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/*
* 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.
*/
#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];
/* No megakernel used for GPU. */
if (i == DEVICE_KERNEL_INTEGRATOR_MEGAKERNEL) {
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, NULL, 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*/
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