cuda/queue.cpp

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/* SPDX-FileCopyrightText: 2011-2022 Blender Foundation
 *
 * SPDX-License-Identifier: Apache-2.0 */
 
#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
{
  const int max_num_threads = cuda_device_->get_num_multiprocessors() *
                              cuda_device_->get_max_num_threads_per_multiprocessor();
  int num_states = max(max_num_threads, 65536) * 16;
 
  const char *factor_str = getenv("CYCLES_CONCURRENT_STATES_FACTOR");
  if (factor_str) {
    const float factor = (float)atof(factor_str);
    if (factor != 0.0f) {
      num_states = max((int)(num_states * factor), 1024);
    }
    else {
      VLOG_DEVICE_STATS << "CYCLES_CONCURRENT_STATES_FACTOR evaluated to 0";
    }
  }
 
  VLOG_DEVICE_STATS << "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 size_t /*state_size*/) 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::enqueue(DeviceKernel kernel,
                              const int work_size,
                              DeviceKernelArguments const &args)
{
  if (cuda_device_->have_error()) {
    return false;
  }
 
  debug_enqueue_begin(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:
    case DEVICE_KERNEL_INTEGRATOR_TERMINATED_SHADOW_PATHS_ARRAY:
    case DEVICE_KERNEL_INTEGRATOR_COMPACT_SHADOW_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. */
  assert_success(cuLaunchKernel(cuda_kernel.function,
                                num_blocks,
                                1,
                                1,
                                num_threads_per_block,
                                1,
                                1,
                                shared_mem_bytes,
                                cuda_stream_,
                                const_cast<void **>(args.values),
                                0),
                 "enqueue");
 
  debug_enqueue_end();
 
  return !(cuda_device_->have_error());
}
 
bool CUDADeviceQueue::synchronize()
{
  if (cuda_device_->have_error()) {
    return false;
  }
 
  const CUDAContextScope scope(cuda_device_);
  assert_success(cuStreamSynchronize(cuda_stream_), "synchronize");
 
  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_);
  assert_success(
      cuMemsetD8Async((CUdeviceptr)mem.device_pointer, 0, mem.memory_size(), cuda_stream_),
      "zero_to_device");
}
 
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_);
  assert_success(
      cuMemcpyHtoDAsync(
          (CUdeviceptr)mem.device_pointer, mem.host_pointer, mem.memory_size(), cuda_stream_),
      "copy_to_device");
}
 
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_);
  assert_success(
      cuMemcpyDtoHAsync(
          mem.host_pointer, (CUdeviceptr)mem.device_pointer, mem.memory_size(), cuda_stream_),
      "copy_from_device");
}
 
void CUDADeviceQueue::assert_success(CUresult result, const char *operation)
{
  if (result != CUDA_SUCCESS) {
    const char *name = cuewErrorString(result);
    cuda_device_->set_error(string_printf(
        "%s in CUDA queue %s (%s)", name, operation, debug_active_kernels().c_str()));
  }
}
 
unique_ptr<DeviceGraphicsInterop> CUDADeviceQueue::graphics_interop_create()
{
  return make_unique<CUDADeviceGraphicsInterop>(this);
}
 
CCL_NAMESPACE_END
 
#endif /* WITH_CUDA */