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/* SPDX-License-Identifier: Apache-2.0
* Copyright 2011-2022 Blender Foundation */
#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
{
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 */
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