forked from NVIDIA/cuda-samples
-
Notifications
You must be signed in to change notification settings - Fork 0
/
recursiveGaussian_kernel.cuh
223 lines (186 loc) · 6.53 KB
/
recursiveGaussian_kernel.cuh
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
/* Copyright (c) 2022, 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_