2013-03-17 20:37:19 +01:00
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Eigen 3 is a C++ template library for linear algebra: vectors, matrices, and
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related algorithms. It is:
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* Versatile. Eigen handles, without code duplication, and in a completely
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integrated way:
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o both fixed-size and dynamic-size matrices and vectors.
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o both dense and sparse (the latter is still experimental) matrices and
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vectors.
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o both plain matrices/vectors and abstract expressions.
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o both column-major (the default) and row-major matrix storage.
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o both basic matrix/vector manipulation and many more advanced, specialized
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modules providing algorithms for linear algebra, geometry, quaternions,
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or advanced array manipulation.
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* Fast.
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o Expression templates allow to intelligently remove temporaries and enable
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lazy evaluation, when that is appropriate -- Eigen takes care of this
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automatically and handles aliasing too in most cases.
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o Explicit vectorization is performed for the SSE (2 and later) and AltiVec
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instruction sets, with graceful fallback to non-vectorized code.
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Expression templates allow to perform these optimizations globally for
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whole expressions.
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o With fixed-size objects, dynamic memory allocation is avoided, and the
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loops are unrolled when that makes sense.
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o For large matrices, special attention is paid to cache-friendliness.
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2013-04-08 20:29:37 +02:00
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* Elegant. The API is extremely clean and expressive, thanks to expression
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templates. Implementing an algorithm on top of Eigen feels like just copying
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pseudocode. You can use complex expressions and still rely on Eigen to
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produce optimized code: there is no need for you to manually decompose
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expressions into small steps.
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* Compiler-friendy. Eigen has very reasonable compilation times at least with
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GCC, compared to other C++ libraries based on expression templates and heavy
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metaprogramming. Eigen is also standard C++ and supports various compilers.
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