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[CUDA] Initial work for boosting and evaluation with CUDA #5279

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Jul 29, 2022
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2 changes: 2 additions & 0 deletions CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -395,6 +395,8 @@ if(USE_CUDA OR USE_CUDA_EXP)
src/treelearner/*.cu
endif()
if(USE_CUDA_EXP)
src/boosting/cuda/*.cpp
src/boosting/cuda/*.cu
src/treelearner/cuda/*.cpp
src/treelearner/cuda/*.cu
src/io/cuda/*.cu
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25 changes: 25 additions & 0 deletions include/LightGBM/cuda/cuda_tree.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -56,6 +56,27 @@ class CUDATree : public Tree {
uint32_t* cuda_bitset_inner,
size_t cuda_bitset_inner_len);

/*!
* \brief Adding prediction value of this tree model to scores
* \param data The dataset
* \param num_data Number of total data
* \param score Will add prediction to score
*/
void AddPredictionToScore(const Dataset* data,
data_size_t num_data,
double* score) const override;

/*!
* \brief Adding prediction value of this tree model to scores
* \param data The dataset
* \param used_data_indices Indices of used data
* \param num_data Number of total data
* \param score Will add prediction to score
*/
void AddPredictionToScore(const Dataset* data,
const data_size_t* used_data_indices,
data_size_t num_data, double* score) const override;

const int* cuda_leaf_parent() const { return cuda_leaf_parent_; }

const int* cuda_left_child() const { return cuda_left_child_; }
Expand Down Expand Up @@ -105,6 +126,10 @@ class CUDATree : public Tree {
size_t cuda_bitset_len,
size_t cuda_bitset_inner_len);

void LaunchAddPredictionToScoreKernel(const Dataset* data,
const data_size_t* used_data_indices,
data_size_t num_data, double* score) const;

void LaunchShrinkageKernel(const double rate);

void LaunchAddBiasKernel(const double val);
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5 changes: 5 additions & 0 deletions include/LightGBM/metric.h
Original file line number Diff line number Diff line change
Expand Up @@ -55,6 +55,11 @@ class Metric {
* \param config Config for metric
*/
LIGHTGBM_EXPORT static Metric* CreateMetric(const std::string& type, const Config& config);

/*!
* \brief Whether boosting is done on CUDA
*/
virtual bool IsCUDAMetric() const { return false; }
};

/*!
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5 changes: 5 additions & 0 deletions include/LightGBM/objective_function.h
Original file line number Diff line number Diff line change
Expand Up @@ -88,6 +88,11 @@ class ObjectiveFunction {
* \brief Load objective function from string object
*/
LIGHTGBM_EXPORT static ObjectiveFunction* CreateObjectiveFunction(const std::string& str);

/*!
* \brief Whether boosting is done on CUDA
*/
virtual bool IsCUDAObjective() const { return false; }
};

} // namespace LightGBM
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3 changes: 2 additions & 1 deletion include/LightGBM/tree_learner.h
Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,8 @@ class TreeLearner {
*/
static TreeLearner* CreateTreeLearner(const std::string& learner_type,
const std::string& device_type,
const Config* config);
const Config* config,
const bool boosting_on_cuda);
};

} // namespace LightGBM
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94 changes: 94 additions & 0 deletions src/boosting/cuda/cuda_score_updater.cpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,94 @@
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for license information.
*/

#include "cuda_score_updater.hpp"

#ifdef USE_CUDA_EXP

namespace LightGBM {

CUDAScoreUpdater::CUDAScoreUpdater(const Dataset* data, int num_tree_per_iteration, const bool boosting_on_cuda):
ScoreUpdater(data, num_tree_per_iteration), num_threads_per_block_(1024), boosting_on_cuda_(boosting_on_cuda) {
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is boosting_on_cuda always true? should we keep this variable?

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No. This is a work around when there are some objective functions not implemented by the CUDA version yet. See line 98 of gbdt.cpp in this PR.

num_data_ = data->num_data();
int64_t total_size = static_cast<int64_t>(num_data_) * num_tree_per_iteration;
InitCUDA(total_size);
has_init_score_ = false;
const double* init_score = data->metadata().init_score();
// if exists initial score, will start from it
if (init_score != nullptr) {
if ((data->metadata().num_init_score() % num_data_) != 0
|| (data->metadata().num_init_score() / num_data_) != num_tree_per_iteration) {
Log::Fatal("Number of class for initial score error");
}
has_init_score_ = true;
CopyFromHostToCUDADevice<double>(cuda_score_, init_score, total_size, __FILE__, __LINE__);
} else {
SetCUDAMemory<double>(cuda_score_, 0, static_cast<size_t>(num_data_), __FILE__, __LINE__);
}
SynchronizeCUDADevice(__FILE__, __LINE__);
if (boosting_on_cuda_) {
// clear host score buffer
score_.clear();
score_.shrink_to_fit();
}
}

void CUDAScoreUpdater::InitCUDA(const size_t total_size) {
AllocateCUDAMemory<double>(&cuda_score_, total_size, __FILE__, __LINE__);
}

CUDAScoreUpdater::~CUDAScoreUpdater() {
DeallocateCUDAMemory<double>(&cuda_score_, __FILE__, __LINE__);
}

inline void CUDAScoreUpdater::AddScore(double val, int cur_tree_id) {
Common::FunctionTimer fun_timer("CUDAScoreUpdater::AddScore", global_timer);
const size_t offset = static_cast<size_t>(num_data_) * cur_tree_id;
LaunchAddScoreConstantKernel(val, offset);
if (!boosting_on_cuda_) {
CopyFromCUDADeviceToHost<double>(score_.data() + offset, cuda_score_ + offset, static_cast<size_t>(num_data_), __FILE__, __LINE__);
}
}

inline void CUDAScoreUpdater::AddScore(const Tree* tree, int cur_tree_id) {
Common::FunctionTimer fun_timer("ScoreUpdater::AddScore", global_timer);
const size_t offset = static_cast<size_t>(num_data_) * cur_tree_id;
tree->AddPredictionToScore(data_, num_data_, cuda_score_ + offset);
if (!boosting_on_cuda_) {
CopyFromCUDADeviceToHost<double>(score_.data() + offset, cuda_score_ + offset, static_cast<size_t>(num_data_), __FILE__, __LINE__);
}
}

inline void CUDAScoreUpdater::AddScore(const TreeLearner* tree_learner, const Tree* tree, int cur_tree_id) {
Common::FunctionTimer fun_timer("ScoreUpdater::AddScore", global_timer);
const size_t offset = static_cast<size_t>(num_data_) * cur_tree_id;
tree_learner->AddPredictionToScore(tree, cuda_score_ + offset);
if (!boosting_on_cuda_) {
CopyFromCUDADeviceToHost<double>(score_.data() + offset, cuda_score_ + offset, static_cast<size_t>(num_data_), __FILE__, __LINE__);
}
}

inline void CUDAScoreUpdater::AddScore(const Tree* tree, const data_size_t* data_indices,
data_size_t data_cnt, int cur_tree_id) {
Common::FunctionTimer fun_timer("ScoreUpdater::AddScore", global_timer);
const size_t offset = static_cast<size_t>(num_data_) * cur_tree_id;
tree->AddPredictionToScore(data_, data_indices, data_cnt, cuda_score_ + offset);
if (!boosting_on_cuda_) {
CopyFromCUDADeviceToHost<double>(score_.data() + offset, cuda_score_ + offset, static_cast<size_t>(num_data_), __FILE__, __LINE__);
}
}

inline void CUDAScoreUpdater::MultiplyScore(double val, int cur_tree_id) {
Common::FunctionTimer fun_timer("CUDAScoreUpdater::MultiplyScore", global_timer);
const size_t offset = static_cast<size_t>(num_data_) * cur_tree_id;
LaunchMultiplyScoreConstantKernel(val, offset);
if (!boosting_on_cuda_) {
CopyFromCUDADeviceToHost<double>(score_.data() + offset, cuda_score_ + offset, static_cast<size_t>(num_data_), __FILE__, __LINE__);
}
}

} // namespace LightGBM

#endif // USE_CUDA_EXP
47 changes: 47 additions & 0 deletions src/boosting/cuda/cuda_score_updater.cu
Original file line number Diff line number Diff line change
@@ -0,0 +1,47 @@
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for license information.
*/

#include "cuda_score_updater.hpp"

#ifdef USE_CUDA_EXP

namespace LightGBM {

__global__ void AddScoreConstantKernel(
const double val,
const size_t offset,
const data_size_t num_data,
double* score) {
const data_size_t data_index = static_cast<data_size_t>(threadIdx.x + blockIdx.x * blockDim.x);
if (data_index < num_data) {
score[data_index + offset] += val;
}
}

void CUDAScoreUpdater::LaunchAddScoreConstantKernel(const double val, const size_t offset) {
const int num_blocks = (num_data_ + num_threads_per_block_) / num_threads_per_block_;
Log::Warning("adding init score = %f", val);
AddScoreConstantKernel<<<num_blocks, num_threads_per_block_>>>(val, offset, num_data_, cuda_score_);
}

__global__ void MultiplyScoreConstantKernel(
const double val,
const size_t offset,
const data_size_t num_data,
double* score) {
const data_size_t data_index = static_cast<data_size_t>(threadIdx.x + blockIdx.x * blockDim.x);
if (data_index < num_data) {
score[data_index] *= val;
}
}

void CUDAScoreUpdater::LaunchMultiplyScoreConstantKernel(const double val, const size_t offset) {
const int num_blocks = (num_data_ + num_threads_per_block_) / num_threads_per_block_;
MultiplyScoreConstantKernel<<<num_blocks, num_threads_per_block_>>>(val, offset, num_data_, cuda_score_);
}

} // namespace LightGBM

#endif // USE_CUDA_EXP
65 changes: 65 additions & 0 deletions src/boosting/cuda/cuda_score_updater.hpp
Original file line number Diff line number Diff line change
@@ -0,0 +1,65 @@
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for license information.
*/

#ifndef LIGHTGBM_BOOSTING_CUDA_CUDA_SCORE_UPDATER_HPP_
#define LIGHTGBM_BOOSTING_CUDA_CUDA_SCORE_UPDATER_HPP_

#ifdef USE_CUDA_EXP

#include <LightGBM/cuda/cuda_utils.h>

#include "../score_updater.hpp"

namespace LightGBM {

class CUDAScoreUpdater: public ScoreUpdater {
public:
CUDAScoreUpdater(const Dataset* data, int num_tree_per_iteration, const bool boosting_on_cuda);

~CUDAScoreUpdater();

inline void AddScore(double val, int cur_tree_id) override;

inline void AddScore(const Tree* tree, int cur_tree_id) override;

inline void AddScore(const TreeLearner* tree_learner, const Tree* tree, int cur_tree_id) override;

inline void AddScore(const Tree* tree, const data_size_t* data_indices,
data_size_t data_cnt, int cur_tree_id) override;

inline void MultiplyScore(double val, int cur_tree_id) override;

inline const double* score() const override {
if (boosting_on_cuda_) {
return cuda_score_;
} else {
return score_.data();
}
}

/*! \brief Disable copy */
CUDAScoreUpdater& operator=(const CUDAScoreUpdater&) = delete;

CUDAScoreUpdater(const CUDAScoreUpdater&) = delete;

private:
void InitCUDA(const size_t total_size);

void LaunchAddScoreConstantKernel(const double val, const size_t offset);

void LaunchMultiplyScoreConstantKernel(const double val, const size_t offset);

double* cuda_score_;

const int num_threads_per_block_;

const bool boosting_on_cuda_;
};

} // namespace LightGBM

#endif // USE_CUDA_EXP

#endif // LIGHTGBM_BOOSTING_CUDA_CUDA_SCORE_UPDATER_HPP_
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