blender/intern/cycles/device/cuda/kernel.cpp
Brecht Van Lommel 5fc85d1cb7 Refactor: Cycles: Move MNEE walk into separate kernel
The new intersect_mnee kernel runs before shade_surface, and
shade_surface_mnee is eliminated. That large kernel was causing problems
for some GPU compilers.

MNEE state is packed into a shadow path state to avoid significantly
increasing the path state size. This shadow state is then either turned
into an actual shadow ray state or discarded in shade_surface.

MNEE was re-enabled on HIP RDNA2 as it works again now. Texture cache
misses now also work correctly with MNEE.

This adds some extra code to the regular shade_surface kernel even when
MNEE is not used, to use the MNEE sampled point instead of sampling a
light. But there seems to be no significant performance impact.

Co-authored-by: Sergey Sharybin <sergey@blender.org>
Pull Request: https://projects.blender.org/blender/blender/pulls/158698
2026-05-27 20:34:06 +02:00

56 lines
1.4 KiB
C++

/* SPDX-FileCopyrightText: 2011-2022 Blender Foundation
*
* SPDX-License-Identifier: Apache-2.0 */
#ifdef WITH_CUDA
# include "device/cuda/kernel.h"
# include "device/cuda/device_impl.h"
CCL_NAMESPACE_BEGIN
void CUDADeviceKernels::load(CUDADevice *device)
{
CUmodule cuModule = device->cuModule;
for (int i = 0; i < (int)DEVICE_KERNEL_NUM; i++) {
CUDADeviceKernel &kernel = kernels_[i];
if (!device_kernel_has_gpu_function((DeviceKernel)i)) {
continue;
}
const std::string function_name = std::string("kernel_gpu_") +
device_kernel_as_string((DeviceKernel)i);
cuda_device_assert(device,
cuModuleGetFunction(&kernel.function, cuModule, function_name.c_str()));
if (kernel.function) {
cuda_device_assert(device, cuFuncSetCacheConfig(kernel.function, CU_FUNC_CACHE_PREFER_L1));
cuda_device_assert(
device,
cuOccupancyMaxPotentialBlockSize(
&kernel.min_blocks, &kernel.num_threads_per_block, kernel.function, nullptr, 0, 0));
}
else {
LOG_ERROR << "Unable to load kernel " << function_name;
}
}
loaded = true;
}
const CUDADeviceKernel &CUDADeviceKernels::get(DeviceKernel kernel) const
{
return kernels_[(int)kernel];
}
bool CUDADeviceKernels::available(DeviceKernel kernel) const
{
return kernels_[(int)kernel].function != nullptr;
}
CCL_NAMESPACE_END
#endif /* WITH_CUDA */