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#define __2D_WORK_GROUP
#define __2D_GRID
#include <opencl.h>


#if mykernel == 1

//__axiom(get_global_size(0) == 512);
//__axiom(get_global_size(1) == 512);

__axiom(get_num_groups(0) == 2);
__axiom(get_num_groups(1) == 512);

__axiom(get_local_size(0) == 256);
__axiom(get_local_size(1) == 1);

/*
 * Transpose Kernel 
 * input image is transposed by reading the data into a block
 * and writing it to output image
 */
__kernel 
void transpose_kernel(__global uchar4 *output,
                      __global uchar4  *input,
                      __local  uchar4 *block,
                      const    uint    width,
                      const    uint    height,
                      const    uint blockSize)
{
	__requires(width == get_global_size(0));
	__requires(height == get_global_size(1));
	__requires(blockSize == get_local_size(0));
	uint globalIdx = get_global_id(0);
	uint globalIdy = get_global_id(1);
	
	uint localIdx = get_local_id(0);
	uint localIdy = get_local_id(1);
	
    /* copy from input to local memory */
	block[localIdy * blockSize + localIdx] = input[globalIdy*width + globalIdx];

    /* wait until the whole block is filled */
	barrier(CLK_LOCAL_MEM_FENCE);

    /* calculate the corresponding raster indices of source and target */
	uint sourceIndex = localIdy * blockSize + localIdx;
	uint targetIndex = globalIdy + globalIdx * height; 
	
	output[targetIndex] = block[sourceIndex];
}


#endif
#if mykernel == 2

//__axiom(get_global_size(0) == 512);
//__axiom(get_global_size(1) == 1);

__axiom(get_num_groups(0) == 2);
__axiom(get_num_groups(1) == 1);

__axiom(get_local_size(0) == 256);
__axiom(get_local_size(1) == 1);


/*  Recursive Gaussian filter
 *  parameters:	
 *      input - pointer to input data 
 *      output - pointer to output data 
 *      width  - image width
 *      iheight  - image height
 *      a0-a3, b1, b2, coefp, coefn - gaussian parameters
 */
__kernel void RecursiveGaussian_kernel(__global const uchar4* input, __global uchar4* output, 
				       const int width, const int height, 
				       const float a0, const float a1, 
				       const float a2, const float a3, 
				       const float b1, const float b2, 
				       const float coefp, const float coefn)
{
    // compute x : current column ( kernel executes on 1 column )
    unsigned int x = get_global_id(0);

    if (x >= width) 
	return;

    // start forward filter pass
    float4 xp = (float4)0.0f;  // previous input
    float4 yp = (float4)0.0f;  // previous output
    float4 yb = (float4)0.0f;  // previous output by 2

    for (int y = 0; y < height; y++) 
    {
	  int pos = x + y * width;
        float4 xc = (float4)(input[pos].x, input[pos].y, input[pos].z, input[pos].w);
        float4 yc = (a0 * xc) + (a1 * xp) - (b1 * yp) - (b2 * yb);
	  output[pos] = (uchar4)(yc.x, yc.y, yc.z, yc.w);
        xp = xc; 
        yb = yp; 
        yp = yc; 

    }

     barrier(CLK_GLOBAL_MEM_FENCE);


    // start reverse filter pass: ensures response is symmetrical
    float4 xn = (float4)(0.0f);
    float4 xa = (float4)(0.0f);
    float4 yn = (float4)(0.0f);
    float4 ya = (float4)(0.0f);


    for (int y = height - 1; y > -1; y--) 
    {
        int pos = x + y * width;
        float4 xc =  (float4)(input[pos].x, input[pos].y, input[pos].z, input[pos].w);
        float4 yc = (a2 * xn) + (a3 * xa) - (b1 * yn) - (b2 * ya);
        xa = xn; 
        xn = xc; 
        ya = yn; 
        yn = yc;
	  float4 temp = (float4)(output[pos].x, output[pos].y, output[pos].z, output[pos].w) + yc;
	  output[pos] = (uchar4)(temp.x, temp.y, temp.z, temp.w);

    }
}

#endif




	 






	

	




	

	

	
	