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  <title>Ginkgo</title>

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		<p>Ginkgo is a high-performance linear algebra library for
			manycore systems, with a focus on solution of sparse linear systems.
			It is implemented using modern C++ (you will need at least a C++17
			compliant compiler to build it), with GPU kernels implemented in
			CUDA (for NVIDIA devices), HIP (for AMD devices) and SYCL/DPC++ (for
			Intel devices and other supported hardware).</p>
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					<h2>High Performance</h2>
					<p>Competitive performance on state-of-the-art hardware architectures.</p>
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							href="https://ginkgo-project.github.io/gpe/"
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					<h2>Cross Platform</h2>
					<p>Ginkgo supports execution on CUDA, HIP and SYCL accelerators, and OpenMP-enabled devices.</p>
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						<a class="btn btn-ginkgo-orange-1"
							href="https://ginkgo-project.github.io/ginkgo-generated-documentation/doc/develop/"
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					<h2>Collaborative Effort</h2>
					<p>Collaborative open-source effort with a permissive license.</p>
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							href="https://github.com/ginkgo-project/ginkgo/blob/develop/LICENSE"
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					<h2>Tutorials</h2>
					<p>Check out some tutorials.</p>
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							href="https://github.com/ginkgo-project/ginkgo/wiki/Tutorial:-Building-a-Poisson-Solver"
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					<h2>Extensibility</h2>
					<p>Easily integrate new solvers, matrix formats, loggers, stopping criteria for your application.</p>
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							href="https://github.com/ginkgo-project/ginkgo/wiki/Tutorial-9:-Customize:-Loggers"
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					<h2>Get Involved</h2>
					<p>Discuss library features, issues, and extensions.</p>
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