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blender-archive/intern/cycles/device/device_cpu.cpp
Brecht Van Lommel d9773edaa3 Cycles: code refactor to bake using regular render session and tiles
There should be no user visible change from this, except that tile size
now affects performance. The goal here is to simplify bake denoising in
D3099, letting it reuse more denoising tiles and pass code.

A lot of code is now shared with regular rendering, with the two main
differences being that we read some render result passes from the bake API
when starting to render a tile, and call the bake kernel instead of the
path trace kernel.

With this kind of design where Cycles asks for tiles from the bake API,
it should eventually be easier to reduce memory usage, show tiles as
they are baked, or bake multiple passes at once, though there's still
quite some work needed for that.

Reviewers: #cycles

Subscribers: monio, wmatyjewicz, lukasstockner97, michaelknubben

Differential Revision: https://developer.blender.org/D3108
2020-05-15 20:25:24 +02:00

1379 lines
48 KiB
C++

/*
* 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.
*/
#include <stdlib.h>
#include <string.h>
/* So ImathMath is included before our kernel_cpu_compat. */
#ifdef WITH_OSL
/* So no context pollution happens from indirectly included windows.h */
# include "util/util_windows.h"
# include <OSL/oslexec.h>
#endif
#include "device/device.h"
#include "device/device_denoising.h"
#include "device/device_intern.h"
#include "device/device_split_kernel.h"
// clang-format off
#include "kernel/kernel.h"
#include "kernel/kernel_compat_cpu.h"
#include "kernel/kernel_types.h"
#include "kernel/split/kernel_split_data.h"
#include "kernel/kernel_globals.h"
#include "kernel/kernel_adaptive_sampling.h"
#include "kernel/filter/filter.h"
#include "kernel/osl/osl_shader.h"
#include "kernel/osl/osl_globals.h"
// clang-format on
#include "render/buffers.h"
#include "render/coverage.h"
#include "util/util_debug.h"
#include "util/util_foreach.h"
#include "util/util_function.h"
#include "util/util_logging.h"
#include "util/util_map.h"
#include "util/util_opengl.h"
#include "util/util_optimization.h"
#include "util/util_progress.h"
#include "util/util_system.h"
#include "util/util_thread.h"
CCL_NAMESPACE_BEGIN
class CPUDevice;
/* Has to be outside of the class to be shared across template instantiations. */
static const char *logged_architecture = "";
template<typename F> class KernelFunctions {
public:
KernelFunctions()
{
kernel = (F)NULL;
}
KernelFunctions(
F kernel_default, F kernel_sse2, F kernel_sse3, F kernel_sse41, F kernel_avx, F kernel_avx2)
{
const char *architecture_name = "default";
kernel = kernel_default;
/* Silence potential warnings about unused variables
* when compiling without some architectures. */
(void)kernel_sse2;
(void)kernel_sse3;
(void)kernel_sse41;
(void)kernel_avx;
(void)kernel_avx2;
#ifdef WITH_CYCLES_OPTIMIZED_KERNEL_AVX2
if (DebugFlags().cpu.has_avx2() && system_cpu_support_avx2()) {
architecture_name = "AVX2";
kernel = kernel_avx2;
}
else
#endif
#ifdef WITH_CYCLES_OPTIMIZED_KERNEL_AVX
if (DebugFlags().cpu.has_avx() && system_cpu_support_avx()) {
architecture_name = "AVX";
kernel = kernel_avx;
}
else
#endif
#ifdef WITH_CYCLES_OPTIMIZED_KERNEL_SSE41
if (DebugFlags().cpu.has_sse41() && system_cpu_support_sse41()) {
architecture_name = "SSE4.1";
kernel = kernel_sse41;
}
else
#endif
#ifdef WITH_CYCLES_OPTIMIZED_KERNEL_SSE3
if (DebugFlags().cpu.has_sse3() && system_cpu_support_sse3()) {
architecture_name = "SSE3";
kernel = kernel_sse3;
}
else
#endif
#ifdef WITH_CYCLES_OPTIMIZED_KERNEL_SSE2
if (DebugFlags().cpu.has_sse2() && system_cpu_support_sse2()) {
architecture_name = "SSE2";
kernel = kernel_sse2;
}
#else
{
/* Dummy to prevent the architecture if below become
* conditional when WITH_CYCLES_OPTIMIZED_KERNEL_SSE2
* is not defined. */
}
#endif
if (strcmp(architecture_name, logged_architecture) != 0) {
VLOG(1) << "Will be using " << architecture_name << " kernels.";
logged_architecture = architecture_name;
}
}
inline F operator()() const
{
assert(kernel);
return kernel;
}
protected:
F kernel;
};
class CPUSplitKernel : public DeviceSplitKernel {
CPUDevice *device;
public:
explicit CPUSplitKernel(CPUDevice *device);
virtual bool enqueue_split_kernel_data_init(const KernelDimensions &dim,
RenderTile &rtile,
int num_global_elements,
device_memory &kernel_globals,
device_memory &kernel_data_,
device_memory &split_data,
device_memory &ray_state,
device_memory &queue_index,
device_memory &use_queues_flag,
device_memory &work_pool_wgs);
virtual SplitKernelFunction *get_split_kernel_function(const string &kernel_name,
const DeviceRequestedFeatures &);
virtual int2 split_kernel_local_size();
virtual int2 split_kernel_global_size(device_memory &kg, device_memory &data, DeviceTask *task);
virtual uint64_t state_buffer_size(device_memory &kg, device_memory &data, size_t num_threads);
};
class CPUDevice : public Device {
public:
TaskPool task_pool;
KernelGlobals kernel_globals;
device_vector<TextureInfo> texture_info;
bool need_texture_info;
#ifdef WITH_OSL
OSLGlobals osl_globals;
#endif
bool use_split_kernel;
DeviceRequestedFeatures requested_features;
KernelFunctions<void (*)(KernelGlobals *, float *, int, int, int, int, int)> path_trace_kernel;
KernelFunctions<void (*)(KernelGlobals *, uchar4 *, float *, float, int, int, int, int)>
convert_to_half_float_kernel;
KernelFunctions<void (*)(KernelGlobals *, uchar4 *, float *, float, int, int, int, int)>
convert_to_byte_kernel;
KernelFunctions<void (*)(KernelGlobals *, uint4 *, float4 *, int, int, int, int, int)>
shader_kernel;
KernelFunctions<void (*)(KernelGlobals *, float *, int, int, int, int, int)> bake_kernel;
KernelFunctions<void (*)(
int, TileInfo *, int, int, float *, float *, float *, float *, float *, int *, int, int)>
filter_divide_shadow_kernel;
KernelFunctions<void (*)(
int, TileInfo *, int, int, int, int, float *, float *, float, int *, int, int)>
filter_get_feature_kernel;
KernelFunctions<void (*)(int, int, int, int *, float *, float *, int, int *)>
filter_write_feature_kernel;
KernelFunctions<void (*)(int, int, float *, float *, float *, float *, int *, int)>
filter_detect_outliers_kernel;
KernelFunctions<void (*)(int, int, float *, float *, float *, float *, int *, int)>
filter_combine_halves_kernel;
KernelFunctions<void (*)(
int, int, float *, float *, float *, float *, int *, int, int, int, float, float)>
filter_nlm_calc_difference_kernel;
KernelFunctions<void (*)(float *, float *, int *, int, int)> filter_nlm_blur_kernel;
KernelFunctions<void (*)(float *, float *, int *, int, int)> filter_nlm_calc_weight_kernel;
KernelFunctions<void (*)(
int, int, float *, float *, float *, float *, float *, int *, int, int, int)>
filter_nlm_update_output_kernel;
KernelFunctions<void (*)(float *, float *, int *, int)> filter_nlm_normalize_kernel;
KernelFunctions<void (*)(
float *, TileInfo *, int, int, int, float *, int *, int *, int, int, bool, int, float)>
filter_construct_transform_kernel;
KernelFunctions<void (*)(int,
int,
int,
float *,
float *,
float *,
int *,
float *,
float3 *,
int *,
int *,
int,
int,
int,
int,
bool)>
filter_nlm_construct_gramian_kernel;
KernelFunctions<void (*)(int, int, int, float *, int *, float *, float3 *, int *, int)>
filter_finalize_kernel;
KernelFunctions<void (*)(KernelGlobals *,
ccl_constant KernelData *,
ccl_global void *,
int,
ccl_global char *,
int,
int,
int,
int,
int,
int,
int,
int,
ccl_global int *,
int,
ccl_global char *,
ccl_global unsigned int *,
unsigned int,
ccl_global float *)>
data_init_kernel;
unordered_map<string, KernelFunctions<void (*)(KernelGlobals *, KernelData *)>> split_kernels;
#define KERNEL_FUNCTIONS(name) \
KERNEL_NAME_EVAL(cpu, name), KERNEL_NAME_EVAL(cpu_sse2, name), \
KERNEL_NAME_EVAL(cpu_sse3, name), KERNEL_NAME_EVAL(cpu_sse41, name), \
KERNEL_NAME_EVAL(cpu_avx, name), KERNEL_NAME_EVAL(cpu_avx2, name)
CPUDevice(DeviceInfo &info_, Stats &stats_, Profiler &profiler_, bool background_)
: Device(info_, stats_, profiler_, background_),
texture_info(this, "__texture_info", MEM_GLOBAL),
#define REGISTER_KERNEL(name) name##_kernel(KERNEL_FUNCTIONS(name))
REGISTER_KERNEL(path_trace),
REGISTER_KERNEL(convert_to_half_float),
REGISTER_KERNEL(convert_to_byte),
REGISTER_KERNEL(shader),
REGISTER_KERNEL(bake),
REGISTER_KERNEL(filter_divide_shadow),
REGISTER_KERNEL(filter_get_feature),
REGISTER_KERNEL(filter_write_feature),
REGISTER_KERNEL(filter_detect_outliers),
REGISTER_KERNEL(filter_combine_halves),
REGISTER_KERNEL(filter_nlm_calc_difference),
REGISTER_KERNEL(filter_nlm_blur),
REGISTER_KERNEL(filter_nlm_calc_weight),
REGISTER_KERNEL(filter_nlm_update_output),
REGISTER_KERNEL(filter_nlm_normalize),
REGISTER_KERNEL(filter_construct_transform),
REGISTER_KERNEL(filter_nlm_construct_gramian),
REGISTER_KERNEL(filter_finalize),
REGISTER_KERNEL(data_init)
#undef REGISTER_KERNEL
{
if (info.cpu_threads == 0) {
info.cpu_threads = TaskScheduler::num_threads();
}
#ifdef WITH_OSL
kernel_globals.osl = &osl_globals;
#endif
use_split_kernel = DebugFlags().cpu.split_kernel;
if (use_split_kernel) {
VLOG(1) << "Will be using split kernel.";
}
need_texture_info = false;
#define REGISTER_SPLIT_KERNEL(name) \
split_kernels[#name] = KernelFunctions<void (*)(KernelGlobals *, KernelData *)>( \
KERNEL_FUNCTIONS(name))
REGISTER_SPLIT_KERNEL(path_init);
REGISTER_SPLIT_KERNEL(scene_intersect);
REGISTER_SPLIT_KERNEL(lamp_emission);
REGISTER_SPLIT_KERNEL(do_volume);
REGISTER_SPLIT_KERNEL(queue_enqueue);
REGISTER_SPLIT_KERNEL(indirect_background);
REGISTER_SPLIT_KERNEL(shader_setup);
REGISTER_SPLIT_KERNEL(shader_sort);
REGISTER_SPLIT_KERNEL(shader_eval);
REGISTER_SPLIT_KERNEL(holdout_emission_blurring_pathtermination_ao);
REGISTER_SPLIT_KERNEL(subsurface_scatter);
REGISTER_SPLIT_KERNEL(direct_lighting);
REGISTER_SPLIT_KERNEL(shadow_blocked_ao);
REGISTER_SPLIT_KERNEL(shadow_blocked_dl);
REGISTER_SPLIT_KERNEL(enqueue_inactive);
REGISTER_SPLIT_KERNEL(next_iteration_setup);
REGISTER_SPLIT_KERNEL(indirect_subsurface);
REGISTER_SPLIT_KERNEL(buffer_update);
REGISTER_SPLIT_KERNEL(adaptive_stopping);
REGISTER_SPLIT_KERNEL(adaptive_filter_x);
REGISTER_SPLIT_KERNEL(adaptive_filter_y);
REGISTER_SPLIT_KERNEL(adaptive_adjust_samples);
#undef REGISTER_SPLIT_KERNEL
#undef KERNEL_FUNCTIONS
}
~CPUDevice()
{
task_pool.stop();
texture_info.free();
}
virtual bool show_samples() const
{
return (info.cpu_threads == 1);
}
virtual BVHLayoutMask get_bvh_layout_mask() const
{
BVHLayoutMask bvh_layout_mask = BVH_LAYOUT_BVH2;
if (DebugFlags().cpu.has_sse2() && system_cpu_support_sse2()) {
bvh_layout_mask |= BVH_LAYOUT_BVH4;
}
/* MSVC does not support the -march=native switch and you always end up */
/* with an sse2 kernel when you use WITH_KERNEL_NATIVE. We *cannot* feed */
/* that kernel BVH8 even if the CPU flags would allow for it. */
#if (defined(__x86_64__) || defined(_M_X64)) && !(defined(_MSC_VER) && defined(WITH_KERNEL_NATIVE))
if (DebugFlags().cpu.has_avx2() && system_cpu_support_avx2()) {
bvh_layout_mask |= BVH_LAYOUT_BVH8;
}
#endif
#ifdef WITH_EMBREE
bvh_layout_mask |= BVH_LAYOUT_EMBREE;
#endif /* WITH_EMBREE */
return bvh_layout_mask;
}
void load_texture_info()
{
if (need_texture_info) {
texture_info.copy_to_device();
need_texture_info = false;
}
}
void mem_alloc(device_memory &mem)
{
if (mem.type == MEM_TEXTURE) {
assert(!"mem_alloc not supported for textures.");
}
else if (mem.type == MEM_GLOBAL) {
assert(!"mem_alloc not supported for global memory.");
}
else {
if (mem.name) {
VLOG(1) << "Buffer allocate: " << mem.name << ", "
<< string_human_readable_number(mem.memory_size()) << " bytes. ("
<< string_human_readable_size(mem.memory_size()) << ")";
}
if (mem.type == MEM_DEVICE_ONLY) {
assert(!mem.host_pointer);
size_t alignment = MIN_ALIGNMENT_CPU_DATA_TYPES;
void *data = util_aligned_malloc(mem.memory_size(), alignment);
mem.device_pointer = (device_ptr)data;
}
else {
mem.device_pointer = (device_ptr)mem.host_pointer;
}
mem.device_size = mem.memory_size();
stats.mem_alloc(mem.device_size);
}
}
void mem_copy_to(device_memory &mem)
{
if (mem.type == MEM_GLOBAL) {
global_free(mem);
global_alloc(mem);
}
else if (mem.type == MEM_TEXTURE) {
tex_free((device_texture &)mem);
tex_alloc((device_texture &)mem);
}
else if (mem.type == MEM_PIXELS) {
assert(!"mem_copy_to not supported for pixels.");
}
else {
if (!mem.device_pointer) {
mem_alloc(mem);
}
/* copy is no-op */
}
}
void mem_copy_from(device_memory & /*mem*/, int /*y*/, int /*w*/, int /*h*/, int /*elem*/)
{
/* no-op */
}
void mem_zero(device_memory &mem)
{
if (!mem.device_pointer) {
mem_alloc(mem);
}
if (mem.device_pointer) {
memset((void *)mem.device_pointer, 0, mem.memory_size());
}
}
void mem_free(device_memory &mem)
{
if (mem.type == MEM_GLOBAL) {
global_free(mem);
}
else if (mem.type == MEM_TEXTURE) {
tex_free((device_texture &)mem);
}
else if (mem.device_pointer) {
if (mem.type == MEM_DEVICE_ONLY) {
util_aligned_free((void *)mem.device_pointer);
}
mem.device_pointer = 0;
stats.mem_free(mem.device_size);
mem.device_size = 0;
}
}
virtual device_ptr mem_alloc_sub_ptr(device_memory &mem, int offset, int /*size*/)
{
return (device_ptr)(((char *)mem.device_pointer) + mem.memory_elements_size(offset));
}
void const_copy_to(const char *name, void *host, size_t size)
{
kernel_const_copy(&kernel_globals, name, host, size);
}
void global_alloc(device_memory &mem)
{
VLOG(1) << "Global memory allocate: " << mem.name << ", "
<< string_human_readable_number(mem.memory_size()) << " bytes. ("
<< string_human_readable_size(mem.memory_size()) << ")";
kernel_global_memory_copy(&kernel_globals, mem.name, mem.host_pointer, mem.data_size);
mem.device_pointer = (device_ptr)mem.host_pointer;
mem.device_size = mem.memory_size();
stats.mem_alloc(mem.device_size);
}
void global_free(device_memory &mem)
{
if (mem.device_pointer) {
mem.device_pointer = 0;
stats.mem_free(mem.device_size);
mem.device_size = 0;
}
}
void tex_alloc(device_texture &mem)
{
VLOG(1) << "Texture allocate: " << mem.name << ", "
<< string_human_readable_number(mem.memory_size()) << " bytes. ("
<< string_human_readable_size(mem.memory_size()) << ")";
mem.device_pointer = (device_ptr)mem.host_pointer;
mem.device_size = mem.memory_size();
stats.mem_alloc(mem.device_size);
const uint slot = mem.slot;
if (slot >= texture_info.size()) {
/* Allocate some slots in advance, to reduce amount of re-allocations. */
texture_info.resize(slot + 128);
}
texture_info[slot] = mem.info;
texture_info[slot].data = (uint64_t)mem.host_pointer;
need_texture_info = true;
}
void tex_free(device_texture &mem)
{
if (mem.device_pointer) {
mem.device_pointer = 0;
stats.mem_free(mem.device_size);
mem.device_size = 0;
need_texture_info = true;
}
}
void *osl_memory()
{
#ifdef WITH_OSL
return &osl_globals;
#else
return NULL;
#endif
}
void thread_run(DeviceTask *task)
{
if (task->type == DeviceTask::RENDER)
thread_render(*task);
else if (task->type == DeviceTask::SHADER)
thread_shader(*task);
else if (task->type == DeviceTask::FILM_CONVERT)
thread_film_convert(*task);
else if (task->type == DeviceTask::DENOISE_BUFFER)
thread_denoise(*task);
}
class CPUDeviceTask : public DeviceTask {
public:
CPUDeviceTask(CPUDevice *device, DeviceTask &task) : DeviceTask(task)
{
run = function_bind(&CPUDevice::thread_run, device, this);
}
};
bool denoising_non_local_means(device_ptr image_ptr,
device_ptr guide_ptr,
device_ptr variance_ptr,
device_ptr out_ptr,
DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_NON_LOCAL_MEANS);
int4 rect = task->rect;
int r = task->nlm_state.r;
int f = task->nlm_state.f;
float a = task->nlm_state.a;
float k_2 = task->nlm_state.k_2;
int w = align_up(rect.z - rect.x, 4);
int h = rect.w - rect.y;
int stride = task->buffer.stride;
int channel_offset = task->nlm_state.is_color ? task->buffer.pass_stride : 0;
float *temporary_mem = (float *)task->buffer.temporary_mem.device_pointer;
float *blurDifference = temporary_mem;
float *difference = temporary_mem + task->buffer.pass_stride;
float *weightAccum = temporary_mem + 2 * task->buffer.pass_stride;
memset(weightAccum, 0, sizeof(float) * w * h);
memset((float *)out_ptr, 0, sizeof(float) * w * h);
for (int i = 0; i < (2 * r + 1) * (2 * r + 1); i++) {
int dy = i / (2 * r + 1) - r;
int dx = i % (2 * r + 1) - r;
int local_rect[4] = {
max(0, -dx), max(0, -dy), rect.z - rect.x - max(0, dx), rect.w - rect.y - max(0, dy)};
filter_nlm_calc_difference_kernel()(dx,
dy,
(float *)guide_ptr,
(float *)variance_ptr,
NULL,
difference,
local_rect,
w,
channel_offset,
0,
a,
k_2);
filter_nlm_blur_kernel()(difference, blurDifference, local_rect, w, f);
filter_nlm_calc_weight_kernel()(blurDifference, difference, local_rect, w, f);
filter_nlm_blur_kernel()(difference, blurDifference, local_rect, w, f);
filter_nlm_update_output_kernel()(dx,
dy,
blurDifference,
(float *)image_ptr,
difference,
(float *)out_ptr,
weightAccum,
local_rect,
channel_offset,
stride,
f);
}
int local_rect[4] = {0, 0, rect.z - rect.x, rect.w - rect.y};
filter_nlm_normalize_kernel()((float *)out_ptr, weightAccum, local_rect, w);
return true;
}
bool denoising_construct_transform(DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_CONSTRUCT_TRANSFORM);
for (int y = 0; y < task->filter_area.w; y++) {
for (int x = 0; x < task->filter_area.z; x++) {
filter_construct_transform_kernel()((float *)task->buffer.mem.device_pointer,
task->tile_info,
x + task->filter_area.x,
y + task->filter_area.y,
y * task->filter_area.z + x,
(float *)task->storage.transform.device_pointer,
(int *)task->storage.rank.device_pointer,
&task->rect.x,
task->buffer.pass_stride,
task->buffer.frame_stride,
task->buffer.use_time,
task->radius,
task->pca_threshold);
}
}
return true;
}
bool denoising_accumulate(device_ptr color_ptr,
device_ptr color_variance_ptr,
device_ptr scale_ptr,
int frame,
DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_RECONSTRUCT);
float *temporary_mem = (float *)task->buffer.temporary_mem.device_pointer;
float *difference = temporary_mem;
float *blurDifference = temporary_mem + task->buffer.pass_stride;
int r = task->radius;
int frame_offset = frame * task->buffer.frame_stride;
for (int i = 0; i < (2 * r + 1) * (2 * r + 1); i++) {
int dy = i / (2 * r + 1) - r;
int dx = i % (2 * r + 1) - r;
int local_rect[4] = {max(0, -dx),
max(0, -dy),
task->reconstruction_state.source_w - max(0, dx),
task->reconstruction_state.source_h - max(0, dy)};
filter_nlm_calc_difference_kernel()(dx,
dy,
(float *)color_ptr,
(float *)color_variance_ptr,
(float *)scale_ptr,
difference,
local_rect,
task->buffer.stride,
task->buffer.pass_stride,
frame_offset,
1.0f,
task->nlm_k_2);
filter_nlm_blur_kernel()(difference, blurDifference, local_rect, task->buffer.stride, 4);
filter_nlm_calc_weight_kernel()(
blurDifference, difference, local_rect, task->buffer.stride, 4);
filter_nlm_blur_kernel()(difference, blurDifference, local_rect, task->buffer.stride, 4);
filter_nlm_construct_gramian_kernel()(dx,
dy,
task->tile_info->frames[frame],
blurDifference,
(float *)task->buffer.mem.device_pointer,
(float *)task->storage.transform.device_pointer,
(int *)task->storage.rank.device_pointer,
(float *)task->storage.XtWX.device_pointer,
(float3 *)task->storage.XtWY.device_pointer,
local_rect,
&task->reconstruction_state.filter_window.x,
task->buffer.stride,
4,
task->buffer.pass_stride,
frame_offset,
task->buffer.use_time);
}
return true;
}
bool denoising_solve(device_ptr output_ptr, DenoisingTask *task)
{
for (int y = 0; y < task->filter_area.w; y++) {
for (int x = 0; x < task->filter_area.z; x++) {
filter_finalize_kernel()(x,
y,
y * task->filter_area.z + x,
(float *)output_ptr,
(int *)task->storage.rank.device_pointer,
(float *)task->storage.XtWX.device_pointer,
(float3 *)task->storage.XtWY.device_pointer,
&task->reconstruction_state.buffer_params.x,
task->render_buffer.samples);
}
}
return true;
}
bool denoising_combine_halves(device_ptr a_ptr,
device_ptr b_ptr,
device_ptr mean_ptr,
device_ptr variance_ptr,
int r,
int4 rect,
DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_COMBINE_HALVES);
for (int y = rect.y; y < rect.w; y++) {
for (int x = rect.x; x < rect.z; x++) {
filter_combine_halves_kernel()(x,
y,
(float *)mean_ptr,
(float *)variance_ptr,
(float *)a_ptr,
(float *)b_ptr,
&rect.x,
r);
}
}
return true;
}
bool denoising_divide_shadow(device_ptr a_ptr,
device_ptr b_ptr,
device_ptr sample_variance_ptr,
device_ptr sv_variance_ptr,
device_ptr buffer_variance_ptr,
DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_DIVIDE_SHADOW);
for (int y = task->rect.y; y < task->rect.w; y++) {
for (int x = task->rect.x; x < task->rect.z; x++) {
filter_divide_shadow_kernel()(task->render_buffer.samples,
task->tile_info,
x,
y,
(float *)a_ptr,
(float *)b_ptr,
(float *)sample_variance_ptr,
(float *)sv_variance_ptr,
(float *)buffer_variance_ptr,
&task->rect.x,
task->render_buffer.pass_stride,
task->render_buffer.offset);
}
}
return true;
}
bool denoising_get_feature(int mean_offset,
int variance_offset,
device_ptr mean_ptr,
device_ptr variance_ptr,
float scale,
DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_GET_FEATURE);
for (int y = task->rect.y; y < task->rect.w; y++) {
for (int x = task->rect.x; x < task->rect.z; x++) {
filter_get_feature_kernel()(task->render_buffer.samples,
task->tile_info,
mean_offset,
variance_offset,
x,
y,
(float *)mean_ptr,
(float *)variance_ptr,
scale,
&task->rect.x,
task->render_buffer.pass_stride,
task->render_buffer.offset);
}
}
return true;
}
bool denoising_write_feature(int out_offset,
device_ptr from_ptr,
device_ptr buffer_ptr,
DenoisingTask *task)
{
for (int y = 0; y < task->filter_area.w; y++) {
for (int x = 0; x < task->filter_area.z; x++) {
filter_write_feature_kernel()(task->render_buffer.samples,
x + task->filter_area.x,
y + task->filter_area.y,
&task->reconstruction_state.buffer_params.x,
(float *)from_ptr,
(float *)buffer_ptr,
out_offset,
&task->rect.x);
}
}
return true;
}
bool denoising_detect_outliers(device_ptr image_ptr,
device_ptr variance_ptr,
device_ptr depth_ptr,
device_ptr output_ptr,
DenoisingTask *task)
{
ProfilingHelper profiling(task->profiler, PROFILING_DENOISING_DETECT_OUTLIERS);
for (int y = task->rect.y; y < task->rect.w; y++) {
for (int x = task->rect.x; x < task->rect.z; x++) {
filter_detect_outliers_kernel()(x,
y,
(float *)image_ptr,
(float *)variance_ptr,
(float *)depth_ptr,
(float *)output_ptr,
&task->rect.x,
task->buffer.pass_stride);
}
}
return true;
}
bool adaptive_sampling_filter(KernelGlobals *kg, RenderTile &tile, int sample)
{
WorkTile wtile;
wtile.x = tile.x;
wtile.y = tile.y;
wtile.w = tile.w;
wtile.h = tile.h;
wtile.offset = tile.offset;
wtile.stride = tile.stride;
wtile.buffer = (float *)tile.buffer;
/* For CPU we do adaptive stopping per sample so we can stop earlier, but
* for combined CPU + GPU rendering we match the GPU and do it per tile
* after a given number of sample steps. */
if (!kernel_data.integrator.adaptive_stop_per_sample) {
for (int y = wtile.y; y < wtile.y + wtile.h; ++y) {
for (int x = wtile.x; x < wtile.x + wtile.w; ++x) {
const int index = wtile.offset + x + y * wtile.stride;
float *buffer = wtile.buffer + index * kernel_data.film.pass_stride;
kernel_do_adaptive_stopping(kg, buffer, sample);
}
}
}
bool any = false;
for (int y = wtile.y; y < wtile.y + wtile.h; ++y) {
any |= kernel_do_adaptive_filter_x(kg, y, &wtile);
}
for (int x = wtile.x; x < wtile.x + wtile.w; ++x) {
any |= kernel_do_adaptive_filter_y(kg, x, &wtile);
}
return (!any);
}
void adaptive_sampling_post(const RenderTile &tile, KernelGlobals *kg)
{
float *render_buffer = (float *)tile.buffer;
for (int y = tile.y; y < tile.y + tile.h; y++) {
for (int x = tile.x; x < tile.x + tile.w; x++) {
int index = tile.offset + x + y * tile.stride;
ccl_global float *buffer = render_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 = tile.sample / max((float)tile.start_sample + 1.0f,
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, tile.sample / (tile.sample - 1.0f));
}
}
}
}
void render(DeviceTask &task, RenderTile &tile, KernelGlobals *kg)
{
const bool use_coverage = kernel_data.film.cryptomatte_passes & CRYPT_ACCURATE;
scoped_timer timer(&tile.buffers->render_time);
Coverage coverage(kg, tile);
if (use_coverage) {
coverage.init_path_trace();
}
float *render_buffer = (float *)tile.buffer;
int start_sample = tile.start_sample;
int end_sample = tile.start_sample + tile.num_samples;
/* Needed for Embree. */
SIMD_SET_FLUSH_TO_ZERO;
for (int sample = start_sample; sample < end_sample; sample++) {
if (task.get_cancel() || task_pool.canceled()) {
if (task.need_finish_queue == false)
break;
}
if (tile.task == RenderTile::PATH_TRACE) {
for (int y = tile.y; y < tile.y + tile.h; y++) {
for (int x = tile.x; x < tile.x + tile.w; x++) {
if (use_coverage) {
coverage.init_pixel(x, y);
}
path_trace_kernel()(kg, render_buffer, sample, x, y, tile.offset, tile.stride);
}
}
}
else {
for (int y = tile.y; y < tile.y + tile.h; y++) {
for (int x = tile.x; x < tile.x + tile.w; x++) {
bake_kernel()(kg, render_buffer, sample, x, y, tile.offset, tile.stride);
}
}
}
tile.sample = sample + 1;
if (task.adaptive_sampling.use && task.adaptive_sampling.need_filter(sample)) {
const bool stop = adaptive_sampling_filter(kg, tile, sample);
if (stop) {
const int num_progress_samples = end_sample - sample;
tile.sample = end_sample;
task.update_progress(&tile, tile.w * tile.h * num_progress_samples);
break;
}
}
task.update_progress(&tile, tile.w * tile.h);
}
if (use_coverage) {
coverage.finalize();
}
if (task.adaptive_sampling.use) {
adaptive_sampling_post(tile, kg);
}
}
void denoise(DenoisingTask &denoising, RenderTile &tile)
{
ProfilingHelper profiling(denoising.profiler, PROFILING_DENOISING);
tile.sample = tile.start_sample + tile.num_samples;
denoising.functions.construct_transform = function_bind(
&CPUDevice::denoising_construct_transform, this, &denoising);
denoising.functions.accumulate = function_bind(
&CPUDevice::denoising_accumulate, this, _1, _2, _3, _4, &denoising);
denoising.functions.solve = function_bind(&CPUDevice::denoising_solve, this, _1, &denoising);
denoising.functions.divide_shadow = function_bind(
&CPUDevice::denoising_divide_shadow, this, _1, _2, _3, _4, _5, &denoising);
denoising.functions.non_local_means = function_bind(
&CPUDevice::denoising_non_local_means, this, _1, _2, _3, _4, &denoising);
denoising.functions.combine_halves = function_bind(
&CPUDevice::denoising_combine_halves, this, _1, _2, _3, _4, _5, _6, &denoising);
denoising.functions.get_feature = function_bind(
&CPUDevice::denoising_get_feature, this, _1, _2, _3, _4, _5, &denoising);
denoising.functions.write_feature = function_bind(
&CPUDevice::denoising_write_feature, this, _1, _2, _3, &denoising);
denoising.functions.detect_outliers = function_bind(
&CPUDevice::denoising_detect_outliers, this, _1, _2, _3, _4, &denoising);
denoising.filter_area = make_int4(tile.x, tile.y, tile.w, tile.h);
denoising.render_buffer.samples = tile.sample;
denoising.buffer.gpu_temporary_mem = false;
denoising.run_denoising(&tile);
}
void thread_render(DeviceTask &task)
{
if (task_pool.canceled()) {
if (task.need_finish_queue == false)
return;
}
/* allocate buffer for kernel globals */
device_only_memory<KernelGlobals> kgbuffer(this, "kernel_globals");
kgbuffer.alloc_to_device(1);
KernelGlobals *kg = new ((void *)kgbuffer.device_pointer)
KernelGlobals(thread_kernel_globals_init());
profiler.add_state(&kg->profiler);
CPUSplitKernel *split_kernel = NULL;
if (use_split_kernel) {
split_kernel = new CPUSplitKernel(this);
if (!split_kernel->load_kernels(requested_features)) {
thread_kernel_globals_free((KernelGlobals *)kgbuffer.device_pointer);
kgbuffer.free();
delete split_kernel;
return;
}
}
RenderTile tile;
DenoisingTask denoising(this, task);
denoising.profiler = &kg->profiler;
while (task.acquire_tile(this, tile, task.tile_types)) {
if (tile.task == RenderTile::PATH_TRACE) {
if (use_split_kernel) {
device_only_memory<uchar> void_buffer(this, "void_buffer");
split_kernel->path_trace(&task, tile, kgbuffer, void_buffer);
}
else {
render(task, tile, kg);
}
}
else if (tile.task == RenderTile::BAKE) {
render(task, tile, kg);
}
else if (tile.task == RenderTile::DENOISE) {
denoise(denoising, tile);
task.update_progress(&tile, tile.w * tile.h);
}
task.release_tile(tile);
if (task_pool.canceled()) {
if (task.need_finish_queue == false)
break;
}
}
profiler.remove_state(&kg->profiler);
thread_kernel_globals_free((KernelGlobals *)kgbuffer.device_pointer);
kg->~KernelGlobals();
kgbuffer.free();
delete split_kernel;
}
void thread_denoise(DeviceTask &task)
{
RenderTile tile;
tile.x = task.x;
tile.y = task.y;
tile.w = task.w;
tile.h = task.h;
tile.buffer = task.buffer;
tile.sample = task.sample + task.num_samples;
tile.num_samples = task.num_samples;
tile.start_sample = task.sample;
tile.offset = task.offset;
tile.stride = task.stride;
tile.buffers = task.buffers;
DenoisingTask denoising(this, task);
ProfilingState denoising_profiler_state;
profiler.add_state(&denoising_profiler_state);
denoising.profiler = &denoising_profiler_state;
denoise(denoising, tile);
task.update_progress(&tile, tile.w * tile.h);
profiler.remove_state(&denoising_profiler_state);
}
void thread_film_convert(DeviceTask &task)
{
float sample_scale = 1.0f / (task.sample + 1);
if (task.rgba_half) {
for (int y = task.y; y < task.y + task.h; y++)
for (int x = task.x; x < task.x + task.w; x++)
convert_to_half_float_kernel()(&kernel_globals,
(uchar4 *)task.rgba_half,
(float *)task.buffer,
sample_scale,
x,
y,
task.offset,
task.stride);
}
else {
for (int y = task.y; y < task.y + task.h; y++)
for (int x = task.x; x < task.x + task.w; x++)
convert_to_byte_kernel()(&kernel_globals,
(uchar4 *)task.rgba_byte,
(float *)task.buffer,
sample_scale,
x,
y,
task.offset,
task.stride);
}
}
void thread_shader(DeviceTask &task)
{
KernelGlobals *kg = new KernelGlobals(thread_kernel_globals_init());
for (int sample = 0; sample < task.num_samples; sample++) {
for (int x = task.shader_x; x < task.shader_x + task.shader_w; x++)
shader_kernel()(kg,
(uint4 *)task.shader_input,
(float4 *)task.shader_output,
task.shader_eval_type,
task.shader_filter,
x,
task.offset,
sample);
if (task.get_cancel() || task_pool.canceled())
break;
task.update_progress(NULL);
}
thread_kernel_globals_free(kg);
delete kg;
}
int get_split_task_count(DeviceTask &task)
{
if (task.type == DeviceTask::SHADER)
return task.get_subtask_count(info.cpu_threads, 256);
else
return task.get_subtask_count(info.cpu_threads);
}
void task_add(DeviceTask &task)
{
/* Load texture info. */
load_texture_info();
/* split task into smaller ones */
list<DeviceTask> tasks;
if (task.type == DeviceTask::SHADER)
task.split(tasks, info.cpu_threads, 256);
else
task.split(tasks, info.cpu_threads);
foreach (DeviceTask &task, tasks)
task_pool.push(new CPUDeviceTask(this, task));
}
void task_wait()
{
task_pool.wait_work();
}
void task_cancel()
{
task_pool.cancel();
}
protected:
inline KernelGlobals thread_kernel_globals_init()
{
KernelGlobals kg = kernel_globals;
kg.transparent_shadow_intersections = NULL;
const int decoupled_count = sizeof(kg.decoupled_volume_steps) /
sizeof(*kg.decoupled_volume_steps);
for (int i = 0; i < decoupled_count; ++i) {
kg.decoupled_volume_steps[i] = NULL;
}
kg.decoupled_volume_steps_index = 0;
kg.coverage_asset = kg.coverage_object = kg.coverage_material = NULL;
#ifdef WITH_OSL
OSLShader::thread_init(&kg, &kernel_globals, &osl_globals);
#endif
return kg;
}
inline void thread_kernel_globals_free(KernelGlobals *kg)
{
if (kg == NULL) {
return;
}
if (kg->transparent_shadow_intersections != NULL) {
free(kg->transparent_shadow_intersections);
}
const int decoupled_count = sizeof(kg->decoupled_volume_steps) /
sizeof(*kg->decoupled_volume_steps);
for (int i = 0; i < decoupled_count; ++i) {
if (kg->decoupled_volume_steps[i] != NULL) {
free(kg->decoupled_volume_steps[i]);
}
}
#ifdef WITH_OSL
OSLShader::thread_free(kg);
#endif
}
virtual bool load_kernels(const DeviceRequestedFeatures &requested_features_)
{
requested_features = requested_features_;
return true;
}
};
/* split kernel */
class CPUSplitKernelFunction : public SplitKernelFunction {
public:
CPUDevice *device;
void (*func)(KernelGlobals *kg, KernelData *data);
CPUSplitKernelFunction(CPUDevice *device) : device(device), func(NULL)
{
}
~CPUSplitKernelFunction()
{
}
virtual bool enqueue(const KernelDimensions &dim,
device_memory &kernel_globals,
device_memory &data)
{
if (!func) {
return false;
}
KernelGlobals *kg = (KernelGlobals *)kernel_globals.device_pointer;
kg->global_size = make_int2(dim.global_size[0], dim.global_size[1]);
for (int y = 0; y < dim.global_size[1]; y++) {
for (int x = 0; x < dim.global_size[0]; x++) {
kg->global_id = make_int2(x, y);
func(kg, (KernelData *)data.device_pointer);
}
}
return true;
}
};
CPUSplitKernel::CPUSplitKernel(CPUDevice *device) : DeviceSplitKernel(device), device(device)
{
}
bool CPUSplitKernel::enqueue_split_kernel_data_init(const KernelDimensions &dim,
RenderTile &rtile,
int num_global_elements,
device_memory &kernel_globals,
device_memory &data,
device_memory &split_data,
device_memory &ray_state,
device_memory &queue_index,
device_memory &use_queues_flags,
device_memory &work_pool_wgs)
{
KernelGlobals *kg = (KernelGlobals *)kernel_globals.device_pointer;
kg->global_size = make_int2(dim.global_size[0], dim.global_size[1]);
for (int y = 0; y < dim.global_size[1]; y++) {
for (int x = 0; x < dim.global_size[0]; x++) {
kg->global_id = make_int2(x, y);
device->data_init_kernel()((KernelGlobals *)kernel_globals.device_pointer,
(KernelData *)data.device_pointer,
(void *)split_data.device_pointer,
num_global_elements,
(char *)ray_state.device_pointer,
rtile.start_sample,
rtile.start_sample + rtile.num_samples,
rtile.x,
rtile.y,
rtile.w,
rtile.h,
rtile.offset,
rtile.stride,
(int *)queue_index.device_pointer,
dim.global_size[0] * dim.global_size[1],
(char *)use_queues_flags.device_pointer,
(uint *)work_pool_wgs.device_pointer,
rtile.num_samples,
(float *)rtile.buffer);
}
}
return true;
}
SplitKernelFunction *CPUSplitKernel::get_split_kernel_function(const string &kernel_name,
const DeviceRequestedFeatures &)
{
CPUSplitKernelFunction *kernel = new CPUSplitKernelFunction(device);
kernel->func = device->split_kernels[kernel_name]();
if (!kernel->func) {
delete kernel;
return NULL;
}
return kernel;
}
int2 CPUSplitKernel::split_kernel_local_size()
{
return make_int2(1, 1);
}
int2 CPUSplitKernel::split_kernel_global_size(device_memory & /*kg*/,
device_memory & /*data*/,
DeviceTask * /*task*/)
{
return make_int2(1, 1);
}
uint64_t CPUSplitKernel::state_buffer_size(device_memory &kernel_globals,
device_memory & /*data*/,
size_t num_threads)
{
KernelGlobals *kg = (KernelGlobals *)kernel_globals.device_pointer;
return split_data_buffer_size(kg, num_threads);
}
Device *device_cpu_create(DeviceInfo &info, Stats &stats, Profiler &profiler, bool background)
{
return new CPUDevice(info, stats, profiler, background);
}
void device_cpu_info(vector<DeviceInfo> &devices)
{
DeviceInfo info;
info.type = DEVICE_CPU;
info.description = system_cpu_brand_string();
info.id = "CPU";
info.num = 0;
info.has_volume_decoupled = true;
info.has_adaptive_stop_per_sample = true;
info.has_osl = true;
info.has_half_images = true;
info.has_profiling = true;
devices.insert(devices.begin(), info);
}
string device_cpu_capabilities()
{
string capabilities = "";
capabilities += system_cpu_support_sse2() ? "SSE2 " : "";
capabilities += system_cpu_support_sse3() ? "SSE3 " : "";
capabilities += system_cpu_support_sse41() ? "SSE41 " : "";
capabilities += system_cpu_support_avx() ? "AVX " : "";
capabilities += system_cpu_support_avx2() ? "AVX2" : "";
if (capabilities[capabilities.size() - 1] == ' ')
capabilities.resize(capabilities.size() - 1);
return capabilities;
}
CCL_NAMESPACE_END