Cycles: merge of cycles-x branch, a major update to the renderer

This includes much improved GPU rendering performance, viewport interactivity,
new shadow catcher, revamped sampling settings, subsurface scattering anisotropy,
new GPU volume sampling, improved PMJ sampling pattern, and more.

Some features have also been removed or changed, breaking backwards compatibility.
Including the removal of the OpenCL backend, for which alternatives are under
development.

Release notes and code docs:
https://wiki.blender.org/wiki/Reference/Release_Notes/3.0/Cycles
https://wiki.blender.org/wiki/Source/Render/Cycles

Credits:
* Sergey Sharybin
* Brecht Van Lommel
* Patrick Mours (OptiX backend)
* Christophe Hery (subsurface scattering anisotropy)
* William Leeson (PMJ sampling pattern)
* Alaska (various fixes and tweaks)
* Thomas Dinges (various fixes)

For the full commit history, see the cycles-x branch. This squashes together
all the changes since intermediate changes would often fail building or tests.

Ref T87839, T87837, T87836
Fixes T90734, T89353, T80267, T80267, T77185, T69800

1 files changed, 220 insertions, 0 deletions

diff --git a/intern/cycles/device/cuda/queue.cpp b/intern/cycles/device/cuda/queue.cpp
new file mode 100644
index 00000000000..b7f86c10553
--- /dev/null
+++ b/intern/cycles/device/cuda/queue.cpp
@@ -0,0 +1,220 @@
+/*
+ * 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/queue.h"
+
+#  include "device/cuda/device_impl.h"
+#  include "device/cuda/graphics_interop.h"
+#  include "device/cuda/kernel.h"
+
+CCL_NAMESPACE_BEGIN
+
+/* CUDADeviceQueue */
+
+CUDADeviceQueue::CUDADeviceQueue(CUDADevice *device)
+    : DeviceQueue(device), cuda_device_(device), cuda_stream_(nullptr)
+{
+  const CUDAContextScope scope(cuda_device_);
+  cuda_device_assert(cuda_device_, cuStreamCreate(&cuda_stream_, CU_STREAM_NON_BLOCKING));
+}
+
+CUDADeviceQueue::~CUDADeviceQueue()
+{
+  const CUDAContextScope scope(cuda_device_);
+  cuStreamDestroy(cuda_stream_);
+}
+
+int CUDADeviceQueue::num_concurrent_states(const size_t state_size) const
+{
+  int num_states = max(cuda_device_->get_num_multiprocessors() *
+                           cuda_device_->get_max_num_threads_per_multiprocessor() * 16,
+                       1048576);
+
+  const char *factor_str = getenv("CYCLES_CONCURRENT_STATES_FACTOR");
+  if (factor_str) {
+    num_states = max((int)(num_states * atof(factor_str)), 1024);
+  }
+
+  VLOG(3) << "GPU queue concurrent states: " << num_states << ", using up to "
+          << string_human_readable_size(num_states * state_size);
+
+  return num_states;
+}
+
+int CUDADeviceQueue::num_concurrent_busy_states() const
+{
+  const int max_num_threads = cuda_device_->get_num_multiprocessors() *
+                              cuda_device_->get_max_num_threads_per_multiprocessor();
+
+  if (max_num_threads == 0) {
+    return 65536;
+  }
+
+  return 4 * max_num_threads;
+}
+
+void CUDADeviceQueue::init_execution()
+{
+  /* Synchronize all textures and memory copies before executing task. */
+  CUDAContextScope scope(cuda_device_);
+  cuda_device_->load_texture_info();
+  cuda_device_assert(cuda_device_, cuCtxSynchronize());
+
+  debug_init_execution();
+}
+
+bool CUDADeviceQueue::kernel_available(DeviceKernel kernel) const
+{
+  return cuda_device_->kernels.available(kernel);
+}
+
+bool CUDADeviceQueue::enqueue(DeviceKernel kernel, const int work_size, void *args[])
+{
+  if (cuda_device_->have_error()) {
+    return false;
+  }
+
+  debug_enqueue(kernel, work_size);
+
+  const CUDAContextScope scope(cuda_device_);
+  const CUDADeviceKernel &cuda_kernel = cuda_device_->kernels.get(kernel);
+
+  /* Compute kernel launch parameters. */
+  const int num_threads_per_block = cuda_kernel.num_threads_per_block;
+  const int num_blocks = divide_up(work_size, num_threads_per_block);
+
+  int shared_mem_bytes = 0;
+
+  switch (kernel) {
+    case DEVICE_KERNEL_INTEGRATOR_QUEUED_PATHS_ARRAY:
+    case DEVICE_KERNEL_INTEGRATOR_QUEUED_SHADOW_PATHS_ARRAY:
+    case DEVICE_KERNEL_INTEGRATOR_ACTIVE_PATHS_ARRAY:
+    case DEVICE_KERNEL_INTEGRATOR_TERMINATED_PATHS_ARRAY:
+    case DEVICE_KERNEL_INTEGRATOR_SORTED_PATHS_ARRAY:
+    case DEVICE_KERNEL_INTEGRATOR_COMPACT_PATHS_ARRAY:
+      /* See parall_active_index.h for why this amount of shared memory is needed. */
+      shared_mem_bytes = (num_threads_per_block + 1) * sizeof(int);
+      break;
+
+    default:
+      break;
+  }
+
+  /* Launch kernel. */
+  cuda_device_assert(cuda_device_,
+                     cuLaunchKernel(cuda_kernel.function,
+                                    num_blocks,
+                                    1,
+                                    1,
+                                    num_threads_per_block,
+                                    1,
+                                    1,
+                                    shared_mem_bytes,
+                                    cuda_stream_,
+                                    args,
+                                    0));
+
+  return !(cuda_device_->have_error());
+}
+
+bool CUDADeviceQueue::synchronize()
+{
+  if (cuda_device_->have_error()) {
+    return false;
+  }
+
+  const CUDAContextScope scope(cuda_device_);
+  cuda_device_assert(cuda_device_, cuStreamSynchronize(cuda_stream_));
+  debug_synchronize();
+
+  return !(cuda_device_->have_error());
+}
+
+void CUDADeviceQueue::zero_to_device(device_memory &mem)
+{
+  assert(mem.type != MEM_GLOBAL && mem.type != MEM_TEXTURE);
+
+  if (mem.memory_size() == 0) {
+    return;
+  }
+
+  /* Allocate on demand. */
+  if (mem.device_pointer == 0) {
+    cuda_device_->mem_alloc(mem);
+  }
+
+  /* Zero memory on device. */
+  assert(mem.device_pointer != 0);
+
+  const CUDAContextScope scope(cuda_device_);
+  cuda_device_assert(
+      cuda_device_,
+      cuMemsetD8Async((CUdeviceptr)mem.device_pointer, 0, mem.memory_size(), cuda_stream_));
+}
+
+void CUDADeviceQueue::copy_to_device(device_memory &mem)
+{
+  assert(mem.type != MEM_GLOBAL && mem.type != MEM_TEXTURE);
+
+  if (mem.memory_size() == 0) {
+    return;
+  }
+
+  /* Allocate on demand. */
+  if (mem.device_pointer == 0) {
+    cuda_device_->mem_alloc(mem);
+  }
+
+  assert(mem.device_pointer != 0);
+  assert(mem.host_pointer != nullptr);
+
+  /* Copy memory to device. */
+  const CUDAContextScope scope(cuda_device_);
+  cuda_device_assert(
+      cuda_device_,
+      cuMemcpyHtoDAsync(
+          (CUdeviceptr)mem.device_pointer, mem.host_pointer, mem.memory_size(), cuda_stream_));
+}
+
+void CUDADeviceQueue::copy_from_device(device_memory &mem)
+{
+  assert(mem.type != MEM_GLOBAL && mem.type != MEM_TEXTURE);
+
+  if (mem.memory_size() == 0) {
+    return;
+  }
+
+  assert(mem.device_pointer != 0);
+  assert(mem.host_pointer != nullptr);
+
+  /* Copy memory from device. */
+  const CUDAContextScope scope(cuda_device_);
+  cuda_device_assert(
+      cuda_device_,
+      cuMemcpyDtoHAsync(
+          mem.host_pointer, (CUdeviceptr)mem.device_pointer, mem.memory_size(), cuda_stream_));
+}
+
+unique_ptr<DeviceGraphicsInterop> CUDADeviceQueue::graphics_interop_create()
+{
+  return make_unique<CUDADeviceGraphicsInterop>(this);
+}
+
+CCL_NAMESPACE_END
+
+#endif /* WITH_CUDA */