-
Notifications
You must be signed in to change notification settings - Fork 102
/
reference.cpp
120 lines (91 loc) · 4.06 KB
/
reference.cpp
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
/*
SYCL Academy (c)
SYCL Academy is licensed under a Creative Commons
Attribution-ShareAlike 4.0 International License.
You should have received a copy of the license along with this
work. If not, see <http://creativecommons.org/licenses/by-sa/4.0/>.
*/
#include "../helpers.hpp"
#include <algorithm>
#include <iostream>
#include <benchmark.h>
#include <image_conv.h>
#include <sycl/sycl.hpp>
class image_convolution;
inline constexpr util::filter_type filterType = util::filter_type::blur;
inline constexpr int filterWidth = 11;
inline constexpr int halo = filterWidth / 2;
int main() {
const char* inputImageFile = "../Images/dogs.png";
const char* outputImageFile = "../Images/blurred_dogs.png";
auto inputImage = util::read_image(inputImageFile, halo);
auto outputImage = util::allocate_image(
inputImage.width(), inputImage.height(), inputImage.channels());
auto filter = util::generate_filter(util::filter_type::blur, filterWidth);
try {
sycl::queue myQueue { sycl::gpu_selector_v };
std::cout << "Running on "
<< myQueue.get_device().get_info<sycl::info::device::name>()
<< "\n";
auto inputImgWidth = inputImage.width();
auto inputImgHeight = inputImage.height();
auto channels = inputImage.channels();
auto filterWidth = filter.width();
auto halo = filter.half_width();
auto globalRange = sycl::range(inputImgWidth, inputImgHeight);
auto localRange = sycl::range(1, 32);
auto ndRange = sycl::nd_range(globalRange, localRange);
auto inBufRange =
sycl::range(inputImgHeight + (halo * 2), inputImgWidth + (halo * 2)) *
sycl::range(1, channels);
auto outBufRange =
sycl::range(inputImgHeight, inputImgWidth) * sycl::range(1, channels);
auto filterRange = filterWidth * sycl::range(1, channels);
{
auto inBuf = sycl::buffer { inputImage.data(), inBufRange };
auto outBuf = sycl::buffer<float, 2> { outBufRange };
auto filterBuf = sycl::buffer { filter.data(), filterRange };
outBuf.set_final_data(outputImage.data());
util::benchmark(
[&]() {
myQueue.submit([&](sycl::handler& cgh) {
sycl::accessor inputAcc { inBuf, cgh, sycl::read_only };
sycl::accessor outputAcc { outBuf, cgh, sycl::write_only };
sycl::accessor filterAcc { filterBuf, cgh, sycl::read_only };
cgh.parallel_for<image_convolution>(
ndRange, [=](sycl::nd_item<2> item) {
auto globalId = item.get_global_id();
globalId = sycl::id { globalId[1], globalId[0] };
auto channelsStride = sycl::range(1, channels);
auto haloOffset = sycl::id(halo, halo);
auto src = (globalId + haloOffset) * channelsStride;
auto dest = globalId * channelsStride;
float sum[4] = { 0.0f, 0.0f, 0.0f, 0.0f };
for (int r = 0; r < filterWidth; ++r) {
for (int c = 0; c < filterWidth; ++c) {
auto srcOffset =
sycl::id(src[0] + (r - halo),
src[1] + ((c - halo) * channels));
auto filterOffset = sycl::id(r, c * channels);
for (int i = 0; i < 4; ++i) {
auto channelOffset = sycl::id(0, i);
sum[i] += inputAcc[srcOffset + channelOffset] *
filterAcc[filterOffset + channelOffset];
}
}
}
for (size_t i = 0; i < 4; ++i) {
outputAcc[dest + sycl::id { 0, i }] = sum[i];
}
});
});
myQueue.wait_and_throw();
},
100, "image convolution (coalesced)");
}
} catch (const sycl::exception& e) {
std::cout << "Exception caught: " << e.what() << std::endl;
}
util::write_image(outputImage, outputImageFile);
SYCLACADEMY_ASSERT(true);
}