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, 232 deletions

diff --git a/intern/cycles/kernel/kernels/cuda/kernel.cu b/intern/cycles/kernel/kernels/cuda/kernel.cu
deleted file mode 100644
index cf62b6e781e..00000000000
--- a/intern/cycles/kernel/kernels/cuda/kernel.cu
+++ /dev/null
@@ -1,232 +0,0 @@
-/*
- * Copyright 2011-2013 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/kernel_compat_cuda.h"
-#include "kernel_config.h"
-
-#include "util/util_atomic.h"
-
-#include "kernel/kernel_math.h"
-#include "kernel/kernel_types.h"
-#include "kernel/kernel_globals.h"
-#include "kernel/kernel_color.h"
-#include "kernel/kernels/cuda/kernel_cuda_image.h"
-#include "kernel/kernel_film.h"
-#include "kernel/kernel_path.h"
-#include "kernel/kernel_path_branched.h"
-#include "kernel/kernel_bake.h"
-#include "kernel/kernel_work_stealing.h"
-#include "kernel/kernel_adaptive_sampling.h"
-
-/* kernels */
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_path_trace(WorkTile *tile, uint total_work_size)
-{
-	int work_index = ccl_global_id(0);
-	bool thread_is_active = work_index < total_work_size;
-	uint x, y, sample;
-	KernelGlobals kg;
-	if(thread_is_active) {
-		get_work_pixel(tile, work_index, &x, &y, &sample);
-
-		kernel_path_trace(&kg, tile->buffer, sample, x, y, tile->offset, tile->stride);
-	}
-
-	if(kernel_data.film.cryptomatte_passes) {
-		__syncthreads();
-		if(thread_is_active) {
-			kernel_cryptomatte_post(&kg, tile->buffer, sample, x, y, tile->offset, tile->stride);
-		}
-	}
-}
-
-#ifdef __BRANCHED_PATH__
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_BRANCHED_MAX_REGISTERS)
-kernel_cuda_branched_path_trace(WorkTile *tile, uint total_work_size)
-{
-	int work_index = ccl_global_id(0);
-	bool thread_is_active = work_index < total_work_size;
-	uint x, y, sample;
-	KernelGlobals kg;
-	if(thread_is_active) {
-		get_work_pixel(tile, work_index, &x, &y, &sample);
-
-		kernel_branched_path_trace(&kg, tile->buffer, sample, x, y, tile->offset, tile->stride);
-	}
-	
-	if(kernel_data.film.cryptomatte_passes) {
-		__syncthreads();
-		if(thread_is_active) {
-			kernel_cryptomatte_post(&kg, tile->buffer, sample, x, y, tile->offset, tile->stride);
-		}
-	}
-}
-#endif
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_adaptive_stopping(WorkTile *tile, int sample, uint total_work_size)
-{
-	int work_index = ccl_global_id(0);
-	bool thread_is_active = work_index < total_work_size;
-	KernelGlobals kg;
-	if(thread_is_active && kernel_data.film.pass_adaptive_aux_buffer) {
-		uint x = tile->x + work_index % tile->w;
-		uint y = tile->y + work_index / tile->w;
-		int index = tile->offset + x + y * tile->stride;
-		ccl_global float *buffer = tile->buffer + index * kernel_data.film.pass_stride;
-		kernel_do_adaptive_stopping(&kg, buffer, sample);
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_adaptive_filter_x(WorkTile *tile, int sample, uint)
-{
-	KernelGlobals kg;
-	if(kernel_data.film.pass_adaptive_aux_buffer && sample > kernel_data.integrator.adaptive_min_samples) {
-		if(ccl_global_id(0) < tile->h) {
-			int y = tile->y + ccl_global_id(0);
-			kernel_do_adaptive_filter_x(&kg, y, tile);
-		}
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_adaptive_filter_y(WorkTile *tile, int sample, uint)
-{
-	KernelGlobals kg;
-	if(kernel_data.film.pass_adaptive_aux_buffer && sample > kernel_data.integrator.adaptive_min_samples) {
-		if(ccl_global_id(0) < tile->w) {
-			int x = tile->x + ccl_global_id(0);
-			kernel_do_adaptive_filter_y(&kg, x, tile);
-		}
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_adaptive_scale_samples(WorkTile *tile, int start_sample, int sample, uint total_work_size)
-{
-	if(kernel_data.film.pass_adaptive_aux_buffer) {
-		int work_index = ccl_global_id(0);
-		bool thread_is_active = work_index < total_work_size;
-		KernelGlobals kg;
-		if(thread_is_active) {
-			uint x = tile->x + work_index % tile->w;
-			uint y = tile->y + work_index / tile->w;
-			int index = tile->offset + x + y * tile->stride;
-			ccl_global float *buffer = tile->buffer + index * kernel_data.film.pass_stride;
-			if(buffer[kernel_data.film.pass_sample_count] < 0.0f) {
-				buffer[kernel_data.film.pass_sample_count] = -buffer[kernel_data.film.pass_sample_count];
-				float sample_multiplier = sample / buffer[kernel_data.film.pass_sample_count];
-				if(sample_multiplier != 1.0f) {
-					kernel_adaptive_post_adjust(&kg, buffer, sample_multiplier);
-				}
-			}
-			else {
-				kernel_adaptive_post_adjust(&kg, buffer, sample / (sample - 1.0f));
-			}
-		}
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_convert_to_byte(uchar4 *rgba, float *buffer, float sample_scale, int sx, int sy, int sw, int sh, int offset, int stride)
-{
-	int x = sx + blockDim.x*blockIdx.x + threadIdx.x;
-	int y = sy + blockDim.y*blockIdx.y + threadIdx.y;
-
-	if(x < sx + sw && y < sy + sh) {
-		kernel_film_convert_to_byte(NULL, rgba, buffer, sample_scale, x, y, offset, stride);
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_convert_to_half_float(uchar4 *rgba, float *buffer, float sample_scale, int sx, int sy, int sw, int sh, int offset, int stride)
-{
-	int x = sx + blockDim.x*blockIdx.x + threadIdx.x;
-	int y = sy + blockDim.y*blockIdx.y + threadIdx.y;
-
-	if(x < sx + sw && y < sy + sh) {
-		kernel_film_convert_to_half_float(NULL, rgba, buffer, sample_scale, x, y, offset, stride);
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_displace(uint4 *input,
-                     float4 *output,
-                     int type,
-                     int sx,
-                     int sw,
-                     int offset,
-                     int sample)
-{
-	int x = sx + blockDim.x*blockIdx.x + threadIdx.x;
-
-	if(x < sx + sw) {
-		KernelGlobals kg;
-		kernel_displace_evaluate(&kg, input, output, x);
-	}
-}
-
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_background(uint4 *input,
-                       float4 *output,
-                       int type,
-                       int sx,
-                       int sw,
-                       int offset,
-                       int sample)
-{
-	int x = sx + blockDim.x*blockIdx.x + threadIdx.x;
-
-	if(x < sx + sw) {
-		KernelGlobals kg;
-		kernel_background_evaluate(&kg, input, output, x);
-	}
-}
-
-#ifdef __BAKING__
-extern "C" __global__ void
-CUDA_LAUNCH_BOUNDS(CUDA_THREADS_BLOCK_WIDTH, CUDA_KERNEL_MAX_REGISTERS)
-kernel_cuda_bake(WorkTile *tile, uint total_work_size)
-{
-	int work_index = ccl_global_id(0);
-
-	if(work_index < total_work_size) {
-		uint x, y, sample;
-		get_work_pixel(tile, work_index, &x, &y, &sample);
-
-		KernelGlobals kg;
-		kernel_bake_evaluate(&kg, tile->buffer, sample, x, y, tile->offset, tile->stride);
-	}
-}
-#endif
-
-#endif
-