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+
+namespace Eigen {
+
+/** \page TopicCUDA Using Eigen in CUDA kernels
+
+\b Disclaimer: this page is about an \b experimental feature in %Eigen.
+
+Staring from CUDA 5.0, the CUDA compiler, \c nvcc, is able to properly parse %Eigen's code (almost).
+A few adaptations of the %Eigen's code already allows to use some parts of %Eigen in your own CUDA kernels.
+To this end you need the devel branch of %Eigen, CUDA 5.0 or greater with GCC.
+
+Known issues:
+
+ - \c nvcc with MS Visual Studio does not work (patch welcome)
+ 
+ - \c nvcc with \c clang does not work (patch welcome)
+ 
+ - \c nvcc 5.5 with gcc-4.7 (or greater) has issues with the standard \c \<limits\> header file. To workaround this, you can add the following before including any other files:
+   \code
+    // workaround issue between gcc >= 4.7 and cuda 5.5
+    #if (defined __GNUC__) && (__GNUC__>4 || __GNUC_MINOR__>=7)
+      #undef _GLIBCXX_ATOMIC_BUILTINS
+      #undef _GLIBCXX_USE_INT128
+    #endif
+   \endcode
+   
+ - On 64bits system Eigen uses \c long \c int as the default type for indexes and sizes. On CUDA device, it would make sense to default to 32 bits \c int.
+   However, to keep host and CUDA code compatible, this cannot be done automatically by %Eigen, and the user is thus required to define \c EIGEN_DEFAULT_DENSE_INDEX_TYPE to \c int throughout his code (or only for CUDA code if there is no interaction between host and CUDA code through %Eigen's object).
+
+*/
+
+}