monolish_coo.hpp

Go to the documentation of this file.

#pragma once
#include <exception>
#include <memory>
#include <omp.h>
#include <stdexcept>
#include <string>
#include <vector>
 
#if USE_SXAT
#undef _HAS_CPP17
#endif
#include <random>
#if USE_SXAT
#define _HAS_CPP17 1
#endif
 
#define MM_BANNER "%%MatrixMarket"
#define MM_MAT "matrix"
#define MM_VEC "vector"
#define MM_FMT "coordinate"
#define MM_TYPE_REAL "real"
#define MM_TYPE_GENERAL "general"
#define MM_TYPE_SYMM "symmetric"
 
namespace monolish {
template <typename Float> class vector;
template <typename TYPE, typename Float> class view1D;
namespace tensor {
template <typename Float> class tensor_Dense;
}
namespace matrix {
template <typename Float> class Dense;
template <typename Float> class CRS;
template <typename Float> class LinearOperator;
 
template <typename Float> class COO {
private:
  size_t rowN;
 
  size_t colN;
 
  // size_t nnz;
 
  mutable bool gpu_status = false;
 
public:
  std::vector<int> row_index;
 
  std::vector<int> col_index;
 
  std::shared_ptr<Float> val;
 
  size_t val_nnz = 0;
 
  std::size_t alloc_nnz = 0;
 
  bool val_create_flag = false;
 
  COO()
      : rowN(0), colN(0), gpu_status(false), row_index(), col_index(),
        val_nnz(0) {
    val_create_flag = true;
  }
 
  COO(const size_t M, const size_t N)
      : rowN(M), colN(N), gpu_status(false), row_index(), col_index(),
        val_nnz(0) {
    val_create_flag = true;
  }
 
  COO(const size_t M, const size_t N, const size_t NNZ, const int *row,
      const int *col, const Float *value);
 
  COO(const size_t M, const size_t N, const size_t NNZ,
      const std::vector<int> &row, const std::vector<int> &col,
      const std::vector<Float> &value) {
    this = COO(M, N, NNZ, row.data(), col.data(), value.data());
  }
 
  COO(const size_t M, const size_t N, const size_t NNZ,
      const std::vector<int> &row, const std::vector<int> &col,
      const vector<Float> &value) {
    assert(value.get_device_mem_stat() == false);
    this = COO(M, N, NNZ, row.data(), col.data(), value.data());
  }
 
  COO(const size_t M, const size_t N, const size_t NNZ, const int *row,
      const int *col, const Float *value, const size_t origin);
 
  COO(const size_t M, const size_t N, const size_t NNZ,
      const std::vector<int> &row, const std::vector<int> &col,
      const std::vector<Float> &value, const size_t origin) {
    this = COO(M, N, NNZ, row.data(), col.data(), value.data(), origin);
  }
 
  COO(const matrix::COO<Float> &coo);
 
  COO(const matrix::COO<Float> &coo, Float value);
 
  void convert(const matrix::CRS<Float> &crs);
 
  COO(const matrix::CRS<Float> &crs) {
    val_create_flag = true;
    convert(crs);
  }
 
  void convert(const matrix::Dense<Float> &dense);
 
  COO(const matrix::Dense<Float> &dense) {
    val_create_flag = true;
    convert(dense);
  }
 
  void convert(const matrix::LinearOperator<Float> &linearoperator);
 
  COO(const matrix::LinearOperator<Float> &linearoperator) {
    val_create_flag = true;
    convert(linearoperator);
  }
 
  void set_row(const size_t M) { rowN = M; };
 
  void set_col(const size_t N) { colN = N; };
 
  // void set_nnz(const size_t NNZ) { val_nnz = NNZ; };
 
  // communication
  // ///////////////////////////////////////////////////////////////////////////
  void send() const {
    throw std::runtime_error("error, GPU util of COO format is not impl. ");
  };
 
  void recv() const {
    throw std::runtime_error("error, GPU util of COO format is not impl. ");
  };
 
  void device_free() const {};
 
  [[nodiscard]] bool get_device_mem_stat() const { return gpu_status; }
 
  ~COO() {
    if (val_create_flag) {
      if (get_device_mem_stat()) {
        device_free();
      }
    }
  }
 
  [[nodiscard]] const Float *data() const { return val.get(); }
 
  [[nodiscard]] Float *data() { return val.get(); }
 
  void resize(size_t N, Float Val = 0) {
    if (get_device_mem_stat()) {
      throw std::runtime_error("Error, GPU matrix cant use resize");
    }
    if (val_create_flag) {
      std::shared_ptr<Float> tmp(new Float[N], std::default_delete<Float[]>());
      size_t copy_size = std::min(val_nnz, N);
      for (size_t i = 0; i < copy_size; ++i) {
        tmp.get()[i] = data()[i];
      }
      for (size_t i = copy_size; i < N; ++i) {
        tmp.get()[i] = Val;
      }
      val = tmp;
      alloc_nnz = N;
      val_nnz = N;
 
      row_index.resize(N);
      col_index.resize(N);
    } else {
      throw std::runtime_error("Error, not create vector cant use resize");
    }
  }
 
  // I/O
  // ///////////////////////////////////////////////////////////////////////////
 
  void input_mm(const std::string filename);
 
  COO(const std::string filename) { input_mm(filename); }
 
  void output_mm(const std::string filename) const;
 
  void print_all(bool force_cpu = false) const;
 
  void print_all(const std::string filename) const;
 
  [[nodiscard]] Float at(const size_t i, const size_t j) const;
 
  [[nodiscard]] Float at(const size_t i, const size_t j) {
    return static_cast<const COO *>(this)->at(i, j);
  };
 
  void set_ptr(const size_t rN, const size_t cN, const std::vector<int> &r,
               const std::vector<int> &c, const std::vector<Float> &v);
 
  void set_ptr(const size_t rN, const size_t cN, const std::vector<int> &r,
               const std::vector<int> &c, const size_t vsize, const Float *v);
 
  [[nodiscard]] size_t get_row() const { return rowN; }
 
  [[nodiscard]] size_t get_col() const { return colN; }
 
  [[nodiscard]] size_t get_nnz() const { return val_nnz; }
 
  void fill(Float value);
 
  [[nodiscard]] std::vector<int> &get_row_ptr() { return row_index; }
 
  [[nodiscard]] std::vector<int> &get_col_ind() { return col_index; }
 
  [[nodiscard]] std::vector<Float> get_val_ptr() {
    std::vector<Float> val(val_nnz);
    for (size_t i = 0; i < val_nnz; ++i) {
      val[i] = data()[i];
    }
    return val;
  }
 
  [[nodiscard]] const std::vector<int> &get_row_ptr() const {
    return row_index;
  }
 
  [[nodiscard]] const std::vector<int> &get_col_ind() const {
    return col_index;
  }
 
  [[nodiscard]] const std::vector<Float> get_val_ptr() const {
    std::vector<Float> val(val_nnz);
    for (size_t i = 0; i < val_nnz; ++i) {
      val[i] = data()[i];
    }
    return val;
  }
 
  // Utility
  // ///////////////////////////////////////////////////////////////////////////
 
  void transpose();
 
  void transpose(const COO &B);
 
  double get_data_size() const {
    return 3 * get_nnz() * sizeof(Float) / 1.0e+9;
  }
 
  [[nodiscard]] std::string type() const { return "COO"; }
 
  void diag(vector<Float> &vec) const;
  void diag(view1D<vector<Float>, Float> &vec) const;
  void diag(view1D<matrix::Dense<Float>, Float> &vec) const;
  void diag(view1D<tensor::tensor_Dense<Float>, Float> &vec) const;
 
  void row(const size_t r, vector<Float> &vec) const;
  void row(const size_t r, view1D<vector<Float>, Float> &vec) const;
  void row(const size_t r, view1D<matrix::Dense<Float>, Float> &vec) const;
  void row(const size_t r,
           view1D<tensor::tensor_Dense<Float>, Float> &vec) const;
 
  void col(const size_t c, vector<Float> &vec) const;
  void col(const size_t c, view1D<vector<Float>, Float> &vec) const;
  void col(const size_t c, view1D<matrix::Dense<Float>, Float> &vec) const;
  void col(const size_t c,
           view1D<tensor::tensor_Dense<Float>, Float> &vec) const;
 
 
  void operator=(const COO<Float> &mat);
 
  [[nodiscard]] Float &operator[](size_t i) {
    if (get_device_mem_stat()) {
      throw std::runtime_error("Error, GPU vector cant use operator[]");
    }
    return data()[i];
  }
 
  [[nodiscard]] bool equal(const COO<Float> &mat,
                           bool compare_cpu_and_device = false) const;
 
  [[nodiscard]] bool operator==(const COO<Float> &mat) const;
 
  [[nodiscard]] bool operator!=(const COO<Float> &mat) const;
 
  void insert(const size_t m, const size_t n, const Float val);
 
private:
  void _q_sort(int lo, int hi);
 
public:
  void sort(bool merge);
};
} // namespace matrix
} // namespace monolish