Cycles: merge of cycles-x branch, a major update to the renderer

This includes much improved GPU rendering performance, viewport interactivity,
new shadow catcher, revamped sampling settings, subsurface scattering anisotropy,
new GPU volume sampling, improved PMJ sampling pattern, and more.

Some features have also been removed or changed, breaking backwards compatibility.
Including the removal of the OpenCL backend, for which alternatives are under
development.

Release notes and code docs:
https://wiki.blender.org/wiki/Reference/Release_Notes/3.0/Cycles
https://wiki.blender.org/wiki/Source/Render/Cycles

Credits:
* Sergey Sharybin
* Brecht Van Lommel
* Patrick Mours (OptiX backend)
* Christophe Hery (subsurface scattering anisotropy)
* William Leeson (PMJ sampling pattern)
* Alaska (various fixes and tweaks)
* Thomas Dinges (various fixes)

For the full commit history, see the cycles-x branch. This squashes together
all the changes since intermediate changes would often fail building or tests.

Ref T87839, T87837, T87836
Fixes T90734, T89353, T80267, T80267, T77185, T69800

1 files changed, 0 insertions, 129 deletions

diff --git a/intern/cycles/kernel/filter/filter_transform_sse.h b/intern/cycles/kernel/filter/filter_transform_sse.h
deleted file mode 100644
index 0304d990f9f..00000000000
--- a/intern/cycles/kernel/filter/filter_transform_sse.h
+++ /dev/null
@@ -1,129 +0,0 @@
-/*
- * 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.
- */
-
-CCL_NAMESPACE_BEGIN
-
-ccl_device void kernel_filter_construct_transform(const float *ccl_restrict buffer,
-                                                  CCL_FILTER_TILE_INFO,
-                                                  int x,
-                                                  int y,
-                                                  int4 rect,
-                                                  int pass_stride,
-                                                  int frame_stride,
-                                                  bool use_time,
-                                                  float *transform,
-                                                  int *rank,
-                                                  int radius,
-                                                  float pca_threshold)
-{
-  int buffer_w = align_up(rect.z - rect.x, 4);
-
-  float4 features[DENOISE_FEATURES];
-  const float *ccl_restrict pixel_buffer;
-  int3 pixel;
-
-  int num_features = use_time ? 11 : 10;
-
-  /* === Calculate denoising window. === */
-  int2 low = make_int2(max(rect.x, x - radius), max(rect.y, y - radius));
-  int2 high = make_int2(min(rect.z, x + radius + 1), min(rect.w, y + radius + 1));
-  int num_pixels = (high.y - low.y) * (high.x - low.x) * tile_info->num_frames;
-
-  /* === Shift feature passes to have mean 0. === */
-  float4 feature_means[DENOISE_FEATURES];
-  math_vector_zero_sse(feature_means, num_features);
-  FOR_PIXEL_WINDOW_SSE
-  {
-    filter_get_features_sse(
-        x4, y4, t4, active_pixels, pixel_buffer, features, use_time, NULL, pass_stride);
-    math_vector_add_sse(feature_means, num_features, features);
-  }
-  END_FOR_PIXEL_WINDOW_SSE
-
-  float4 pixel_scale = make_float4(1.0f / num_pixels);
-  for (int i = 0; i < num_features; i++) {
-    feature_means[i] = reduce_add(feature_means[i]) * pixel_scale;
-  }
-
-  /* === Scale the shifted feature passes to a range of [-1; 1] ===
-   * Will be baked into the transform later. */
-  float4 feature_scale[DENOISE_FEATURES];
-  math_vector_zero_sse(feature_scale, num_features);
-  FOR_PIXEL_WINDOW_SSE
-  {
-    filter_get_feature_scales_sse(
-        x4, y4, t4, active_pixels, pixel_buffer, features, use_time, feature_means, pass_stride);
-    math_vector_max_sse(feature_scale, features, num_features);
-  }
-  END_FOR_PIXEL_WINDOW_SSE
-
-  filter_calculate_scale_sse(feature_scale, use_time);
-
-  /* === Generate the feature transformation. ===
-   * This transformation maps the num_features-dimensional feature space to a reduced feature
-   * (r-feature) space which generally has fewer dimensions.
-   * This mainly helps to prevent over-fitting. */
-  float4 feature_matrix_sse[DENOISE_FEATURES * DENOISE_FEATURES];
-  math_matrix_zero_sse(feature_matrix_sse, num_features);
-  FOR_PIXEL_WINDOW_SSE
-  {
-    filter_get_features_sse(
-        x4, y4, t4, active_pixels, pixel_buffer, features, use_time, feature_means, pass_stride);
-    math_vector_mul_sse(features, num_features, feature_scale);
-    math_matrix_add_gramian_sse(feature_matrix_sse, num_features, features, make_float4(1.0f));
-  }
-  END_FOR_PIXEL_WINDOW_SSE
-
-  float feature_matrix[DENOISE_FEATURES * DENOISE_FEATURES];
-  math_matrix_hsum(feature_matrix, num_features, feature_matrix_sse);
-
-  math_matrix_jacobi_eigendecomposition(feature_matrix, transform, num_features, 1);
-
-  *rank = 0;
-  /* Prevent over-fitting when a small window is used. */
-  int max_rank = min(num_features, num_pixels / 3);
-  if (pca_threshold < 0.0f) {
-    float threshold_energy = 0.0f;
-    for (int i = 0; i < num_features; i++) {
-      threshold_energy += feature_matrix[i * num_features + i];
-    }
-    threshold_energy *= 1.0f - (-pca_threshold);
-
-    float reduced_energy = 0.0f;
-    for (int i = 0; i < max_rank; i++, (*rank)++) {
-      if (i >= 2 && reduced_energy >= threshold_energy)
-        break;
-      float s = feature_matrix[i * num_features + i];
-      reduced_energy += s;
-    }
-  }
-  else {
-    for (int i = 0; i < max_rank; i++, (*rank)++) {
-      float s = feature_matrix[i * num_features + i];
-      if (i >= 2 && sqrtf(s) < pca_threshold)
-        break;
-    }
-  }
-
-  math_matrix_transpose(transform, num_features, 1);
-
-  /* Bake the feature scaling into the transformation matrix. */
-  for (int i = 0; i < num_features; i++) {
-    math_vector_scale(transform + i * num_features, feature_scale[i][0], *rank);
-  }
-}
-
-CCL_NAMESPACE_END