6.3.1. Overview</a></li>
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<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id3">6.3.3. Sample Runs</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_commandLineTools.html#nonnegative-matrix-factorization-nmf">6.4. Nonnegative Matrix Factorization (NMF)</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id4">6.4.1. Overview</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id5">6.4.2. Command Line Options</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id6">6.4.3. Sample Runs</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_commandLineTools.html#hierclust">6.5. Hierclust</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id7">6.5.1. Overview</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id9">6.5.2. Command Line Options</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id10">6.5.3. Sample Runs</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_commandLineTools.html#flatclust">6.6. Flatclust</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id12">6.6.1. Overview</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id13">6.6.2. Command Line Options</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_commandLineTools.html#id14">6.6.3. Sample Runs</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pages_smallkAPI.html#examples-of-api-usage">7.1. Examples of API Usage</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_smallkAPI.html#smallk-api">7.2. SmallK API</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_smallkAPI.html#enumerations">7.2.1. Enumerations</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_smallkAPI.html#api-functions">7.2.2. API functions</a><ul>
<li class="toctree-l4"><a class="reference internal" href="pages_smallkAPI.html#initialization-and-cleanup">7.2.2.1. Initialization and cleanup</a></li>
<li class="toctree-l4"><a class="reference internal" href="pages_smallkAPI.html#versioning">7.2.2.2. Versioning</a></li>
<li class="toctree-l4"><a class="reference internal" href="pages_smallkAPI.html#common-functions">7.2.2.3. Common functions</a></li>
<li class="toctree-l4"><a class="reference internal" href="pages_smallkAPI.html#nmf-functions">7.2.2.4. NMF functions</a></li>
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<li class="toctree-l1"><a class="reference internal" href="pages_pysmallkAPI.html">8. Pysmallk API (Python)</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_pysmallkAPI.html#introduction">8.1. Introduction</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_pysmallkAPI.html#examples-of-pysmallk-usage">8.2. Examples of Pysmallk Usage</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_pysmallkAPI.html#pysmallk-functions">8.3. Pysmallk Functions</a><ul>
<li class="toctree-l3"><a class="reference internal" href="pages_pysmallkAPI.html#preprocessor">8.3.1. Preprocessor</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_pysmallkAPI.html#matrixgen">8.3.2. Matrixgen</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_pysmallkAPI.html#smallkapi">8.3.3. SmallkAPI</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_pysmallkAPI.html#flatclust">8.3.4. Flatclust</a></li>
<li class="toctree-l3"><a class="reference internal" href="pages_pysmallkAPI.html#hierclust">8.3.5. Hierclust</a></li>
</ul>
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<li class="toctree-l1"><a class="reference internal" href="pages_tests.html">9. Tests</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_tests.html#smallk-test-results">9.1. SmallK Test Results</a></li>
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<li class="toctree-l1"><a class="reference internal" href="pages_benchmarks_results.html">10. Benchmarks and Results</a></li>
<li class="toctree-l1"><a class="reference internal" href="pages_publications.html">11. Publications</a></li>
<li class="toctree-l1"><a class="reference internal" href="pages_software_repo.html">12. Software Repo</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pages_software_repo.html#getting-the-code-and-instructions">12.1. Getting the code and instructions</a></li>
<li class="toctree-l2"><a class="reference internal" href="pages_software_repo.html#contact-info">12.2. Contact Info</a></li>
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<div class="section" id="introduction-to-smallk">
<h1>Introduction to SmallK<a class="headerlink" href="#introduction-to-smallk" title="Permalink to this headline">¶</a></h1>
<p>SmallK is a high performance software package for low rank matrix approximation via the nonnegative matrix factorization (NMF). NMF is a constrained low rank approximation where a matrix is approximated by a product of two nonnegative factors. The role of NMF in data analytics has been as significant as the singular value decomposition (SVD). However, due to nonnegativity constraints, NMF has far superior interpretability of its results for many practical problems such as image processing, chemometrics, bioinformatics, topic modeling for text analytics and many more. Our approach to solving the NMF nonconvex optimization
problem has proven convergence properties and is one of the most efficient methods developed to date.</p>
</div>
<div class="section" id="distributed-versions">
<h1>Distributed Versions<a class="headerlink" href="#distributed-versions" title="Permalink to this headline">¶</a></h1>
<p>Recently open sourced: MPI-FAUN! Both MPI and OPENMP implementations for MU, HALS and ANLS/BPP based NMF algorithms are now available. The implementations can run off the shelf or can be easily integrated into other source code. These are very highly tuned NMF algorithms to work on super computers. We have tested this software in NERSC as well OLCF cluster. The openmp implementation is tested on many different linux variants with intel processors. The library works well for both sparse and dense matrices.</p>
<p>Please visit <a class="reference external" href="https://github.com/ramkikannan/nmflibrary">MPI-FAUN</a> for more information and source code.</p>
</div>
<div class="section" id="ground-truth-data-for-graph-clustering-and-community-detection">
<h1>Ground truth data for graph clustering and community detection<a class="headerlink" href="#ground-truth-data-for-graph-clustering-and-community-detection" title="Permalink to this headline">¶</a></h1>
<p>Community discovery is an important task for revealing structures in large networks. The massive size of contemporary social networks poses a tremendous challenge to the scalability of traditional graph clustering algorithms and the evaluation of discovered communities.</p>
<p>Our methodology uses a divide-and-conquer strategy to discover hierarchical community structure, non-overlapping within each level. Our algorithm is based on the highly efficient Rank-2 Symmetric Nonnegative Matrix Factorization. We solve several implementation challenges to boost its efficiency on modern CPU architectures, specifically for very sparse adjacency matrices that represent a wide range of social networks. Empirical results have shown that our algorithm has competitive overall efficiency, and that the non-overlapping communities found by our algorithm recover the ground-truth communities better than state-of-the-art algorithms for overlapping
community detection.</p>
<p>Please visit <a class="reference external" href="https://github.com/smallk/smallk_data/tree/master/dblp_ground_truth">dblp ground truth data</a> to obtain the data.</p>
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<div class="section" id="acknowledgements">
<h1>Acknowledgements<a class="headerlink" href="#acknowledgements" title="Permalink to this headline">¶</a></h1>
<p>This work was funded in part by the DARPA XDATA program under contract FA8750-12-2-0309. Our DARPA program manager is <a class="reference external" href="http://www.darpa.mil/staff/mr-wade-shen">Mr. Wade Shen</a> and our XDATA Principal Investigator is <a class="reference external" href="http://www.cc.gatech.edu/~hpark/">Prof. Haesun Park</a> of the Georgia Institute of Technology. We would like to thank Rundong Du for the dblp ground truth data set and Dr. Ramakrishnan Kannan of ORNL for the MPI-FAUN! distributed code. Also, special thanks to Dr. Richard Boyd, Dr. Da Kuang, and Ashley Scripka-Beavers for their contributions to previous versions of this documentation and significant technical contributions. A final special thanks to Ethan Trewhitt, who created the Docker install and advised on how to use Sphinx and RTD for documentation.</p>
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<div class="section" id="copyright-and-software-license">
<h1>Copyright and Software License<a class="headerlink" href="#copyright-and-software-license" title="Permalink to this headline">¶</a></h1>
<p>SmallK is under copyright by the Georgia Institute of Technology, 2017. All source code is released under the <a class="reference external" href="http://www.apache.org/licenses/LICENSE-2.0">Apache 2.0</a> license.</p>
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