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Diffstat (limited to 'intern/cycles/kernel/kernels/cuda/filter.cu')
| -rw-r--r-- | intern/cycles/kernel/kernels/cuda/filter.cu | 235 |
1 files changed, 235 insertions, 0 deletions
diff --git a/intern/cycles/kernel/kernels/cuda/filter.cu b/intern/cycles/kernel/kernels/cuda/filter.cu new file mode 100644 index 00000000000..50f73f9728d --- /dev/null +++ b/intern/cycles/kernel/kernels/cuda/filter.cu @@ -0,0 +1,235 @@ +/* + * Copyright 2011-2017 Blender Foundation + * + * Licensed under the Apache License, Version 2.0 (the "License"); + * you may not use this file except in compliance with the License. + * You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +/* CUDA kernel entry points */ + +#ifdef __CUDA_ARCH__ + +#include "kernel_config.h" + +#include "kernel/kernel_compat_cuda.h" + +#include "kernel/filter/filter_kernel.h" + +/* kernels */ + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_divide_shadow(int sample, + TilesInfo *tiles, + float *unfilteredA, + float *unfilteredB, + float *sampleVariance, + float *sampleVarianceV, + float *bufferVariance, + int4 prefilter_rect, + int buffer_pass_stride, + int buffer_denoising_offset, + bool use_split_variance) +{ + int x = prefilter_rect.x + blockDim.x*blockIdx.x + threadIdx.x; + int y = prefilter_rect.y + blockDim.y*blockIdx.y + threadIdx.y; + if(x < prefilter_rect.z && y < prefilter_rect.w) { + kernel_filter_divide_shadow(sample, + tiles, + x, y, + unfilteredA, + unfilteredB, + sampleVariance, + sampleVarianceV, + bufferVariance, + prefilter_rect, + buffer_pass_stride, + buffer_denoising_offset, + use_split_variance); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_get_feature(int sample, + TilesInfo *tiles, + int m_offset, + int v_offset, + float *mean, + float *variance, + int4 prefilter_rect, + int buffer_pass_stride, + int buffer_denoising_offset, + bool use_split_variance) +{ + int x = prefilter_rect.x + blockDim.x*blockIdx.x + threadIdx.x; + int y = prefilter_rect.y + blockDim.y*blockIdx.y + threadIdx.y; + if(x < prefilter_rect.z && y < prefilter_rect.w) { + kernel_filter_get_feature(sample, + tiles, + m_offset, v_offset, + x, y, + mean, variance, + prefilter_rect, + buffer_pass_stride, + buffer_denoising_offset, + use_split_variance); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_combine_halves(float *mean, float *variance, float *a, float *b, int4 prefilter_rect, int r) +{ + int x = prefilter_rect.x + blockDim.x*blockIdx.x + threadIdx.x; + int y = prefilter_rect.y + blockDim.y*blockIdx.y + threadIdx.y; + if(x < prefilter_rect.z && y < prefilter_rect.w) { + kernel_filter_combine_halves(x, y, mean, variance, a, b, prefilter_rect, r); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_construct_transform(float const* __restrict__ buffer, + float *transform, int *rank, + int4 filter_area, int4 rect, + int radius, float pca_threshold, + int pass_stride) +{ + int x = blockDim.x*blockIdx.x + threadIdx.x; + int y = blockDim.y*blockIdx.y + threadIdx.y; + if(x < filter_area.z && y < filter_area.w) { + int *l_rank = rank + y*filter_area.z + x; + float *l_transform = transform + y*filter_area.z + x; + kernel_filter_construct_transform(buffer, + x + filter_area.x, y + filter_area.y, + rect, pass_stride, + l_transform, l_rank, + radius, pca_threshold, + filter_area.z*filter_area.w, + threadIdx.y*blockDim.x + threadIdx.x); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_nlm_calc_difference(int dx, int dy, + float ccl_restrict_ptr weightImage, + float ccl_restrict_ptr varianceImage, + float *differenceImage, + int4 rect, int w, + int channel_offset, + float a, float k_2) { + int x = blockDim.x*blockIdx.x + threadIdx.x + rect.x; + int y = blockDim.y*blockIdx.y + threadIdx.y + rect.y; + if(x < rect.z && y < rect.w) { + kernel_filter_nlm_calc_difference(x, y, dx, dy, weightImage, varianceImage, differenceImage, rect, w, channel_offset, a, k_2); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_nlm_blur(float ccl_restrict_ptr differenceImage, float *outImage, int4 rect, int w, int f) { + int x = blockDim.x*blockIdx.x + threadIdx.x + rect.x; + int y = blockDim.y*blockIdx.y + threadIdx.y + rect.y; + if(x < rect.z && y < rect.w) { + kernel_filter_nlm_blur(x, y, differenceImage, outImage, rect, w, f); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_nlm_calc_weight(float ccl_restrict_ptr differenceImage, float *outImage, int4 rect, int w, int f) { + int x = blockDim.x*blockIdx.x + threadIdx.x + rect.x; + int y = blockDim.y*blockIdx.y + threadIdx.y + rect.y; + if(x < rect.z && y < rect.w) { + kernel_filter_nlm_calc_weight(x, y, differenceImage, outImage, rect, w, f); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_nlm_update_output(int dx, int dy, + float ccl_restrict_ptr differenceImage, + float ccl_restrict_ptr image, + float *outImage, float *accumImage, + int4 rect, int w, + int f) { + int x = blockDim.x*blockIdx.x + threadIdx.x + rect.x; + int y = blockDim.y*blockIdx.y + threadIdx.y + rect.y; + if(x < rect.z && y < rect.w) { + kernel_filter_nlm_update_output(x, y, dx, dy, differenceImage, image, outImage, accumImage, rect, w, f); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_nlm_normalize(float *outImage, float ccl_restrict_ptr accumImage, int4 rect, int w) { + int x = blockDim.x*blockIdx.x + threadIdx.x + rect.x; + int y = blockDim.y*blockIdx.y + threadIdx.y + rect.y; + if(x < rect.z && y < rect.w) { + kernel_filter_nlm_normalize(x, y, outImage, accumImage, rect, w); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_nlm_construct_gramian(int dx, int dy, + float ccl_restrict_ptr differenceImage, + float ccl_restrict_ptr buffer, + float *color_pass, + float *variance_pass, + float const* __restrict__ transform, + int *rank, + float *XtWX, + float3 *XtWY, + int4 rect, + int4 filter_rect, + int w, int h, int f, + int pass_stride) { + int x = blockDim.x*blockIdx.x + threadIdx.x + max(0, rect.x-filter_rect.x); + int y = blockDim.y*blockIdx.y + threadIdx.y + max(0, rect.y-filter_rect.y); + if(x < min(filter_rect.z, rect.z-filter_rect.x) && y < min(filter_rect.w, rect.w-filter_rect.y)) { + kernel_filter_nlm_construct_gramian(x, y, + dx, dy, + differenceImage, + buffer, + color_pass, variance_pass, + transform, rank, + XtWX, XtWY, + rect, filter_rect, + w, h, f, + pass_stride, + threadIdx.y*blockDim.x + threadIdx.x); + } +} + +extern "C" __global__ void +CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS) +kernel_cuda_filter_finalize(int w, int h, + float *buffer, int *rank, + float *XtWX, float3 *XtWY, + int4 filter_area, int4 buffer_params, + int sample) { + int x = blockDim.x*blockIdx.x + threadIdx.x; + int y = blockDim.y*blockIdx.y + threadIdx.y; + if(x < filter_area.z && y < filter_area.w) { + int storage_ofs = y*filter_area.z+x; + rank += storage_ofs; + XtWX += storage_ofs; + XtWY += storage_ofs; + kernel_filter_finalize(x, y, w, h, buffer, rank, filter_area.z*filter_area.w, XtWX, XtWY, buffer_params, sample); + } +} + +#endif + |