[CUDA] Initial work for boosting and evaluation with CUDA (microsoft#…

…5279)

* initial work for boosting and evaluation with CUDA

* fix compatibility with CPU code

* fix creating objective without USE_CUDA_EXP

* fix static analysis errors

* fix static analysis errors

CMakeLists.txt

@@ -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

include/LightGBM/cuda/cuda_tree.hpp

@@ -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_; }
@@ -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);

include/LightGBM/metric.h

@@ -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; }
 };
 
 /*!

include/LightGBM/objective_function.h

@@ -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

include/LightGBM/tree_learner.h

@@ -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

src/boosting/cuda/cuda_score_updater.cpp

@@ -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) {
+  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

src/boosting/cuda/cuda_score_updater.cu

@@ -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

src/boosting/cuda/cuda_score_updater.hpp

@@ -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_