cuda-samples/Samples/recursiveGaussian/recursiveGaussian_kernel.cuh

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/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
Recursive Gaussian filter
*/
#ifndef _RECURSIVEGAUSSIAN_KERNEL_CU_
#define _RECURSIVEGAUSSIAN_KERNEL_CU_
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
#include <helper_cuda.h>
#include <helper_math.h>
#define BLOCK_DIM 16
#define CLAMP_TO_EDGE 1
// Transpose kernel (see transpose CUDA Sample for details)
__global__ void d_transpose(uint *odata, uint *idata, int width, int height) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
__shared__ uint block[BLOCK_DIM][BLOCK_DIM + 1];
// read the matrix tile into shared memory
unsigned int xIndex = blockIdx.x * BLOCK_DIM + threadIdx.x;
unsigned int yIndex = blockIdx.y * BLOCK_DIM + threadIdx.y;
if ((xIndex < width) && (yIndex < height)) {
unsigned int index_in = yIndex * width + xIndex;
block[threadIdx.y][threadIdx.x] = idata[index_in];
}
cg::sync(cta);
// write the transposed matrix tile to global memory
xIndex = blockIdx.y * BLOCK_DIM + threadIdx.x;
yIndex = blockIdx.x * BLOCK_DIM + threadIdx.y;
if ((xIndex < height) && (yIndex < width)) {
unsigned int index_out = yIndex * height + xIndex;
odata[index_out] = block[threadIdx.x][threadIdx.y];
}
}
// RGBA version
// reads from 32-bit uint array holding 8-bit RGBA
// convert floating point rgba color to 32-bit integer
__device__ uint rgbaFloatToInt(float4 rgba) {
rgba.x = __saturatef(rgba.x); // clamp to [0.0, 1.0]
rgba.y = __saturatef(rgba.y);
rgba.z = __saturatef(rgba.z);
rgba.w = __saturatef(rgba.w);
return (uint(rgba.w * 255) << 24) | (uint(rgba.z * 255) << 16) |
(uint(rgba.y * 255) << 8) | uint(rgba.x * 255);
}
// convert from 32-bit int to float4
__device__ float4 rgbaIntToFloat(uint c) {
float4 rgba;
rgba.x = (c & 0xff) / 255.0f;
rgba.y = ((c >> 8) & 0xff) / 255.0f;
rgba.z = ((c >> 16) & 0xff) / 255.0f;
rgba.w = ((c >> 24) & 0xff) / 255.0f;
return rgba;
}
/*
simple 1st order recursive filter
- processes one image column per thread
parameters:
id - pointer to input data (RGBA image packed into 32-bit integers)
od - pointer to output data
w - image width
h - image height
a - blur parameter
*/
__global__ void d_simpleRecursive_rgba(uint *id, uint *od, int w, int h,
float a) {
unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
if (x >= w) return;
id += x; // advance pointers to correct column
od += x;
// forward pass
float4 yp = rgbaIntToFloat(*id); // previous output
for (int y = 0; y < h; y++) {
float4 xc = rgbaIntToFloat(*id);
float4 yc =
xc + a * (yp - xc); // simple lerp between current and previous value
*od = rgbaFloatToInt(yc);
id += w;
od += w; // move to next row
yp = yc;
}
// reset pointers to point to last element in column
id -= w;
od -= w;
// reverse pass
// ensures response is symmetrical
yp = rgbaIntToFloat(*id);
for (int y = h - 1; y >= 0; y--) {
float4 xc = rgbaIntToFloat(*id);
float4 yc = xc + a * (yp - xc);
*od = rgbaFloatToInt((rgbaIntToFloat(*od) + yc) * 0.5f);
id -= w;
od -= w; // move to previous row
yp = yc;
}
}
/*
recursive Gaussian filter
parameters:
id - pointer to input data (RGBA image packed into 32-bit integers)
od - pointer to output data
w - image width
h - image height
a0-a3, b1, b2, coefp, coefn - filter parameters
*/
__global__ void d_recursiveGaussian_rgba(uint *id, uint *od, int w, int h,
float a0, float a1, float a2, float a3,
float b1, float b2, float coefp,
float coefn) {
unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
if (x >= w) return;
id += x; // advance pointers to correct column
od += x;
// forward pass
float4 xp = make_float4(0.0f); // previous input
float4 yp = make_float4(0.0f); // previous output
float4 yb = make_float4(0.0f); // previous output by 2
#if CLAMP_TO_EDGE
xp = rgbaIntToFloat(*id);
yb = coefp * xp;
yp = yb;
#endif
for (int y = 0; y < h; y++) {
float4 xc = rgbaIntToFloat(*id);
float4 yc = a0 * xc + a1 * xp - b1 * yp - b2 * yb;
*od = rgbaFloatToInt(yc);
id += w;
od += w; // move to next row
xp = xc;
yb = yp;
yp = yc;
}
// reset pointers to point to last element in column
id -= w;
od -= w;
// reverse pass
// ensures response is symmetrical
float4 xn = make_float4(0.0f);
float4 xa = make_float4(0.0f);
float4 yn = make_float4(0.0f);
float4 ya = make_float4(0.0f);
#if CLAMP_TO_EDGE
xn = xa = rgbaIntToFloat(*id);
yn = coefn * xn;
ya = yn;
#endif
for (int y = h - 1; y >= 0; y--) {
float4 xc = rgbaIntToFloat(*id);
float4 yc = a2 * xn + a3 * xa - b1 * yn - b2 * ya;
xa = xn;
xn = xc;
ya = yn;
yn = yc;
*od = rgbaFloatToInt(rgbaIntToFloat(*od) + yc);
id -= w;
od -= w; // move to previous row
}
}
#endif // #ifndef _GAUSSIAN_KERNEL_H_