File Meanmax.h

#include "General.h"
#include "Param.h"
#include "Arrays.h"
#include "Forcing.h"
#include "MemManagement.h"
#include "FlowGPU.h"

Public Functions

Type	Name
void	Calcmeanmax (Param XParam, Loop< T > & XLoop, Model< T > XModel, Model< T > XModel_g) Calculate mean and/or max of requested variables on GPU/CPU.
void	Initmeanmax (Param XParam, Loop< T > XLoop, Model< T > XModel, Model< T > XModel_g) Initialize mean and max statistics at the start of the simulation.
__global__ void	addUandhU_GPU (Param XParam, BlockP< T > XBlock, T * h, T * u, T * v, T * U, T * hU) CUDA kernel to compute velocity magnitude and hU product.
__global__ void	addavg_varGPU (Param XParam, BlockP< T > XBlock, T * Varmean, T * Var) CUDA kernel to accumulate mean values for a variable.
__global__ void	addwettime_GPU (Param XParam, BlockP< T > XBlock, T * wett, T * h, T thresold, T time) CUDA kernel to accumulate wet duration for each cell.
__global__ void	divavg_varGPU (Param XParam, BlockP< T > XBlock, T ntdiv, T * Varmean) CUDA kernel to divide mean values by the number of steps.
__global__ void	max_Norm_GPU (Param XParam, BlockP< T > XBlock, T * Varmax, T * Var1, T * Var2) CUDA kernel to compute max velocity magnitude.
__global__ void	max_hU_GPU (Param XParam, BlockP< T > XBlock, T * Varmax, T * Var1, T * Var2, T * Var3) CUDA kernel to compute max hU value.
__global__ void	max_varGPU (Param XParam, BlockP< T > XBlock, T * Varmax, T * Var) CUDA kernel to compute max value for a variable.
void	resetmeanmax (Param XParam, Loop< T > & XLoop, Model< T > XModel, Model< T > XModel_g) Reset mean and/or max statistics at output steps.
void	resetvalGPU (Param XParam, BlockP< T > XBlock, T & var, T val) Reset a variable array to a specified value on the GPU.*

Public Functions Documentation

function Calcmeanmax

Calculate mean and/or max of requested variables on GPU/CPU.

template<class T>
void Calcmeanmax (
    Param XParam,
    Loop < T > & XLoop,
    Model < T > XModel,
    Model < T > XModel_g
)

Computes mean, max, and wet duration statistics for evolving variables, handling both CPU and GPU execution paths.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XLoop Loop control structure
XModel Model state (CPU)
XModel_g Model state (GPU)

function Initmeanmax

Initialize mean and max statistics at the start of the simulation.

template<class T>
void Initmeanmax (
    Param XParam,
    Loop < T > XLoop,
    Model < T > XModel,
    Model < T > XModel_g
)

Sets up/reset statistics arrays for the initial simulation step.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XLoop Loop control structure
XModel Model state (CPU)
XModel_g Model state (GPU)

function addUandhU_GPU

CUDA kernel to compute velocity magnitude and hU product.

template<class T>
__global__ void addUandhU_GPU (
    Param XParam,
    BlockP < T > XBlock,
    T * h,
    T * u,
    T * v,
    T * U,
    T * hU
)

Calculates the velocity magnitude and its product with water depth for each cell on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
h Water depth array
u U-velocity array
v V-velocity array
U Output velocity magnitude array
hU Output hU product array

function addavg_varGPU

CUDA kernel to accumulate mean values for a variable.

template<class T>
__global__ void addavg_varGPU (
    Param XParam,
    BlockP < T > XBlock,
    T * Varmean,
    T * Var
)

Adds the current value to the running mean for each cell on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
Varmean Mean variable array
Var Source variable array

function addwettime_GPU

CUDA kernel to accumulate wet duration for each cell.

template<class T>
__global__ void addwettime_GPU (
    Param XParam,
    BlockP < T > XBlock,
    T * wett,
    T * h,
    T thresold,
    T time
)

Adds time to the wet duration for cells where water depth exceeds a threshold on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
wett Wet duration array
h Water depth array
thresold Wet threshold value
time Time increment

function divavg_varGPU

CUDA kernel to divide mean values by the number of steps.

template<class T>
__global__ void divavg_varGPU (
    Param XParam,
    BlockP < T > XBlock,
    T ntdiv,
    T * Varmean
)

Finalizes the mean calculation by dividing accumulated values by the number of time steps on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
ntdiv Number of time steps
Varmean Mean variable array

function max_Norm_GPU

CUDA kernel to compute max velocity magnitude.

template<class T>
__global__ void max_Norm_GPU (
    Param XParam,
    BlockP < T > XBlock,
    T * Varmax,
    T * Var1,
    T * Var2
)

Updates the max velocity magnitude for each cell by comparing with the current value on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
Varmax Max variable array
Var1 U-velocity array
Var2 V-velocity array

function max_hU_GPU

CUDA kernel to compute max hU value.

template<class T>
__global__ void max_hU_GPU (
    Param XParam,
    BlockP < T > XBlock,
    T * Varmax,
    T * Var1,
    T * Var2,
    T * Var3
)

Updates the max hU value for each cell by comparing with the current value on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
Varmax Max variable array
h Water depth array
u U-velocity array
v V-velocity array

function max_varGPU

CUDA kernel to compute max value for a variable.

template<class T>
__global__ void max_varGPU (
    Param XParam,
    BlockP < T > XBlock,
    T * Varmax,
    T * Var
)

Updates the max value for each cell by comparing with the current value on the GPU.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
Varmax Max variable array
Var Source variable array

function resetmeanmax

Reset mean and/or max statistics at output steps.

template<class T>
void resetmeanmax (
    Param XParam,
    Loop < T > & XLoop,
    Model < T > XModel,
    Model < T > XModel_g
)

Resets mean, max, and wet duration arrays after output is produced, handling both CPU and GPU paths.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XLoop Loop control structure
XModel Model state (CPU)
XModel_g Model state (GPU)

function resetvalGPU

Reset a variable array to a specified value on the GPU.

template<class T>
void resetvalGPU (
    Param XParam,
    BlockP < T > XBlock,
    T *& var,
    T val
)

Sets all elements of the array to the given value using a CUDA kernel.

Template parameters:

T Data type (float or double)

Parameters:

XParam Model parameters
XBlock Block data
var Variable array to reset
val Value to set

The documentation for this class was generated from the following file src/Meanmax.h