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systems-assistant[bot] committed 2025-07-22 22:52:43 +00:00
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projects/rocprofiler/test/simple_convolution/gfx8_SimpleConvolution.hsaco
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projects/rocprofiler/test/simple_convolution/gfx9_SimpleConvolution.hsaco
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projects/rocprofiler/test/simple_convolution/simple_convolution.cl
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/******************************************************************************
Copyright (c) 2018 Advanced Micro Devices, Inc. All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*******************************************************************************/
/**
* SimpleConvolution is where each pixel of the output image
* is the weighted sum of the neighborhood pixels of the input image
* The neighborhood is defined by the dimensions of the mask and
* weight of each neighbor is defined by the mask itself.
* @param output Output matrix after performing convolution
* @param input Input matrix on which convolution is to be performed
* @param mask mask matrix using which convolution was to be performed
* @param inputDimensions dimensions of the input matrix
* @param maskDimensions dimensions of the mask matrix
*/
__kernel void SimpleConvolution(__global uint * output,
__global uint * input,
__global float * mask,
const uint2 inputDimensions,
const uint2 maskDimensions) {
uint tid = get_global_id(0);
uint width = inputDimensions.x;
uint height = inputDimensions.y;
uint x = tid%width;
uint y = tid/width;
uint maskWidth = maskDimensions.x;
uint maskHeight = maskDimensions.y;
uint vstep = (maskWidth -1)/2;
uint hstep = (maskHeight -1)/2;
// find the left, right, top and bottom indices such that
// the indices do not go beyond image boundaires
uint left = (x < vstep) ? 0 : (x - vstep);
uint right = ((x + vstep) >= width) ? width - 1 : (x + vstep);
uint top = (y < hstep) ? 0 : (y - hstep);
uint bottom = ((y + hstep) >= height)? height - 1: (y + hstep);
// initializing wighted sum value
float sumFX = 0;
for(uint i = left; i <= right; ++i) {
for(uint j = top; j <= bottom; ++j) {
// performing wighted sum within the mask boundaries
uint maskIndex = (j - (y - hstep)) * maskWidth + (i - (x - vstep));
uint index = j * width + i;
sumFX += ((float)input[index] * mask[maskIndex]);
}
}
// To round to the nearest integer
sumFX += 0.5f;
output[tid] = (uint)sumFX;
}
projects/rocprofiler/test/simple_convolution/simple_convolution.cpp
+388
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/******************************************************************************
Copyright (c) 2018 Advanced Micro Devices, Inc. All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*******************************************************************************/
#include "simple_convolution/simple_convolution.h"
#include <assert.h>
#include <string.h>
#include <iostream>
#include "util/helper_funcs.h"
#include "util/test_assert.h"
const uint32_t SimpleConvolution::input_data_[]{
15, 201, 51, 89, 92, 34, 96, 66, 11, 225, 161, 96, 81, 211, 108, 124, 202, 244, 182,
90, 215, 92, 98, 20, 44, 225, 55, 247, 202, 0, 45, 218, 202, 97, 51, 39, 131, 147,
105, 143, 116, 11, 239, 198, 222, 92, 67, 169, 81, 250, 3, 40, 86, 101, 60, 131, 70,
116, 123, 17, 117, 168, 236, 64, 10, 31, 103, 142, 179, 209, 29, 40, 220, 13, 239, 187,
105, 50, 100, 186, 44, 104, 227, 131, 205, 32, 6, 20, 149, 130, 38, 10, 43, 18, 75,
53, 50, 178, 195, 230, 132, 225, 14, 96, 238, 253, 27, 88, 48, 128, 18, 92, 232, 246,
224, 182, 23, 231, 203, 172, 105, 241, 183, 148, 4, 2, 202, 55, 181, 142, 29, 57, 111,
43, 153, 93, 41, 181, 181, 89, 54, 200, 182, 31, 190, 150, 213, 213, 126, 160, 130, 232,
146, 57, 125, 151, 59, 71, 206, 240, 213, 236, 42, 68, 24, 195, 162, 65, 121, 87, 155,
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156, 233, 43, 198, 46, 67, 138, 208, 132, 4, 39, 32, 180, 71, 113, 131, 38, 90, 40,
219, 193, 109, 18, 16, 70, 131, 220, 182, 46, 240, 245, 203, 217, 32, 146, 7, 100, 28,
216, 233, 32, 255, 9, 213, 71, 123, 88, 110, 213, 128, 74, 150, 238, 93, 166, 52, 224,
131, 234, 15, 115, 224, 218, 76, 1, 108, 84, 101, 137, 44, 79, 170, 44, 88, 127, 116,
211, 216, 226, 168, 88, 45, 63, 70, 138, 230, 123, 107, 105, 101, 122, 220, 70, 84, 41,
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237, 229, 246, 104, 80, 95, 206, 202, 60, 20, 31, 101, 92, 225, 226, 9, 44, 140, 5,
34, 97, 89, 151, 171, 129, 229, 216, 82, 139, 51, 99, 120, 24, 89, 225, 104, 185, 175,
50, 246, 196, 82, 91, 32, 51, 62, 42, 96, 202, 47, 130, 44, 137, 26, 215, 10, 255,
176, 93, 138, 227, 193, 3, 251, 27, 229, 100, 212, 149, 151, 202, 89, 233, 38, 122, 29,
100, 164, 125, 46, 212, 0, 90, 93, 26, 50, 103, 25, 226, 197, 164, 198, 135, 168, 194,
162, 141, 38, 119, 34, 190, 66, 124, 167, 104, 247, 197, 204, 156, 67, 251, 112, 67, 85,
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241, 128, 70, 233, 70, 18, 133, 137, 14, 245, 204, 99, 195, 42, 235, 248, 161, 86, 243,
190, 135, 118, 130, 123, 154, 213, 150, 54, 74, 111, 20, 60, 240, 90, 37, 54, 109, 171,
191, 123, 161, 140, 222, 100, 182, 202, 93, 88, 32, 80, 23, 168, 198, 153, 36, 97, 111,
187, 151, 185, 43, 172, 245, 27, 6, 27, 82, 115, 199, 18, 239, 104, 158, 206, 205, 85,
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252, 7, 32, 135, 156, 83, 171, 14, 230, 48, 109, 203, 126, 89, 208, 99, 39, 140, 9,
134, 185, 234, 60, 187, 73, 167, 24, 201, 152, 20, 166, 148, 27, 199, 28, 184, 26, 199,
198, 0, 248, 52, 204, 119, 141, 157, 218, 181, 41, 227, 59, 227, 206, 119, 159, 23, 31,
184, 224, 183, 204, 134, 76, 231, 77, 105, 160, 103, 48, 103, 104, 41, 155, 53, 160, 41,
210, 123, 222, 252, 95, 26, 223, 45, 146, 126, 68, 177, 54, 37, 105, 3, 171, 182, 235,
249, 31, 139, 97, 80, 243, 202, 121, 143, 0, 26, 184, 210, 149, 151, 207, 244, 177, 174,
34, 67, 45, 102, 245, 100, 140, 95, 104, 55, 21, 83, 49, 53, 223, 147, 134, 210, 93,
0, 97, 93, 26, 26, 48, 175, 178, 255, 164, 99, 174, 198, 167, 220, 45, 156, 64, 185,
252, 168, 241, 18, 252, 35, 71, 219, 182, 205, 173, 19, 206, 15, 113, 232, 42, 161, 152,
220, 160, 60, 64, 79, 3, 231, 43, 49, 132, 108, 235, 128, 21, 220, 146, 17, 255, 218,
236, 182, 168, 154, 201, 118, 170, 58, 94, 212, 220, 246, 177, 125, 51, 241, 204, 55, 216,
248, 104, 92, 100, 83, 221, 121, 48, 111, 138, 47, 73, 119, 230, 241, 17, 175, 103, 187,
234, 198, 144, 199, 188, 65, 68, 240, 51, 17, 39, 11, 9, 143, 104, 109, 227, 70, 231,
19, 181, 113, 66, 255, 233, 41, 241, 250, 217, 89, 182, 196, 31, 71, 139, 220, 137, 208,
204, 188, 225, 243, 200, 234, 131, 48, 88, 102, 119, 63, 121, 44, 177, 188, 44, 154, 229,
29, 149, 190, 118, 76, 130, 150, 147, 14, 114, 28, 222, 62, 217, 191, 50, 161, 170, 181,
210, 2, 28, 73, 66, 149, 117, 243, 81, 162, 141, 55, 191, 35, 245, 54, 111, 120, 204,
2, 134, 62, 31, 100, 125, 248, 36, 175, 153, 206, 101, 107, 209, 129, 181, 19, 22, 43,
7, 104, 205, 149, 159, 140, 184, 149, 195, 39, 14, 143, 42, 148, 205, 73, 249, 74, 66,
30, 250, 219, 237, 96, 71, 190, 225, 253, 210, 248, 40, 218, 96, 245, 111, 0, 130, 39,
150, 69, 79, 165, 212, 122, 57, 162, 195, 51, 237, 6, 82, 231, 225, 63, 71, 41, 253,
41, 38, 208, 33, 78, 170, 130, 68, 26, 131, 198, 66, 26, 12, 145, 191, 224, 11, 249,
130, 207, 44, 112, 213, 126, 88, 183, 190, 160, 225, 187, 201, 8, 140, 235, 87, 55, 109,
155, 81, 241, 98, 147, 11, 110, 37, 202, 79, 49, 195, 210, 0, 240, 66, 214, 110, 154,
142, 44, 58, 111, 232, 4, 119, 117, 239, 207, 172, 93, 106, 254, 78, 205, 145, 89, 59,
183, 35, 138, 232, 230, 92, 233, 214, 159, 191, 69, 58, 78, 114, 116, 189, 91, 121, 53,
208, 104, 4, 125, 198, 111, 123, 20, 60, 13, 109, 120, 196, 145, 3, 172, 119, 95, 150,
78, 255, 85, 147, 57, 163, 6, 174, 97, 97, 39, 151, 50, 144, 155, 175, 86, 11, 43,
107, 71, 56, 216, 191, 253, 105, 194, 170, 225, 34, 64, 47, 34, 150, 195, 91, 58, 201,
10, 155, 43, 49, 50, 93, 194, 206, 13, 25, 217, 56, 132, 33, 112, 92, 225, 109, 198,
164, 23, 167, 199, 88, 215, 234, 238, 155, 69, 40, 100, 80, 196, 144, 129, 246, 237, 68,
197, 250, 93, 159, 51, 225, 193, 163, 62, 163, 17, 4, 71, 41, 172, 15, 130, 132, 249,
112, 31, 63, 152, 132, 143, 92, 20, 17, 83, 1, 86, 25, 252, 179, 185, 47, 149, 122,
211, 211, 29, 229, 216, 101, 15, 133, 117, 145, 9, 111, 1, 40, 175, 154, 173, 62, 247,
193, 80, 75, 194, 166, 100, 191, 90, 29, 239, 239, 152, 194, 195, 182, 168, 156, 27, 183,
33, 145, 73, 43, 0, 75, 83, 175, 229, 0, 238, 221, 194, 63, 40, 133, 230, 140, 68,
64, 170, 51, 48, 66, 246, 243, 248, 159, 144, 20, 87, 177, 165, 160, 220, 166, 235, 48,
86, 209, 49, 68, 174, 243, 132, 214, 120, 106, 99, 189, 170, 13, 241, 219, 80, 232, 207,
72, 135, 95, 92, 223, 16, 2, 127, 237, 169, 107, 29, 255, 61, 79, 68, 236, 67, 200,
194, 188, 50, 38, 121, 221, 52, 107, 184, 132, 84, 136, 204, 219, 231, 41, 186, 248, 44,
58, 229, 213, 166, 3, 212, 227, 82, 25, 207, 150, 225, 146, 82, 20, 185, 204, 242, 237,
55, 170, 113, 139, 50, 62, 103, 26, 103, 34, 18, 148, 93, 247, 105, 3, 251, 62, 231,
77, 87, 182, 227, 57, 73, 54, 77, 2, 2, 63, 239, 57, 234, 97, 197, 29, 159, 44,
55, 7, 79, 74, 155, 172, 66, 5, 175, 61, 67, 150, 139, 155, 77, 111, 212, 151, 165,
34, 153, 167, 98, 137, 225, 77, 234, 166, 107, 138, 211, 163, 145, 34, 237, 45, 206, 47,
50, 126, 108, 117, 21, 248, 17, 98, 103, 230, 249, 12, 9, 147, 179, 107, 29, 149, 185,
7, 59, 37, 146, 14, 200, 35, 49, 182, 80, 0, 230, 130, 126, 83, 248, 148, 75, 9,
247, 178, 240, 240, 190, 249, 132, 114, 101, 161, 7, 30, 169, 67, 68, 59, 82, 12, 95,
131, 195, 176, 131, 169, 51, 2, 252, 44, 150, 72, 54, 141, 250, 38, 126, 185, 31, 3,
44, 132, 165, 52, 163, 78, 120, 231, 138, 202, 244, 234, 77, 183, 155, 209, 97, 207, 212,
94, 251, 107, 166, 49, 249, 161, 88, 120, 91, 120, 123, 135, 253, 33, 188, 160, 112, 52,
136, 250, 254, 125, 229, 76, 53, 128, 30, 150, 79, 243, 244, 75, 95, 155, 125, 88, 60,
213, 209, 152, 78, 77, 32, 75, 110, 220, 236, 222, 17, 117, 217, 15, 242, 190, 92, 39,
63, 123, 190, 143, 111, 178, 219, 206, 78, 88, 38, 138, 46, 247, 34, 124, 69, 66, 199,
179, 31, 179, 145, 48, 41, 106, 64, 27, 41, 157, 67, 105, 24, 1, 249, 135, 179, 212,
86, 1, 44, 124, 140, 91, 116, 175, 215, 185, 242, 159, 108, 17, 83, 254, 66, 124, 105,
131, 151, 146, 32, 218, 252, 57, 219, 245, 193, 143, 201, 23, 145, 246, 148, 30, 82, 8,
206, 41, 194, 192, 201, 47, 210, 28, 46, 20, 152, 151, 151, 48, 42, 184, 11, 38, 241,
231, 28, 179, 119, 230, 202, 8, 220, 94, 39, 46, 103, 245, 88, 42, 181, 33, 90, 136,
62, 136, 156, 214, 31, 52, 7, 74, 237, 19, 113, 223, 250, 141, 146, 113, 115, 92, 122,
80, 187, 161, 126, 35, 150, 215, 78, 76, 249, 168, 212, 55, 48, 113, 14, 80, 166, 21,
154, 147, 40, 12, 114, 35, 153, 5, 148, 12, 98, 15, 92, 29, 176, 219, 65, 71, 179,
143, 147, 172, 56, 104, 227, 104, 218, 241, 185, 128, 7, 84, 20, 47, 96, 135, 82, 249,
140, 231, 6, 238, 246, 99, 12, 167, 63, 77, 238, 242, 221, 130, 158, 21, 235, 129, 126,
197, 114, 56, 69, 121, 140, 90, 169, 237, 225, 252, 231, 109, 228, 237, 91, 219, 81, 104,
130, 144, 181, 113, 130, 147, 244, 32, 169, 223, 162, 39, 164, 21, 95, 234, 143, 236, 68,
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51, 73, 188, 214, 113, 96, 235, 209, 75, 122, 190, 144, 179, 151, 181, 233, 88, 73, 3,
7, 56, 248, 7, 143, 112, 152, 156, 89, 171, 61, 53, 223, 135, 242, 181, 248, 83, 161,
202, 158, 28, 136, 46, 208, 32, 228, 186, 121, 45, 189, 128, 102, 182, 136, 246, 38, 32,
147, 127, 204, 208, 181, 171, 87, 167, 97, 80, 250, 2, 26, 153, 31, 163, 200, 239, 195,
172, 169, 60, 218, 103, 188, 65, 30, 69, 55, 68, 102, 202, 196, 50, 154, 121, 221, 242,
33, 63, 67, 28, 66, 93, 181, 97, 0, 126, 81, 196, 43, 251, 0, 5, 98, 189, 70,
128, 3, 126, 197, 105, 72, 137, 155, 227, 3, 121, 214, 36, 184, 25, 65, 250, 118, 247,
91, 119, 117, 173, 60, 160, 168, 60, 166, 10, 250, 237, 139, 253, 107, 80, 102, 180, 217,
2, 151, 221, 123, 109, 1, 52, 134, 66, 46, 253, 57, 138, 117, 175, 55, 178, 79, 223,
239, 245, 234, 233, 226, 117, 231, 78, 198, 78, 2, 159, 80, 154, 124, 204, 7, 126, 0,
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121, 203, 100, 131, 95, 135, 68, 224, 207, 56, 58, 122, 201, 115, 25, 183, 61, 30, 51,
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202, 95, 153, 4, 217, 98, 120, 243, 26, 182, 17, 77, 155, 36, 99, 78, 150, 149, 8,
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146, 137, 43, 82, 227, 105, 216, 83, 48, 140, 10, 106, 175, 254, 70, 77, 67, 59, 112,
188, 237, 69, 133, 10, 212, 5, 198, 138, 105, 199, 180, 252, 81, 223, 79, 53, 73, 39,
137, 121, 180, 148, 228, 99, 146, 42, 177, 214, 102, 33, 147, 84, 102, 25, 94, 59, 31,
37, 197, 137, 237, 122, 133, 63, 90, 213, 116, 163, 253, 253, 29, 177, 145, 2, 21, 36,
45, 198, 251, 147, 231, 143, 232, 78, 168, 71, 137, 199, 108, 79, 80, 90, 201, 214, 153,
35, 172, 13, 199, 169, 11, 228, 91, 157, 231, 112, 193, 20, 54, 189, 167, 30, 77, 144,
108, 245, 215, 246, 189, 68, 69, 14, 158, 14, 228, 55, 50, 145, 69, 249, 58, 80, 222,
149, 237, 198, 5, 175, 218, 60, 109, 130, 91, 186, 18, 200, 175, 234, 190, 109, 46, 3,
123, 204, 18, 96, 4, 68, 241, 73, 62, 44, 154, 29, 193, 136, 227, 199, 55, 189, 4,
164, 64, 95, 95, 82, 39, 15, 60, 230, 124, 107, 233, 248, 55, 251, 89, 60, 63, 75,
134, 126, 119, 32, 156, 57, 168, 127, 0, 224, 61, 5, 133, 125, 100, 228, 208, 140, 243,
12, 114, 111, 119, 92, 104, 175, 87, 193, 236, 151, 13, 114, 21, 132, 146, 177, 189, 59,
49, 190, 27, 110, 195, 160, 236, 40, 132, 188, 181, 120, 201, 40, 232, 65, 132, 80, 241,
220, 18, 221, 115, 31, 79, 137, 164, 226, 58, 98, 29, 108, 32, 57, 219, 228, 218, 199,
13, 95, 132, 195, 215, 77, 235, 191, 143, 112, 16, 128, 76, 35, 93, 191, 66, 173, 73,
231, 143, 132, 73, 173, 240, 106, 231, 203, 78, 193, 147, 92, 33, 23, 31, 248, 100, 11,
184, 243, 123, 201, 115, 200, 236, 209, 135, 47, 126, 209, 22, 14, 85, 95, 188, 69, 202,
163, 17, 24, 101, 164, 117, 134, 187, 148, 127, 31, 159, 55, 19, 27, 1, 135, 227, 237,
89, 107, 28, 216, 60, 51, 230, 145, 147, 163, 215, 93, 70, 232, 118, 172, 140, 235, 50,
71, 128, 177, 103, 32, 233, 123, 60, 234, 2, 31, 216, 91, 139, 244, 52, 200, 40, 26,
90, 188, 189, 49, 25, 4, 25, 144, 176, 166, 124, 227, 237, 252, 148, 85, 29, 125, 208,
89, 104, 210, 121, 64, 46, 4, 53, 99, 204, 93, 125, 38, 25, 59, 88, 51, 64, 113,
195, 241, 23, 64, 212, 5, 60, 104, 90, 90, 230, 42, 179, 78, 253, 44, 143, 44, 49,
196, 143, 254, 34, 13, 36, 60, 73, 125, 112, 137, 239, 52, 122, 7, 116, 79, 12, 177,
183, 103, 11, 158, 146, 190, 237, 143, 235, 124, 188, 28, 65, 76, 26, 100, 89, 63, 160,
163, 188, 17, 44, 172, 69, 167, 179, 185, 246, 191, 107, 174, 38, 118, 76, 184, 53, 58,
72, 32, 182, 5, 61, 248, 81, 88, 92, 170, 152, 253, 77, 84, 14, 122, 1, 83, 34,
180, 13, 25, 115, 120, 199, 154, 238, 20, 83, 36, 79, 155, 68, 5, 160, 130, 254, 242,
218, 90, 156, 114, 87, 234, 199, 101, 101, 200, 185, 135, 124, 198, 160, 240, 62, 104, 138,
45, 125, 222, 81, 204, 122, 150, 210, 26, 24, 208, 12, 242, 42, 169, 101, 130, 148, 44,
232, 249, 245, 161, 128, 113, 103, 33, 98, 166, 137, 236, 212, 7, 202, 38, 211, 69, 188,
165, 95, 212, 118, 108, 199, 161, 22, 45, 35, 170, 90, 11, 163, 79, 173, 36, 193, 20,
69, 35, 187, 207, 16, 144, 214, 219, 182, 170, 32, 114, 79, 128, 71, 198, 237, 15, 103,
4, 60, 139, 175, 150, 151, 82, 230, 68, 119, 168, 89, 188, 204, 20, 140, 220, 165, 98,
184, 91, 12, 217, 205, 92, 90, 20, 35, 71, 36, 138, 76, 96, 22, 251, 247, 173, 78,
222, 241, 197, 134, 75, 130, 83, 96, 14, 47, 5, 113, 232, 96, 126, 193, 45, 218, 28,
66, 253, 99, 103, 136, 176, 200, 158, 171, 191, 76, 249, 158, 62, 190, 37, 137, 65, 120,
233, 80, 168, 238, 193, 145, 79, 63, 82, 125, 26, 111, 191, 24, 210, 39, 161, 131, 239,
64, 46, 175, 140, 39, 77, 202, 230, 115, 84, 40, 235, 62, 120, 148, 45, 57, 37, 124,
121, 120, 249, 148, 231, 185, 172, 186, 224, 77, 61, 207, 141, 107, 126, 26, 147, 204, 229,
121, 63, 58, 161, 43, 120, 25, 191, 165, 83, 228, 34, 205, 92, 27, 97, 67, 213, 13,
253, 182, 91, 59, 133, 233, 166, 4, 4, 57, 209, 233, 179, 16, 35, 85, 59, 155, 111,
250, 65, 194, 223, 99, 144, 59, 127, 241, 127, 85, 255, 125, 11, 90, 184, 145, 68, 95,
150, 72, 153, 103, 49, 76, 120, 85, 161, 179, 241, 16, 174, 51, 211, 142, 150, 99, 201,
22, 85, 73, 108, 84, 199, 120, 175, 128, 9, 243, 223, 160, 59, 120, 8, 109, 197, 128,
194, 103, 52, 180, 119, 227, 231, 75, 113, 126, 175, 59, 148, 4, 132, 1, 89, 75, 121,
8, 204, 131, 251, 171, 36, 55, 36, 44, 165, 233, 172, 103, 80, 224, 28, 200, 195, 3,
20, 53, 129, 195, 112, 22, 200, 244, 23, 34, 64, 145, 42, 12, 20, 38, 184, 56, 94,
220, 101, 3, 198, 17, 107, 22, 242, 135, 222, 182, 138, 243, 235, 11, 182, 91, 34, 127,
80, 58, 161, 145, 203, 204, 158, 224, 242, 86, 24, 81, 51, 126, 84, 249, 143, 191, 15,
130, 70, 238, 57, 209, 225, 36, 221, 152, 128, 255, 24, 208, 57, 186, 97, 4, 134, 255,
229, 121, 86, 254, 202, 137, 124, 31, 130, 12, 222, 146, 142, 37, 129, 199, 247, 98, 236,
212, 251, 108, 211, 20, 60, 13, 206, 158, 18, 84};
SimpleConvolution::SimpleConvolution() {
width_ = 64;
height_ = 64;
mask_width_ = 3;
mask_height_ = mask_width_;
randomize_seed_ = 0;
if (!IsPowerOf2(width_)) {
width_ = RoundToPowerOf2(width_);
}
if (!IsPowerOf2(height_)) {
height_ = RoundToPowerOf2(height_);
}
if (!(mask_width_ % 2)) {
mask_width_++;
}
if (!(mask_height_ % 2)) {
mask_height_++;
}
if (width_ * height_ < 256) {
width_ = 64;
height_ = 64;
}
const uint32_t input_size_bytes = width_ * height_ * sizeof(uint32_t);
const uint32_t mask_size_bytes = mask_width_ * mask_height_ * sizeof(float);
SetInDescr(KERNARG_BUF_ID, KERNARG_DES_ID, sizeof(kernel_args_t));
SetInDescr(INPUT_BUF_ID, SYS_DES_ID, input_size_bytes);
SetInDescr(MASK_BUF_ID, SYS_DES_ID, mask_size_bytes);
SetOutDescr(LOCAL_BUF_ID, LOCAL_DES_ID, input_size_bytes);
SetHostDescr(REFOUT_BUF_ID, REFOUT_DES_ID, input_size_bytes);
if (!randomize_seed_) TEST_ASSERT(sizeof(input_data_) <= input_size_bytes);
}
void SimpleConvolution::Init() {
std::clog << "SimpleConvolution::init :" << std::endl;
mem_descr_t kernarg_des = GetDescr(KERNARG_BUF_ID);
mem_descr_t input_des = GetDescr(INPUT_BUF_ID);
mem_descr_t mask_des = GetDescr(MASK_BUF_ID);
mem_descr_t output_des = GetDescr(LOCAL_BUF_ID);
#if 0
printf("kernarg_des %p 0x%x\n", kernarg_des.ptr, kernarg_des.size);
printf("input_des %p 0x%x\n", input_des.ptr, input_des.size);
printf("mask_des %p 0x%x\n", mask_des.ptr, mask_des.size);
printf("output_des %p 0x%x\n", output_des.ptr, output_des.size);
#endif
uint32_t* input = reinterpret_cast<uint32_t*>(input_des.ptr);
uint32_t* output_local = reinterpret_cast<uint32_t*>(output_des.ptr);
float* mask = reinterpret_cast<float*>(mask_des.ptr);
kernel_args_t* kernel_args = reinterpret_cast<kernel_args_t*>(kernarg_des.ptr);
if (randomize_seed_) {
// random initialisation of input
FillRandom<uint32_t>(input, width_, height_, 0, 255, randomize_seed_);
} else {
// initialization with preset values
memcpy(input, input_data_, width_ * height_ * sizeof(uint32_t));
}
// Fill a blurr filter or some other filter of your choice
const float val = 1.0f / (mask_width_ * 2.0f - 1.0f);
for (uint32_t i = 0; i < (mask_width_ * mask_height_); i++) {
mask[i] = 0;
}
for (uint32_t i = 0; i < mask_width_; i++) {
uint32_t y = mask_height_ / 2;
mask[y * mask_width_ + i] = val;
}
for (uint32_t i = 0; i < mask_height_; i++) {
uint32_t x = mask_width_ / 2;
mask[i * mask_width_ + x] = val;
}
// Print the INPUT array.
std::clog << std::dec;
PrintArray<uint32_t>("> Input[0]", input, width_, 1);
PrintArray<float>("> Mask", mask, mask_width_, mask_height_);
// Fill the kernel args
kernel_args->arg1 = output_local;
kernel_args->arg2 = input;
kernel_args->arg3 = mask;
kernel_args->arg4 = width_;
kernel_args->arg41 = height_;
kernel_args->arg5 = mask_width_;
kernel_args->arg51 = mask_height_;
// Calculate the reference output
ReferenceImplementation(reinterpret_cast<uint32_t*>(GetRefOut()), input, mask, width_, height_,
mask_width_, mask_height_);
}
void SimpleConvolution::PrintOutput(const void* ptr) const {
PrintArray<uint32_t>("> Output[0]", reinterpret_cast<const uint32_t*>(ptr), width_, 1);
}
bool SimpleConvolution::ReferenceImplementation(uint32_t* output, const uint32_t* input,
const float* mask, const uint32_t width,
const uint32_t height, const uint32_t mask_width,
const uint32_t mask_height) {
const uint32_t vstep = (mask_width - 1) / 2;
const uint32_t hstep = (mask_height - 1) / 2;
// for each pixel in the input
for (uint32_t x = 0; x < width; x++) {
for (uint32_t y = 0; y < height; y++) {
// find the left, right, top and bottom indices such that
// the indices do not go beyond image boundaires
const uint32_t left = (x < vstep) ? 0 : (x - vstep);
const uint32_t right = ((x + vstep) >= width) ? width - 1 : (x + vstep);
const uint32_t top = (y < hstep) ? 0 : (y - hstep);
const uint32_t bottom = ((y + hstep) >= height) ? height - 1 : (y + hstep);
// initializing wighted sum value
float sum_fx = 0;
for (uint32_t i = left; i <= right; ++i) {
for (uint32_t j = top; j <= bottom; ++j) {
// performing wighted sum within the mask boundaries
uint32_t mask_idx = (j - (y - hstep)) * mask_width + (i - (x - vstep));
uint32_t index = j * width + i;
// to round to the nearest integer
sum_fx += ((float)input[index] * mask[mask_idx]);
}
}
sum_fx += 0.5f;
output[y * width + x] = uint32_t(sum_fx);
}
}
return true;
}
projects/rocprofiler/test/simple_convolution/simple_convolution.h
+94
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@@ -0,0 +1,94 @@
/******************************************************************************
Copyright (c) 2018 Advanced Micro Devices, Inc. All rights reserved.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
*******************************************************************************/
#ifndef TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_
#define TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_
#include <map>
#include <vector>
#include "ctrl/test_kernel.h"
// Class implements SimpleConvolution kernel parameters
class SimpleConvolution : public TestKernel {
public:
// Kernel buffers IDs
enum { INPUT_BUF_ID, LOCAL_BUF_ID, MASK_BUF_ID, KERNARG_BUF_ID, REFOUT_BUF_ID };
// Constructor
SimpleConvolution();
// Initialize method
void Init();
// Return compute grid size
uint32_t GetGridSize() const { return width_ * height_; }
// Print output
void PrintOutput(const void* ptr) const;
// Return name
std::string Name() const { return std::string("SimpleConvolution"); }
private:
// Local kernel arguments declaration
struct kernel_args_t {
void* arg1;
void* arg2;
void* arg3;
uint32_t arg4;
uint32_t arg41;
uint32_t arg5;
uint32_t arg51;
};
// Reference CPU implementation of Simple Convolution
// @param output Output matrix after performing convolution
// @param input Input matrix on which convolution is to be performed
// @param mask mask matrix using which convolution was to be performed
// @param input_dimensions dimensions of the input matrix
// @param mask_dimensions dimensions of the mask matrix
// @return bool true on success and false on failure
bool ReferenceImplementation(uint32_t* output, const uint32_t* input, const float* mask,
const uint32_t width, const uint32_t height,
const uint32_t maskWidth, const uint32_t maskHeight);
// Width of the Input array
uint32_t width_;
// Height of the Input array
uint32_t height_;
// Mask dimensions
uint32_t mask_width_;
// Mask dimensions
uint32_t mask_height_;
// Randomize input data
unsigned randomize_seed_;
// Input data
static const uint32_t input_data_[];
};
#endif // TEST_SIMPLE_CONVOLUTION_SIMPLE_CONVOLUTION_H_