mmdeploy/csrc/device/cuda/linear_allocator.h
lvhan028 36124f6205
Merge sdk (#251)
* check in cmake

* move backend_ops to csrc/backend_ops

* check in preprocess, model, some codebase and their c-apis

* check in CMakeLists.txt

* check in parts of test_csrc

* commit everything else

* add readme

* update core's BUILD_INTERFACE directory

* skip codespell on third_party

* update trt_net and ort_net's CMakeLists

* ignore clion's build directory

* check in pybind11

* add onnx.proto. Remove MMDeploy's dependency on ncnn's source code

* export MMDeployTargets only when MMDEPLOY_BUILD_SDK is ON

* remove useless message

* target include directory is wrong

* change target name from mmdeploy_ppl_net to mmdeploy_pplnn_net

* skip install directory

* update project's cmake

* remove useless code

* set CMAKE_BUILD_TYPE to Release by force if it isn't set by user

* update custom ops CMakeLists

* pass object target's source lists

* fix lint end-of-file

* fix lint: trailing whitespace

* fix codespell hook

* remove bicubic_interpolate to csrc/backend_ops/

* set MMDEPLOY_BUILD_SDK OFF

* change custom ops build command

* add spdlog installation command

* update docs on how to checkout pybind11

* move bicubic_interpolate to backend_ops/tensorrt directory

* remove useless code

* correct cmake

* fix typo

* fix typo

* fix install directory

* correct sdk's readme

* set cub dir when cuda version < 11.0

* change directory where clang-format will apply to

* fix build command

* add .clang-format

* change clang-format style from google to file

* reformat csrc/backend_ops

* format sdk's code

* turn off clang-format for some files

* add -Xcompiler=-fno-gnu-unique

* fix trt topk initialize

* check in config for sdk demo

* update cmake script and csrc's readme

* correct config's path

* add cuda include directory, otherwise compile failed in case of tensorrt8.2

* clang-format onnx2ncnn.cpp

Co-authored-by: zhangli <lzhang329@gmail.com>
Co-authored-by: grimoire <yaoqian@sensetime.com>
2021-12-07 10:57:55 +08:00

70 lines
1.8 KiB
C++

// Copyright (c) OpenMMLab. All rights reserved.
#ifndef MMDEPLOY_SRC_DEVICE_CUDA_LINEARALLOCATOR_H_
#define MMDEPLOY_SRC_DEVICE_CUDA_LINEARALLOCATOR_H_
#include "default_allocator.h"
namespace mmdeploy::cuda {
class LinearAllocator {
public:
explicit LinearAllocator(std::size_t size) : size_(size) {
base_ = static_cast<uint8_t*>(gDefaultAllocator().Allocate(size));
ptr_ = base_;
}
~LinearAllocator() { gDefaultAllocator().Deallocate(base_, size_); }
[[nodiscard]] void* Allocate(std::size_t n) {
std::optional<std::lock_guard<std::mutex> > lock;
if (mutex_) {
lock.emplace(*mutex_);
}
++count_;
total_ += n;
auto ptr = static_cast<void*>(ptr_);
std::size_t space = base_ + size_ - ptr_;
if (std::align(16, n, ptr, space)) {
ERROR("success n={}, total={}, count={}", n, total_, count_);
ptr_ = static_cast<uint8_t*>(ptr) + n;
return ptr;
}
ERROR("fallback {}, total={}, count={}", n, total_, count_);
return gDefaultAllocator().Allocate(n);
}
void Deallocate(void* _p, std::size_t n) {
std::optional<std::lock_guard<std::mutex> > lock;
if (mutex_) {
lock.emplace(*mutex_);
}
auto p = static_cast<uint8_t*>(_p);
if (!(base_ <= p && p < ptr_)) {
gDefaultAllocator().Deallocate(_p, n);
}
total_ -= n;
--count_;
ERROR("deallocate total={}, count={}", total_, count_);
if (total_ == 0) {
assert(count_ == 0);
ptr_ = base_;
}
}
private:
std::size_t size_;
uint8_t* base_;
uint8_t* ptr_;
std::size_t total_{};
std::size_t count_{};
std::optional<std::mutex> mutex_;
};
inline LinearAllocator& gLinearAllocator() {
static LinearAllocator v(1U << 30);
return v;
}
} // namespace mmdeploy::cuda
#endif // MMDEPLOY_SRC_DEVICE_CUDA_LINEARALLOCATOR_H_