/* * 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" /* 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_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(uint4 *input, float4 *output, int type, int filter, int sx, int sw, int offset, int sample) { int x = sx + blockDim.x*blockIdx.x + threadIdx.x; if(x < sx + sw) { KernelGlobals kg; kernel_bake_evaluate(&kg, input, output, (ShaderEvalType)type, filter, x, offset, sample); } } #endif #endif