forked from bartvdbraak/blender
Cycles: Change device-only memory to actually only allocate on the device
This patch changes the `MEM_DEVICE_ONLY` type to only allocate on the device and fail if that is not possible anymore because out-of-memory (since OptiX acceleration structures may not be allocated in host memory). It also fixes high peak memory usage during OptiX acceleration structure building. Reviewed By: brecht Maniphest Tasks: T85985 Differential Revision: https://developer.blender.org/D10535
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@ -27,8 +27,8 @@ BVHOptiX::BVHOptiX(const BVHParams ¶ms_,
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Device *device)
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: BVH(params_, geometry_, objects_),
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traversable_handle(0),
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as_data(device, params_.top_level ? "optix tlas" : "optix blas"),
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motion_transform_data(device, "optix motion transform")
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as_data(device, params_.top_level ? "optix tlas" : "optix blas", false),
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motion_transform_data(device, "optix motion transform", false)
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{
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}
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@ -854,7 +854,7 @@ CUDADevice::CUDAMem *CUDADevice::generic_alloc(device_memory &mem, size_t pitch_
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void *shared_pointer = 0;
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if (mem_alloc_result != CUDA_SUCCESS && can_map_host) {
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if (mem_alloc_result != CUDA_SUCCESS && can_map_host && mem.type != MEM_DEVICE_ONLY) {
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if (mem.shared_pointer) {
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/* Another device already allocated host memory. */
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mem_alloc_result = CUDA_SUCCESS;
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@ -877,8 +877,14 @@ CUDADevice::CUDAMem *CUDADevice::generic_alloc(device_memory &mem, size_t pitch_
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}
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if (mem_alloc_result != CUDA_SUCCESS) {
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status = " failed, out of device and host memory";
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set_error("System is out of GPU and shared host memory");
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if (mem.type == MEM_DEVICE_ONLY) {
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status = " failed, out of device memory";
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set_error("System is out of GPU memory");
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}
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else {
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status = " failed, out of device and host memory";
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set_error("System is out of GPU and shared host memory");
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}
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}
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if (mem.name) {
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@ -396,8 +396,7 @@ class CPUDevice : public Device {
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<< string_human_readable_size(mem.memory_size()) << ")";
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}
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if (mem.type == MEM_DEVICE_ONLY) {
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assert(!mem.host_pointer);
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if (mem.type == MEM_DEVICE_ONLY || !mem.host_pointer) {
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size_t alignment = MIN_ALIGNMENT_CPU_DATA_TYPES;
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void *data = util_aligned_malloc(mem.memory_size(), alignment);
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mem.device_pointer = (device_ptr)data;
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@ -459,7 +458,7 @@ class CPUDevice : public Device {
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tex_free((device_texture &)mem);
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}
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else if (mem.device_pointer) {
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if (mem.type == MEM_DEVICE_ONLY) {
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if (mem.type == MEM_DEVICE_ONLY || !mem.host_pointer) {
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util_aligned_free((void *)mem.device_pointer);
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}
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mem.device_pointer = 0;
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@ -171,7 +171,8 @@ class DenoisingTask {
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bool gpu_temporary_mem;
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DenoiseBuffers(Device *device)
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: mem(device, "denoising pixel buffer"), temporary_mem(device, "denoising temporary mem")
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: mem(device, "denoising pixel buffer"),
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temporary_mem(device, "denoising temporary mem", true)
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{
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}
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} buffer;
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@ -270,8 +270,8 @@ class device_memory {
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template<typename T> class device_only_memory : public device_memory {
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public:
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device_only_memory(Device *device, const char *name)
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: device_memory(device, name, MEM_DEVICE_ONLY)
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device_only_memory(Device *device, const char *name, bool allow_host_memory_fallback = false)
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: device_memory(device, name, allow_host_memory_fallback ? MEM_READ_WRITE : MEM_DEVICE_ONLY)
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{
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data_type = device_type_traits<T>::data_type;
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data_elements = max(device_type_traits<T>::num_elements, 1);
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@ -197,8 +197,8 @@ class OptiXDevice : public CUDADevice {
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OptiXDevice(DeviceInfo &info_, Stats &stats_, Profiler &profiler_, bool background_)
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: CUDADevice(info_, stats_, profiler_, background_),
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sbt_data(this, "__sbt", MEM_READ_ONLY),
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launch_params(this, "__params"),
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denoiser_state(this, "__denoiser_state")
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launch_params(this, "__params", false),
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denoiser_state(this, "__denoiser_state", true)
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{
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// Store number of CUDA streams in device info
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info.cpu_threads = DebugFlags().optix.cuda_streams;
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@ -878,8 +878,8 @@ class OptiXDevice : public CUDADevice {
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device_ptr input_ptr = rtile.buffer + pixel_offset;
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// Copy tile data into a common buffer if necessary
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device_only_memory<float> input(this, "denoiser input");
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device_vector<TileInfo> tile_info_mem(this, "denoiser tile info", MEM_READ_WRITE);
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device_only_memory<float> input(this, "denoiser input", true);
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device_vector<TileInfo> tile_info_mem(this, "denoiser tile info", MEM_READ_ONLY);
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bool contiguous_memory = true;
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for (int i = 0; i < RenderTileNeighbors::SIZE; i++) {
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@ -924,7 +924,7 @@ class OptiXDevice : public CUDADevice {
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}
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# if OPTIX_DENOISER_NO_PIXEL_STRIDE
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device_only_memory<float> input_rgb(this, "denoiser input rgb");
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device_only_memory<float> input_rgb(this, "denoiser input rgb", true);
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input_rgb.alloc_to_device(rect_size.x * rect_size.y * 3 * task.denoising.input_passes);
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void *input_args[] = {&input_rgb.device_pointer,
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@ -1146,6 +1146,13 @@ class OptiXDevice : public CUDADevice {
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const OptixBuildInput &build_input,
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uint16_t num_motion_steps)
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{
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/* Allocate and build acceleration structures only one at a time, to prevent parallel builds
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* from running out of memory (since both original and compacted acceleration structure memory
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* may be allocated at the same time for the duration of this function). The builds would
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* otherwise happen on the same CUDA stream anyway. */
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static thread_mutex mutex;
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thread_scoped_lock lock(mutex);
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const CUDAContextScope scope(cuContext);
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// Compute memory usage
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@ -1170,11 +1177,12 @@ class OptiXDevice : public CUDADevice {
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optixAccelComputeMemoryUsage(context, &options, &build_input, 1, &sizes));
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// Allocate required output buffers
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device_only_memory<char> temp_mem(this, "optix temp as build mem");
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device_only_memory<char> temp_mem(this, "optix temp as build mem", true);
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temp_mem.alloc_to_device(align_up(sizes.tempSizeInBytes, 8) + 8);
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if (!temp_mem.device_pointer)
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return false; // Make sure temporary memory allocation succeeded
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// Acceleration structure memory has to be allocated on the device (not allowed to be on host)
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device_only_memory<char> &out_data = bvh->as_data;
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if (operation == OPTIX_BUILD_OPERATION_BUILD) {
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assert(out_data.device == this);
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@ -1222,7 +1230,7 @@ class OptiXDevice : public CUDADevice {
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// There is no point compacting if the size does not change
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if (compacted_size < sizes.outputSizeInBytes) {
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device_only_memory<char> compacted_data(this, "optix compacted as");
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device_only_memory<char> compacted_data(this, "optix compacted as", false);
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compacted_data.alloc_to_device(compacted_size);
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if (!compacted_data.device_pointer)
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// Do not compact if memory allocation for compacted acceleration structure fails
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@ -1242,6 +1250,7 @@ class OptiXDevice : public CUDADevice {
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std::swap(out_data.device_size, compacted_data.device_size);
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std::swap(out_data.device_pointer, compacted_data.device_pointer);
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// Original acceleration structure memory is freed when 'compacted_data' goes out of scope
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}
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}
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