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<h1>About</h1>
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<p>We have a <a href="https://github.com/OpenMathLib/OpenBLAS/discussions/">GitHub discussions</a> forum to discuss usage and development of OpenBLAS. We also have a <a href="https://groups.google.com/forum/#!forum/openblas-users">Google group for <em>users</em></a> and a <a href="https://groups.google.com/forum/#!forum/openblas-dev">Google group for <em>development of</em></a> OpenBLAS. </p>
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<h2 id="donations">Donations</h2>
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<p>You can read OpenBLAS statement of receipts and disbursement and cash balance on <a href="https://docs.google.com/spreadsheet/ccc?key=0AghkTjXe2lDndE1UZml0dGpaUzJmZGhvenBZd1F2R1E&usp=sharing">google doc</a>. A backer list is available <a href="https://github.com/OpenMathLib/OpenBLAS/blob/develop/BACKERS.md">on GitHub</a>.</p>
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<p>We welcome the hardware donation, including the latest CPU and boards.</p>
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<h2 id="acknowledgements">Acknowledgements</h2>
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<p>This work is partially supported by
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* Research and Development of Compiler System and Toolchain for Domestic CPU, National S&T Major Projects: Core Electronic Devices, High-end General Chips and Fundamental Software (No.2009ZX01036-001-002)
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* National High-tech R&D Program of China (Grant No.2012AA010903)</p>
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<h2 id="users-of-openblas">Users of OpenBLAS</h2>
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<ul>
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<li><a href='http://julialang.org/'>Julia - a high-level, high-performance dynamic programming language for technical computing</a><br /></li>
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<li>Ceemple v1.0.3 (C++ technical computing environment), including OpenBLAS, Qt, Boost, OpenCV and others. The only solution with immediate-recompilation of C++ code. Available from <a href='http://www.ceemple.com'>Ceemple C++ Technical Computing</a>.</li>
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<li><a href="https://github.com/fommil/netlib-java">netlib-java</a> and various upstream libraries, allowing OpenBLAS to be used from languages on the Java Virtual Machine.</li>
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</ul>
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<!-- TODO: academia users, industry users, hpc centers deployed openblas, etc. -->
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<h2 id="publications">Publications</h2>
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<h3 id="2013">2013</h3>
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<ul>
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<li>Wang Qian, Zhang Xianyi, Zhang Yunquan, Qing Yi, <strong>AUGEM: Automatically Generate High Performance Dense Linear Algebra Kernels on x86 CPUs</strong>, In the International Conference for High Performance Computing, Networking, Storage and Analysis (SC'13), Denver CO, November 2013. [<a href="http://xianyi.github.io/paper/augem_SC13.pdf">pdf</a>]</li>
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</ul>
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<h3 id="2012">2012</h3>
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<ul>
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<li>Zhang Xianyi, Wang Qian, Zhang Yunquan, <strong>Model-driven Level 3 BLAS Performance Optimization on Loongson 3A Processor</strong>, 2012 IEEE 18th International Conference on Parallel and Distributed Systems (ICPADS), 17-19 Dec. 2012.</li>
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</ul>
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