# MKL FFTΒΆ

The speed-boosted variants of NumPy’s FFT operations are accessible in the `numpy.fft` package, and the `accelerate.mkl.fftpack` package. The following functions in these packages are accelerated using MKL:

Function Description
`fft(a, n=None, axis=-1)` 1-dimensional forward transform
`ifft(a, n=None, axis=-1)` 1-dimensional inverse transform
`rfft(a, n=None, axis=-1)` 1-dimensional forward transform of purely real data
`irfft(a, n=None, axis=-1)` 1-dimensional inverse transform of purely real data
`hfft(a, n=None, axis=-1)` Hermite transform
`ihfft(a, n=None, axis=-1)` Inverse Hermite transform
`fftn(a, s=None, axes=None)` N-dimensional forward transform
`ifftn(a, s=None, axes=None)` N-dimensional inverse transform
`fft2(a, s=None, axes=(-2, -1))` 2-dimensional forward transform
`ifft2(a, s=None, axes=(-2, -1))` 2-dimensional inverse transform
`rfftn(a, s=None, axes=None)` N-dimensional forward transform of purely real data
`rfft2(a, s=None, axes=(-2, -1))` 2-dimensional forward transform of purely real data
`irfftn(a, s=None, axes=None)` N-dimensional inverse transform of purely real data
`irfft2(a, s=None, axes=(-2, -1))` 2-dimensional inverse transform of purely real data

For further information on these functions, please refer to the Numpy documentation: `numpy.fft`.