Cycles: add Optix device backend
This uses hardware-accelerated raytracing on NVIDIA RTX graphics cards. It is still currently experimental. Most features are supported, but a few are still missing like baking, branched path tracing and using CPU memory. https://wiki.blender.org/wiki/Reference/Release_Notes/2.81/Cycles#NVIDIA_RTX For building with Optix support, the Optix SDK must be installed. See here for build instructions: https://wiki.blender.org/wiki/Building_Blender/CUDA Differential Revision: https://developer.blender.org/D5363
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@@ -81,6 +81,8 @@ bool debug_flags_sync_from_scene(BL::Scene b_scene)
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/* Synchronize CUDA flags. */
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flags.cuda.adaptive_compile = get_boolean(cscene, "debug_use_cuda_adaptive_compile");
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flags.cuda.split_kernel = get_boolean(cscene, "debug_use_cuda_split_kernel");
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/* Synchronize OptiX flags. */
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flags.optix.cuda_streams = get_int(cscene, "debug_optix_cuda_streams");
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/* Synchronize OpenCL device type. */
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switch (get_enum(cscene, "debug_opencl_device_type")) {
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case 0:
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@@ -960,14 +962,16 @@ static PyObject *enable_print_stats_func(PyObject * /*self*/, PyObject * /*args*
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static PyObject *get_device_types_func(PyObject * /*self*/, PyObject * /*args*/)
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{
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vector<DeviceType> device_types = Device::available_types();
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bool has_cuda = false, has_opencl = false;
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bool has_cuda = false, has_optix = false, has_opencl = false;
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foreach (DeviceType device_type, device_types) {
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has_cuda |= (device_type == DEVICE_CUDA);
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has_optix |= (device_type == DEVICE_OPTIX);
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has_opencl |= (device_type == DEVICE_OPENCL);
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}
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PyObject *list = PyTuple_New(2);
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PyObject *list = PyTuple_New(3);
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PyTuple_SET_ITEM(list, 0, PyBool_FromLong(has_cuda));
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PyTuple_SET_ITEM(list, 1, PyBool_FromLong(has_opencl));
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PyTuple_SET_ITEM(list, 1, PyBool_FromLong(has_optix));
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PyTuple_SET_ITEM(list, 2, PyBool_FromLong(has_opencl));
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return list;
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}
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