github
/
ColossalAI
mirror of https://github.com/hpcaitech/ColossalAI
1
0
Fork 0
Code Issues Projects Releases Wiki Activity

add implementatino for GetGPULaunchConfig1D

Browse Source
pull/5457/head
xs_courtesy 9 months ago
parent f366a5ea1f
commit 388e043930
7 changed files with 105 additions and 100 deletions
Show Stats Download Patch File Download Diff File

20
extensions/csrc/common/dev_info_mgr.h
Unescape View File

@ -1,20 +0,0 @@
#pragma once
#include <memory>
#include "common/nvgpu_dev_info.h"
#include "target.h"
namespace colossalAI {
namespace common {
template <typename Ret>
class DevInfoMgr final {
public:
static std::unique_ptr<Ret> GetDevInfo(int device_num) const {
return std::make_unique<Ret>(device_num);
}
};
} // namespace common
} // namespace colossalAI

2
extensions/csrc/common/target.h
Unescape View File

@ -105,7 +105,7 @@ class Target {
static Target DefaultAscendTarget();
static Target DefaultCUDATarget() {
return Target(OS::Linux, Arch::CUDA, BitLen::k64);
return Target(OS::Linux, Arch::NVGPU, BitLen::k64);
}
friend std::ostream& operator<<(std::ostream& os, const Target& target);

7
extensions/csrc/cuda/activation_kernel.cu
Unescape View File

@ -4,6 +4,7 @@
#include "../common/micros.h"
#include "../common/mp_type_traits.h"
#include "utils/gpu_launch_config.h"
template<typename T>
__device__ __forceinline__ T silu_kernel(const T& x) {
@ -51,8 +52,10 @@ torch::Tensor silu_and_mul(const torch::Tensor& ins)
int64_t numel = ((torch::numel(ins)) >> 1);
// TODO(LiuYang): Maybe we need to implement a function to get launch config
dim3 grid((numel+255)/256);
dim3 block(256);
colossalAI::cuda::utils::NVGPUDevInfo dev_info(0);
auto config = colossalAI::cuda::utils::GetGPULaunchConfig1D(dev_info,numel,1);
dim3 grid = config.grid;
dim3 block = config.block;
DISPATCH_FLOAT_HALF_AND_BFLOAT(
ins.scalar_type(),

76
extensions/csrc/cuda/utils/gpu_launch_config.h
Unescape View File

@ -3,32 +3,74 @@
#include <cuda.h>
#include <cuda_runtime.h>
#include "nvgpu_dev_info.h"
namespace colossalAI {
namespace cuda {
namespace utils {
GPULaunchConfig GPUGetGPULaunchConfig1D(int64_t numel, int vec_size);
struct GPULaunchConfig {
dim3 block{1, 1, 1};
dim3 grid{1, 1, 1};
};
static GPULaunchConfig GetGPULaunchConfig1D(const NVGPUDevInfo& dev_info,
int64_t numel, int64_t vec_size) {
const int64_t max_threads_per_block = dev_info.GetMaxThreadsPerBlock();
const int64_t max_blocks_per_grid = dev_info.GetMaxGridDims()[0];
const int64_t kMinimumSize = 64;
const int64_t kMaximumSize = 512;
int64_t active_threads = (numel + vec_size - 1) / vec_size;
int64_t sm_num = dev_info.GetMultiProcessorCount();
// Note(LiuYang): expected threads should be in [64, 128, 256, 512] generally
int64_t expected_threads_per_block = kMaximumSize;
// TODO(LiuYang): to be implemented
GPULaunchConfig GPUGetGPULaunchConfig2D(int64_t numel, int vec_size);
auto RoundUpToPowerOfTwo = [](int64_t x) {
bool is_power_of_two = false;
int64_t ret = 1;
int64_t y = x;
while (y > 0) {
is_power_of_two = ((ret ^ x) == 0);
y = (x >> 1);
ret = (ret << 1);
if (y > 0) is_power_of_two = false;
}
if (is_power_of_two) return x;
return ret;
};
// TODO(LiuYang): to be implemented
GPULaunchConfig GPUGetGPULaunchConfig3D(int64_t numel, int vec_size);
if ((active_threads / (sm_num << 1)) < max_threads_per_block) {
expected_threads_per_block =
RoundUpToPowerOfTwo(active_threads / (sm_num << 1));
} else if ((active_threads / (sm_num << 2)) < max_threads_per_block) {
expected_threads_per_block =
RoundUpToPowerOfTwo(active_threads / (sm_num << 2));
}
class GPULaunchConfig {
public:
GPULaunchConfig(){};
GPULaunchConfig(const dim3& block, const dim3& grid)
: block_(block), grid_(grid) {}
friend GPULaunchConfig GPUGetGPULaunchConfig1D(int64_t numel, int vec_size);
expected_threads_per_block =
std::max(expected_threads_per_block, kMinimumSize);
int64_t expect_block_per_grid =
((active_threads + expected_threads_per_block - 1) /
expected_threads_per_block);
protected:
void set_block(const dim3& dim) { block_ = dim; }
void set_grid(const dim3& dim) { grid_ = dim; }
if (expect_block_per_grid > max_blocks_per_grid) {
expect_block_per_grid = max_blocks_per_grid;
expected_threads_per_block =
(active_threads + expect_block_per_grid - 1) / expect_block_per_grid;
if (expected_threads_per_block > max_threads_per_block)
throw std::invalid_argument(
"Threads required for current input exceed for current GPU!");
expected_threads_per_block =
RoundUpToPowerOfTwo(expected_threads_per_block);
expect_block_per_grid = ((active_threads + expected_threads_per_block - 1) /
expected_threads_per_block);
}
private:
dim3 block_(1, 1, 1);
dim3 grid_(1, 1, 1);
GPULaunchConfig config;
config.block.x = expected_threads_per_block;
config.grid.x = expect_block_per_grid;
return config;
}
} // namespace utils

4
extensions/csrc/cuda/utils/micros.h
Unescape View File

@ -3,10 +3,12 @@
#include <cuda.h>
#include <cuda_runtime.h>
#include <exception>
#define CUDA_CHECK(func) \
{ \
auto status = func; \
if (status != cudaSuccess) { \
LOG(FATAL) << "CUDA Error : " << cudaGetErrorString(status); \
throw std::runtime_error(cudaGetErrorString(status)); \
} \
}

45
extensions/csrc/cuda/utils/nvgpu_dev_info.cc
Unescape View File

@ -1,45 +0,0 @@
#include "nvgpu_dev_info.h"
#include <array>
namespace colossalAI {
namespace cuda {
namespace utils {
std::array<int, 3> NVGPUDevInfo::GetMaxGridDims() const {
std::array<int, 3> ret;
ret[0] = prop_->maxGridSize[0];
ret[1] = prop_->maxGridSize[1];
ret[2] = prop_->maxGridSize[2];
return ret;
}
std::array<int, 3> NVGPUDevInfo::GetMaxBlockDims() const {
std::array<int, 3> ret;
ret[0] = prop_->maxThreadsDim[0];
ret[1] = prop_->maxThreadsDim[1];
ret[2] = prop_->maxThreadsDim[2];
return ret;
}
std::array<int, 2> NVGPUDevInfo::GetCapability() const {
std::array<int, 2> ret;
ret[0] = prop_.major;
ret[1] = prop_.minor;
}
int NVGPUDevInfo::GetMultiProcessorCount() const {
return prop_->multiProcessorCount;
}
int NVGPUDevInfo::GetMaxThreadsPerMultiProcessor() const {
return prop_->maxThreadsPerMultiProcessor;
}
int NVGPUDevInfo::GetMaxThreadsPerBlock() const {
return prop_->maxThreadsPerBlock;
}
} // namespace utils
} // namespace cuda
} // namespace colossalAI

41
extensions/csrc/cuda/utils/nvgpu_dev_info.h
Unescape View File

@ -8,7 +8,6 @@
#include <vector>
#include "micros.h"
#include "target.h"
namespace colossalAI {
namespace cuda {
@ -17,19 +16,43 @@ namespace utils {
class NVGPUDevInfo {
public:
explicit NVGPUDevInfo(int device_num) : device_num_(device_num) {
CUDA_CALL(cudaGetDeviceProperties(prop_, device));
CUDA_CHECK(cudaGetDeviceProperties(&prop_, device_num));
}
std::array<int, 3> GetMaxGridDims() const;
std::array<int, 3> GetMaxBlockDims() const;
std::array<int, 2> GetCapability() const;
int GetMultiProcessorCount() const;
int GetMaxThreadsPerMultiProcessor() const;
int GetMaxThreadsPerBlock() const;
std::array<int, 3> GetMaxGridDims() const {
std::array<int, 3> ret;
ret[0] = prop_.maxGridSize[0];
ret[1] = prop_.maxGridSize[1];
ret[2] = prop_.maxGridSize[2];
return ret;
}
std::array<int, 3> GetMaxBlockDims() const {
std::array<int, 3> ret;
ret[0] = prop_.maxThreadsDim[0];
ret[1] = prop_.maxThreadsDim[1];
ret[2] = prop_.maxThreadsDim[2];
return ret;
}
std::array<int, 2> GetCapability() const {
std::array<int, 2> ret;
ret[0] = prop_.major;
ret[1] = prop_.minor;
return ret;
}
int GetMultiProcessorCount() const { return prop_.multiProcessorCount; }
int GetMaxThreadsPerMultiProcessor() const {
return prop_.maxThreadsPerMultiProcessor;
}
int GetMaxThreadsPerBlock() const { return prop_.maxThreadsPerBlock; }
private:
int device_num_;
cudaDeviceProp* prop_;
cudaDeviceProp prop_;
};
} // namespace utils

Write Preview
Loading…
Cancel
Save