expand overview
@@ -22,9 +22,20 @@ The following is a brief overview of supported subset of NumPy interface:
- All operators with `broadcasting <https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html>`_
- All `universal functions <https://docs.scipy.org/doc/numpy/reference/ufuncs.html>`_
for elementwise operations (except those for complex numbers).
-- `Linear algebra functions <https://docs.scipy.org/doc/numpy/reference/routines.linalg.html>`_, including product (\ ``dot``, ``matmul``, etc.) and decomposition (\ ``cholesky``, ``svd``, etc.), accelerated by `cuBLAS <https://developer.nvidia.com/cublas>`_ and `cuSOLVER <https://developer.nvidia.com/cusolver>`.
+- `Linear algebra functions <https://docs.scipy.org/doc/numpy/reference/routines.linalg.html>`_, including product (\ ``dot``, ``matmul``, etc.) and decomposition (\ ``cholesky``, ``svd``, etc.), accelerated by `cuBLAS <https://developer.nvidia.com/cublas>`_ and `cuSOLVER <https://developer.nvidia.com/cusolver>`_.
+- Multi-dimensional fast Fourier transform (FFT), accelerated by `cuFFT <https://developer.nvidia.com/cufft>`_.
- Reduction along axes (``sum``, ``max``, ``argmax``, etc.)
+CuPy additionally supports a subset of SciPy features:
+
+- Sparse matrices and sparse linear algebra, powered by `cuSPARSE <https://developer.nvidia.com/cusparse>`_.
+- Multi-dimensional image processing
+- Signal processing
+- Fast Fourier transform (FFT)
+- Linear algebra functions
+- Special functions
+- Statistical functions
+
CuPy also includes the following features for performance:
- User-defined elementwise CUDA kernels
