58 lines
1.5 KiB
C++
58 lines
1.5 KiB
C++
/* SPDX-FileCopyrightText: 2011-2022 Blender Foundation
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*
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* SPDX-License-Identifier: Apache-2.0 */
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#ifdef WITH_CUDA
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# include "device/cuda/kernel.h"
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# include "device/cuda/device_impl.h"
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CCL_NAMESPACE_BEGIN
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void CUDADeviceKernels::load(CUDADevice *device)
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{
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CUmodule cuModule = device->cuModule;
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for (int i = 0; i < (int)DEVICE_KERNEL_NUM; i++) {
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CUDADeviceKernel &kernel = kernels_[i];
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/* No mega-kernel used for GPU. */
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if (i == DEVICE_KERNEL_INTEGRATOR_MEGAKERNEL) {
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continue;
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}
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const std::string function_name = std::string("kernel_gpu_") +
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device_kernel_as_string((DeviceKernel)i);
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cuda_device_assert(device,
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cuModuleGetFunction(&kernel.function, cuModule, function_name.c_str()));
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if (kernel.function) {
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cuda_device_assert(device, cuFuncSetCacheConfig(kernel.function, CU_FUNC_CACHE_PREFER_L1));
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cuda_device_assert(
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device,
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cuOccupancyMaxPotentialBlockSize(
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&kernel.min_blocks, &kernel.num_threads_per_block, kernel.function, NULL, 0, 0));
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}
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else {
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LOG(ERROR) << "Unable to load kernel " << function_name;
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}
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}
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loaded = true;
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}
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const CUDADeviceKernel &CUDADeviceKernels::get(DeviceKernel kernel) const
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{
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return kernels_[(int)kernel];
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}
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bool CUDADeviceKernels::available(DeviceKernel kernel) const
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{
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return kernels_[(int)kernel].function != nullptr;
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}
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CCL_NAMESPACE_END
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#endif /* WITH_CUDA */
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