# Module: FFT#

Fast fourier transform related variables and subroutines.

Cluster distributed FFT

In intel MKL, the MPI slicing happens along the first dimension in C, or the last dimension in Fortran. Note, this is the most natural way to do the slicing, because you want to keep the contingent data in memory on the same core. In the Mu-PRO PhaseFieldSDK, since we also support thin-film boundary conditions in many of our solvers and in most cases x dimension is larger than z, thus it is not a good choice to slice along the Z direction. As a result, all of the real space allocated arrays in Mu-PRO PhaseFieldSDK is defined as (z, y, x) rather than (x, y, z), so that the slicing happens along the x dimension instead of z.

Important

FFT module is also the base for many other modules. You must call the mupro_fft_setup subroutine before you can use the solvers in the SDK.

Name

mod_mupro_fft

Depends on
Defined variables

None

Defined types

type_mupro_FFContext

Defined subroutines

## Defined Types#

### type_mupro_FFTContext#

Variable

Type

Meaning

Rn1

int32

Size of real space x dimension on the current core

Rn2

int32

Size of real space y dimension on the current core

Rn3

int32

Size of real space z dimension on the current core

Cn1

int32

Size of fourier space x dimension on the current core

Cn2

int32

Size of fourier space y dimension on the current core

Cn3

int32

Size of fourier space z dimension on the current core

lstart

int32

Starting index of the data along x on the current core

Important

MPI slicing in FFT only happens along the last dimension of Fortran array, so to have such slicing happens along the x direction, we have to define the x as the last dimension, y as the second to last, and so on. To give an example, the dimension for polarization is (3,z,y,x).

Note

Since MPI slicing happens along the last dimension of Fortran array (which is x in our convention), so $$\text{Rn3}=\text{nz}$$, $$\text{Rn2}=\text{ny}$$, $$\text{Rn1}\neq \text{nx}$$, and $$\text{lstartR} = \text{0}$$ for rank 0, and $$\text{lstartR}\neq \text{0}$$ for other ranks.

## Defined Subroutines#

### mupro_fft_setup#

Initialize cluster distributed FFT, so that we can use forward and backward functions afterwards.

call mupro_fft_setup(context)

Important

You must call this fft setup subroutine after mupro_size_setup and mupro_mpi_setup but before all other subroutines that involves 3D data.

Argument

Type(Intent)

Meaning

context

type_mupro_FFTContext, intent(OUT)

The initialized FFT system information

### mupro_fft_forward(real_space, fourier_space )#

Forward fft from real space to fourier space.

Argument

Type(Intent)

Meaning

real_space

real(kind=rdp),intent(in),dimension(Rn3,Rn2,Rn1)

Data in real space

fourier_space

complex(kind=rdp),intent(out),dimension(Cn3,Cn2,Cn1)

Data in fourier space

### mupro_fft_backward(fourier_space, real_space )#

Backward fft from fourier space to real space.

Argument

Type(Intent)

Meaning

fourier_space

complex(kind=rdp),intent(in),dimension(Cn3,Cn2,Cn1)

Data in fourier space

real_space

real(kind=rdp),intent(out),dimension(Rn3,Rn2,Rn1)

Data in real space

### mupro_fitted_derivative(data, derivative, order, direction)#

Calculate derivate of 3D data. This function can be called in both thin film and bulk cases. In the thin film case, due to the sudden change in data across the film interface and surface, a special fitting step is included, which is also why the subroutine is called mupro_fitted_derivative.

Argument

Type(Intent)

Meaning

data

real(kind=rdp),intent(in),dimension(Rn3,Rn2,Rn1)

Data in real space

derivate

real(kind=rdp),intent(out),dimension(3, Rn3,Rn2,Rn1 )

Derivative in real space, in the order of $$\frac{d}{dx}$$, $$\frac{d}{dy}$$, $$\frac{d}{dz}$$

order

integer,intent(in)

Order for the fitting along z direction in the thin film case, you can choose from 0 to 4

direction

integer,intent(in)

The direction to calculate derivative, 1: only $$\frac{d}{dx}$$, 2: only $$\frac{d}{dy}$$, 3: only $$\frac{d}{dz}$$, 4: all derivates, 5: $$\frac{d}{dx}$$ and $$\frac{d}{dy}$$

### mupro_fitted_curvature(data, curvature, order, direction)#

Calculate curvature of 3D data. This function can be called in both thin film and bulk cases. In the thin film case, due to the sudden change in data across the film interface and surface, a special fitting step is included, which is also why the subroutine is called mupro_fitted_curvature.

Argument

Type(Intent)

Meaning

data

real(kind=rdp),intent(in),dimension(Rn3,Rn2,Rn1)

Data in real space

derivate

real(kind=rdp),intent(out),dimension(6, Rn3,Rn2,Rn1 )

Curvature in real space, in the order of $$\frac{d^2}{dx^2}$$, $$\frac{d^2}{dy^2}$$, $$\frac{d^2}{dz^2}$$, $$\frac{d^2}{dydz}$$ , $$\frac{d^2}{dxdz}$$, $$\frac{d^2}{dxdy}$$

order

integer,intent(in)

Order for the fitting along z direction in the thin film case, you can choose from 0 to 4

direction

integer,intent(in)

The direction to calculate Curvature, 1 for $$\frac{d^2}{dxdy}$$, 2 for $$\frac{d^2}{dxdz}$$, 4 for $$\frac{d^2}{dydz}$$, 8 for $$\frac{d^2}{dz^2}$$, 16 for $$\frac{d^2}{dy^2}$$, 32 for $$\frac{d^2}{dx^2}$$. To request multiple second derivatives these numbers should be added together