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// Copyright 2019-2023, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// * Redistributions of source code must retain the above copyright
// notice, this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright
// notice, this list of conditions and the following disclaimer in the
// documentation and/or other materials provided with the distribution.
// * Neither the name of NVIDIA CORPORATION nor the names of its
// contributors may be used to endorse or promote products derived
// from this software without specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
// PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
// CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
// EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
// PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
// OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
// OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#pragma once
#ifndef _WIN32
#include <dlfcn.h>
#endif
#include <set>
#include "status.h"
#include "triton/common/sync_queue.h"
#ifdef TRITON_ENABLE_GPU
#include <cuda.h>
#include <cuda_runtime_api.h>
#endif // TRITON_ENABLE_GPU
namespace triton { namespace core {
#ifdef TRITON_ENABLE_GPU
#define RETURN_IF_CUDA_ERR(X, MSG) \
do { \
cudaError_t err__ = (X); \
if (err__ != cudaSuccess) { \
return Status( \
Status::Code::INTERNAL, (MSG) + ": " + cudaGetErrorString(err__)); \
} \
} while (false)
#define RETURN_IF_CUDA_DRIVER_ERR(X, MSG) \
do { \
CUresult cuda_err__ = (X); \
if (cuda_err__ != CUDA_SUCCESS) { \
const char* error_string__; \
CudaDriverHelper::GetInstance().CuGetErrorString( \
&error_string__, cuda_err__); \
return Status(Status::Code::INTERNAL, (MSG) + ": " + error_string__); \
} \
} while (false)
#endif // TRITON_ENABLE_GPU
#ifndef TRITON_ENABLE_GPU
using cudaStream_t = void*;
#endif // !TRITON_ENABLE_GPU
/// Get the memory info for the specified device.
/// \param device_id The device ID.
/// \param free Return free memory in bytes.
/// \param total Return total memory in bytes.
/// \return The error status. A non-OK status means failure to get memory info.
Status GetDeviceMemoryInfo(const int device_id, size_t* free, size_t* total);
/// Enable peer access for all GPU device pairs
/// \param min_compute_capability The minimum support CUDA compute
/// capability.
/// \return The error status. A non-OK status means not all pairs are enabled
Status EnablePeerAccess(const double min_compute_capability);
/// Copy buffer from 'src' to 'dst' for given 'byte_size'. The buffer location
/// is identified by the memory type and id, and the corresponding copy will be
/// initiated.
/// \param msg The message to be prepended in error message.
/// \param src_memory_type The memory type CPU/GPU of the source.
/// \param src_memory_type_id The device id of the source.
/// \param dst_memory_type The memory type CPU/GPU of the destination.
/// \param dst_memory_type_id The device id of the destination.
/// \param byte_size The size in bytes to me copied from source to destination.
/// \param src The buffer start address of the source.
/// \param dst The buffer start address of the destination.
/// \param cuda_stream The stream to be associated with, and 0 can be
/// passed for default stream.
/// \param cuda_used returns whether a CUDA memory copy is initiated. If true,
/// the caller should synchronize on the given 'cuda_stream' to ensure data copy
/// is completed.
/// \param copy_on_stream whether the memory copies should be performed in cuda
/// host functions on the 'cuda_stream'.
/// \return The error status. A non-ok status indicates failure to copy the
/// buffer.
Status CopyBuffer(
const std::string& msg, const TRITONSERVER_MemoryType src_memory_type,
const int64_t src_memory_type_id,
const TRITONSERVER_MemoryType dst_memory_type,
const int64_t dst_memory_type_id, const size_t byte_size, const void* src,
void* dst, cudaStream_t cuda_stream, bool* cuda_used,
bool copy_on_stream = false);
#ifdef TRITON_ENABLE_GPU
/// Validates the compute capability of the GPU indexed
/// \param gpu_id The index of the target GPU.
/// \param min_compute_capability The minimum support CUDA compute
/// capability.
/// \return The error status. A non-OK status means the target GPU is
/// not supported.
Status CheckGPUCompatibility(
const int gpu_id, const double min_compute_capability);
/// Obtains a set of gpu ids that is supported by triton.
/// \param supported_gpus Returns the set of integers which is
/// populated by ids of supported GPUS
/// \param min_compute_capability The minimum support CUDA compute
/// capability.
/// \return The error status. A non-ok status means there were
/// errors encountered while querying GPU devices.
Status GetSupportedGPUs(
std::set<int>* supported_gpus, const double min_compute_capability);
/// Checks if the GPU specified is an integrated GPU and supports Zero-copy.
/// \param gpu_id The index of the target GPU.
/// \param zero_copy_support If true, Zero-copy is supported by this GPU.
/// \return The error status. A non-OK status means the target GPU is
/// not supported.
Status SupportsIntegratedZeroCopy(const int gpu_id, bool* zero_copy_support);
/// Set the CUDA context to the specified device ID
/// It will rollback to the previous device upon destruction.
class ScopedSetDevice {
public:
ScopedSetDevice(int device)
{
overriden_ = false;
prev_device_ = device;
cudaGetDevice(&prev_device_);
if (prev_device_ != device) {
overriden_ = true;
cudaSetDevice(device);
}
}
~ScopedSetDevice()
{
if (overriden_) {
cudaSetDevice(prev_device_);
}
}
private:
int prev_device_;
bool overriden_;
};
#endif
// Helper around CopyBuffer that updates the completion queue with the returned
// status and cuda_used flag.
void CopyBufferHandler(
const std::string& msg, const TRITONSERVER_MemoryType src_memory_type,
const int64_t src_memory_type_id,
const TRITONSERVER_MemoryType dst_memory_type,
const int64_t dst_memory_type_id, const size_t byte_size, const void* src,
void* dst, cudaStream_t cuda_stream, void* response_ptr,
triton::common::SyncQueue<std::tuple<Status, bool, void*>>*
completion_queue);
struct CopyParams {
CopyParams(void* dst, const void* src, const size_t byte_size)
: dst_(dst), src_(src), byte_size_(byte_size)
{
}
void* dst_;
const void* src_;
const size_t byte_size_;
};
#ifdef TRITON_ENABLE_GPU
/// A singleton for Cuda Driver APIs. In order to continue supporting Triton
/// deployments when GPUs are not available we need to use CUDA driver APIs
/// through dlopen
class CudaDriverHelper {
public:
static CudaDriverHelper& GetInstance()
{
static CudaDriverHelper instance;
return instance;
}
private:
void* dl_open_handle_ = nullptr;
std::string error_str_;
CUresult (*cu_mem_create_fn_)(
CUmemGenericAllocationHandle*, size_t, CUmemAllocationProp*,
unsigned long long) = nullptr;
CUresult (*cu_mem_map_fn_)(
CUdeviceptr ptr, size_t size, size_t offset,
CUmemGenericAllocationHandle handle, unsigned long long flags) = nullptr;
CUresult (*cu_mem_set_access_fn_)(
CUdeviceptr, size_t, const CUmemAccessDesc*, size_t) = nullptr;
CUresult (*cu_get_error_string_fn_)(CUresult, const char**) = nullptr;
CUresult (*cu_mem_get_allocation_granularity_fn_)(
size_t*, const CUmemAllocationProp*,
CUmemAllocationGranularity_flags) = nullptr;
CUresult (*cu_mem_release_fn_)(CUmemGenericAllocationHandle) = nullptr;
CUresult (*cu_init_fn_)(unsigned int) = nullptr;
CUresult (*cu_mem_address_reserve_fn_)(
CUdeviceptr* ptr, size_t size, size_t alignment, CUdeviceptr addr,
unsigned long long flags) = nullptr;
CUresult (*cu_mem_unmap_fn_)(CUdeviceptr ptr, size_t size) = nullptr;
CUresult (*cu_mem_address_free_fn_)(CUdeviceptr ptr, size_t size) = nullptr;
CudaDriverHelper();
~CudaDriverHelper();
public:
CudaDriverHelper(CudaDriverHelper const&) = delete;
void operator=(CudaDriverHelper const&) = delete;
bool IsAvailable();
const std::string& GetErrorString() const { return error_str_; }
void ClearErrorString() { return error_str_.clear(); }
Status CuMemGetAllocationGranularity(
size_t* aligned_size, const CUmemAllocationProp* prop,
CUmemAllocationGranularity_flags flags);
Status CuMemCreate(
CUmemGenericAllocationHandle* block, size_t byte_size,
CUmemAllocationProp* prop, unsigned long long flags);
Status CuMemSetAccess(
CUdeviceptr ptr, size_t size, const CUmemAccessDesc* desc, size_t count);
Status CuMemMap(
CUdeviceptr ptr, size_t size, size_t offset,
CUmemGenericAllocationHandle handle, unsigned long long flags);
Status CuMemRelease(CUmemGenericAllocationHandle handle);
Status CuMemAddressFree(CUdeviceptr ptr, size_t size);
Status CuMemUnmap(CUdeviceptr ptr, size_t size);
Status CuMemAddressReserve(
CUdeviceptr* ptr, size_t size, size_t alignment, CUdeviceptr addr,
unsigned long long flags);
void CuGetErrorString(const char** error_string, CUresult error);
};
/// Get the minimum allocation granularity.
/// \param aligned_size Returns minimum allocation granularity.
/// \return The error status. A non-OK status means there were some errors
/// when querying the allocation granularity.
Status GetAllocationGranularity(size_t& aligned_sz);
#endif
}} // namespace triton::core