monolish_dense.hpp

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#pragma once
#include "monolish_matrix.hpp"
 
namespace monolish {
template <typename Float> class vector;
template <typename TYPE, typename Float> class view1D;
namespace matrix {
template <typename Float> class Dense {
private:
  size_t rowN;
 
  size_t colN;
 
  size_t nnz;
 
  mutable bool gpu_status = false;
 
public:
  std::vector<Float> val;
 
  Dense() {}
 
  void convert(const COO<Float> &coo);
 
  void convert(const Dense<Float> &dense);
 
  Dense(const COO<Float> &coo) { convert(coo); }
 
  Dense(const Dense<Float> &dense);
 
  Dense(const size_t M, const size_t N);
 
  Dense(const size_t M, const size_t N, const Float *value);
 
  Dense(const size_t M, const size_t N, const std::vector<Float> &value);
 
  Dense(const size_t M, const size_t N, const vector<Float> &value);
 
  Dense(const size_t M, const size_t N,
        const std::initializer_list<Float> &list);
 
  Dense(const size_t M, const size_t N, const Float min, const Float max);
 
  Dense(const size_t M, const size_t N, const Float value);
 
  void set_ptr(const size_t M, const size_t N, const std::vector<Float> &value);
 
  size_t get_row() const { return rowN; }
 
  size_t get_col() const { return colN; }
 
  size_t get_nnz() const { return get_row() * get_col(); }
 
  void set_row(const size_t N) { rowN = N; };
 
  void set_col(const size_t M) { colN = M; };
 
  void set_nnz(const size_t NZ) { nnz = NZ; };
 
  std::string type() const { return "Dense"; }
 
  Dense &transpose();
 
  void transpose(const Dense &B);
 
  double get_data_size() const { return get_nnz() * sizeof(Float) / 1.0e+9; }
 
  Float at(const size_t i, const size_t j) const;
 
  Float at(const size_t i, const size_t j) {
    return static_cast<const Dense *>(this)->at(i, j);
  };
 
  void insert(const size_t i, const size_t j, const Float Val);
 
  void print_all(bool force_cpu = false) const;
 
  // communication
  // ///////////////////////////////////////////////////////////////////////////
  void send() const;
 
  void recv();
 
  void nonfree_recv();
 
  void device_free() const;
 
  bool get_device_mem_stat() const { return gpu_status; }
 
  ~Dense() {
    if (get_device_mem_stat()) {
      device_free();
    }
  }
 
 
  void diag(vector<Float> &vec) const;
  void diag(view1D<vector<Float>, Float> &vec) const;
  void diag(view1D<matrix::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 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 fill(Float value);
 
  void operator=(const Dense<Float> &mat);
 
  bool equal(const Dense<Float> &mat,
             bool compare_cpu_and_device = false) const;
 
  bool operator==(const Dense<Float> &mat) const;
 
  bool operator!=(const Dense<Float> &mat) const;
 
 
  void diag_add(const Float alpha);
 
  void diag_sub(const Float alpha);
 
  void diag_mul(const Float alpha);
 
  void diag_div(const Float alpha);
 
  void diag_add(const vector<Float> &vec);
  void diag_add(const view1D<vector<Float>, Float> &vec);
  void diag_add(const view1D<matrix::Dense<Float>, Float> &vec);
 
  void diag_sub(const vector<Float> &vec);
  void diag_sub(const view1D<vector<Float>, Float> &vec);
  void diag_sub(const view1D<matrix::Dense<Float>, Float> &vec);
 
  void diag_mul(const vector<Float> &vec);
  void diag_mul(const view1D<vector<Float>, Float> &vec);
  void diag_mul(const view1D<matrix::Dense<Float>, Float> &vec);
 
  void diag_div(const vector<Float> &vec);
  void diag_div(const view1D<vector<Float>, Float> &vec);
  void diag_div(const view1D<matrix::Dense<Float>, Float> &vec);
};
} // namespace matrix
} // namespace monolish