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#ifndef RTS_REALFIELD_H
#define RTS_REALFIELD_H
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#include "../visualization/colormap.h"
#include "../envi/envi.h"
#include "../math/rect.h"
#include "../cuda/devices.h"
#include "cublas_v2.h"
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#include <cuda_runtime.h>
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///Compute a Gaussian function in 3D (mostly for testing)
/*template<typename T>
__global__ void gpu_gaussian(T* dest, unsigned int r0, unsigned int r1, T mean, T std, rts::rect<T> shape)
{
int iu = blockIdx.x * blockDim.x + threadIdx.x;
int iv = blockIdx.y * blockDim.y + threadIdx.y;
//make sure that the thread indices are in-bounds
if(iu >= r0 || iv >= r1) return;
//compute the index into the field
int i = iv*r0 + iu;
T u = (T)iu / (T)r0;
T v = (T)iv / (T)r1;
rts::vec<T> p = shape(u, v);
T fx = (T)1.0 / (std * (T)sqrt(2 * 3.14159f) ) * exp( - pow(p[0] - mean, 2) / (2 * std*std) );
T fy = (T)1.0 / (std * (T)sqrt(2 * 3.14159f) ) * exp( - pow(p[1] - mean, 2) / (2 * std*std) );
T fz = (T)1.0 / (std * (T)sqrt(2 * 3.14159f) ) * exp( - pow(p[2] - mean, 2) / (2 * std*std) );
dest[i] = fx * fy * fz;
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}*/
namespace rts{
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//multiply R = X * Y
template<typename T>
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__global__ void gpu_realfield_multiply(T* R, T* X, T* Y, unsigned int r0, unsigned int r1){
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int iu = blockIdx.x * blockDim.x + threadIdx.x;
int iv = blockIdx.y * blockDim.y + threadIdx.y;
//make sure that the thread indices are in-bounds
if(iu >= r0 || iv >= r1) return;
//compute the index into the field
int i = iv*r0 + iu;
//calculate and store the result
R[i] = X[i] * Y[i];
}
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template<typename P, unsigned int N = 1, bool positive = false>
class realfield{
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P* X[N]; //an array of N gpu pointers for each field component
int R[2]; //resolution of the slice
rect<P> shape;
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void process_filename(std::string name, std::string &prefix, std::string &postfix,
std::string &ext, unsigned int &digits)
{
std::stringstream ss(name);
std::string item;
std::vector<std::string> elems;
while(std::getline(ss, item, '.')) //split the string at the '.' character (filename and extension)
{
elems.push_back(item);
}
prefix = elems[0]; //prefix contains the filename (with wildcard '?' characters)
ext = elems[1]; //file extension (ex. .bmp, .png)
ext = std::string(".") + ext; //add a period back into the extension
size_t i0 = prefix.find_first_of("?"); //find the positions of the first and last wildcard ('?'')
size_t i1 = prefix.find_last_of("?");
postfix = prefix.substr(i1+1);
prefix = prefix.substr(0, i0);
digits = i1 - i0 + 1; //compute the number of wildcards
}
void init()
{
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for(unsigned int n=0; n<N; n++)
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X[n] = NULL;
}
void destroy()
{
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for(unsigned int n=0; n<N; n++)
if(X[n] != NULL)
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HANDLE_ERROR(cudaFree(X[n]));
}
public:
//field constructor
realfield()
{
R[0] = R[1] = 0;
init();
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//std::cout<<"realfield CONSTRUCTOR"<<std::endl;
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}
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realfield(unsigned int x, unsigned int y)
{
//set the resolution
R[0] = x;
R[1] = y;
//allocate memory on the GPU
for(unsigned int n=0; n<N; n++)
{
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HANDLE_ERROR(cudaMalloc( (void**)&X[n], sizeof(P) * R[0] * R[1] ));
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}
//shape = rect<P>(vec<P>(-1, -1, 0), vec<P>(-1, 1, 0), vec<P>(1, 1, 0)); //default geometry
clear(); //zero the field
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//std::cout<<"realfield CONSTRUCTOR"<<std::endl;
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}
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~realfield()
{
destroy();
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//std::cout<<"realfield DESTRUCTOR"<<std::endl;
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}
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P* ptr(unsigned int n = 0)
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{
if(n < N)
return X[n];
else return NULL;
}
//set all components of the field to zero
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void clear()
{
for(unsigned int n=0; n<N; n++)
if(X[n] != NULL)
HANDLE_ERROR(cudaMemset(X[n], 0, sizeof(P) * R[0] * R[1]));
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}
void toImage(std::string filename, unsigned int n, P vmin, P vmax, rts::colormapType cmap = rts::cmBrewer)
{
rts::gpu2image<P>(X[n], filename, R[0], R[1], vmin, vmax, cmap);
}
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void toImages(std::string filename, bool global_max = true, rts::colormapType cmap = rts::cmBrewer)
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{
std::string prefix, postfix, extension;
unsigned int digits;
process_filename(filename, prefix, postfix, extension, digits); //process the filename for wild cards
cublasStatus_t stat;
cublasHandle_t handle;
//create a CUBLAS handle
stat = cublasCreate(&handle);
if(stat != CUBLAS_STATUS_SUCCESS)
{
std::cout<<"CUBLAS Error: initialization failed"<<std::endl;
exit(1);
}
int L = R[0] * R[1]; //compute the number of discrete points in a slice
int result; //result of the max operation
P maxVal[N]; //array stores minimum and maximum values
P maxAll = 0; //largest value in the data set
//compute the maximum value for each vector component
for(int n=0; n<N; n++)
{
if(sizeof(P) == 4)
stat = cublasIsamax(handle, L, (const float*)X[n], 1, &result);
else
stat = cublasIdamax(handle, L, (const double*)X[n], 1, &result);
result -= 1; //adjust for 1-based indexing
if(stat != CUBLAS_STATUS_SUCCESS) //if there was a GPU error, terminate
{
std::cout<<"CUBLAS Error: failure finding maximum value."<<std::endl;
exit(1);
}
//retrieve the maximum value for this slice and store it in the maxVal array
HANDLE_ERROR(cudaMemcpy(&maxVal[n], X[n] + result, sizeof(P), cudaMemcpyDeviceToHost));
if(abs(maxVal[n]) > maxAll) //if maxVal is larger, update the maxAll variable
maxAll = maxVal[n];
}
cublasDestroy(handle); //destroy the CUBLAS handle
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P outputMax = abs(maxAll); //maximum value used for each output image
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for(int n=0; n<N; n++) //for each image
{
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if(!global_max) outputMax = maxVal[n]; //calculate the maximum value for this image
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stringstream ss; //assemble the file name
ss<<prefix<<std::setfill('0')<<std::setw(digits)<<n<<postfix<<extension;
std::cout<<ss.str()<<std::endl;
if(positive) //if the image is positive
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toImage(ss.str(), n, 0, abs(outputMax), cmap); //save the image using the global maximum
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else
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toImage(ss.str(), n, -abs(outputMax), abs(outputMax), cmap); //save the image using the global maximum
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}
}
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//assignment operator
realfield & operator= (const realfield & rhs)
{
//de-allocate any existing GPU memory
destroy();
//copy the slice resolution
R[0] = rhs.R[0];
R[1] = rhs.R[1];
for(unsigned int n=0; n<N; n++)
{
//allocate the necessary memory
HANDLE_ERROR(cudaMalloc(&X[n], sizeof(P) * R[0] * R[1]));
//copy the slice
HANDLE_ERROR(cudaMemcpy(X[n], rhs.X[n], sizeof(P) * R[0] * R[1], cudaMemcpyDeviceToDevice));
}
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//std::cout<<"Assignment operator."<<std::endl;
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return *this;
}
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//multiply two fields (element-wise multiplication)
realfield<P, N, positive> operator* (const realfield & rhs){
int maxThreads = rts::maxThreadsPerBlock(); //compute the optimal block size
int SQRT_BLOCK = (int)std::sqrt((float)maxThreads);
//create one thread for each detector pixel
dim3 dimBlock(SQRT_BLOCK, SQRT_BLOCK);
dim3 dimGrid((R[0] + SQRT_BLOCK -1)/SQRT_BLOCK, (R[1] + SQRT_BLOCK - 1)/SQRT_BLOCK);
//create a scalar field to store the result
realfield<P, N, positive> result(R[0], R[1]);
for(int n=0; n<N; n++)
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rts::gpu_realfield_multiply <<<dimGrid, dimBlock>>> (result.X[n], X[n], rhs.X[n], R[0], R[1]);
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return result;
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}
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///copy constructor
realfield(const realfield &rhs)
{
//first make a shallow copy
R[0] = rhs.R[0];
R[1] = rhs.R[1];
for(unsigned int n=0; n<N; n++)
{
//do we have to make a deep copy?
if(rhs.X[n] == NULL)
X[n] = NULL; //no
else
{
//allocate the necessary memory
HANDLE_ERROR(cudaMalloc(&X[n], sizeof(P) * R[0] * R[1]));
//copy the slice
HANDLE_ERROR(cudaMemcpy(X[n], rhs.X[n], sizeof(P) * R[0] * R[1], cudaMemcpyDeviceToDevice));
}
}
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//std::cout<<"realfield COPY CONSTRUCTOR"<<std::endl;
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}
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/*void gaussian(P mean, P std, unsigned int n=0) //creates a 3D gaussian using component n
{
int maxThreads = rts::maxThreadsPerBlock(); //compute the optimal block size
int SQRT_BLOCK = (int)sqrt((float)maxThreads);
//create one thread for each detector pixel
dim3 dimBlock(SQRT_BLOCK, SQRT_BLOCK);
dim3 dimGrid((R[0] + SQRT_BLOCK -1)/SQRT_BLOCK, (R[1] + SQRT_BLOCK - 1)/SQRT_BLOCK);
gpu_gaussian<float> <<<dimGrid, dimBlock>>> (X[n], R[0], R[1], mean, std, shape);
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}*/
};
} //end namespace rts
#endif
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