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1 files changed, 6 insertions, 13 deletions
diff --git a/math/eigen2/DESCR b/math/eigen2/DESCR
index 38332b7f76d..f6a63080ae5 100644
--- a/math/eigen2/DESCR
+++ b/math/eigen2/DESCR
@@ -8,24 +8,17 @@ related algorithms. It is:
o both plain matrices/vectors and abstract expressions.
o both column-major (the default) and row-major matrix storage.
o both basic matrix/vector manipulation and many more advanced, specialized
- modules providing algorithms for linear algebra, geometry, quaternions,
- or advanced array manipulation.
+ modules providing algorithms for linear algebra, geometry, quaternions, or
+ advanced array manipulation.
* Fast.
o Expression templates allow to intelligently remove temporaries and enable
lazy evaluation, when that is appropriate -- Eigen takes care of this
automatically and handles aliasing too in most cases.
o Explicit vectorization is performed for the SSE (2 and later) and AltiVec
- instruction sets, with graceful fallback to non-vectorized code.
- Expression templates allow to perform these optimizations globally for
- whole expressions.
+ instruction sets, with graceful fallback to non-vectorized code. Expression
+ templates allow to perform these optimizations globally for whole
+ expressions.
o With fixed-size objects, dynamic memory allocation is avoided, and the
loops are unrolled when that makes sense.
o For large matrices, special attention is paid to cache-friendliness.
-* Elegant. The API is extremely clean and expressive, thanks to expression
- templates. Implementing an algorithm on top of Eigen feels like just copying
- pseudocode. You can use complex expressions and still rely on Eigen to
- produce optimized code: there is no need for you to manually decompose
- expressions into small steps.
-* Compiler-friendy. Eigen has very reasonable compilation times at least with
- GCC, compared to other C++ libraries based on expression templates and heavy
- metaprogramming. Eigen is also standard C++ and supports various compilers.
+...and more!