sharded_quadratic_program.h

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// Copyright 2010-2021 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
 
#ifndef PDLP_SHARDED_QUADRATIC_PROGRAM_H_
#define PDLP_SHARDED_QUADRATIC_PROGRAM_H_
 
#include <cstdint>
#include <memory>
 
#include "Eigen/Core"
#include "Eigen/SparseCore"
#include "ortools/base/threadpool.h"
#include "ortools/pdlp/quadratic_program.h"
#include "ortools/pdlp/sharder.h"
 
namespace operations_research::pdlp {
 
// This class stores:
//  - A QuadraticProgram (QP)
//  - A transposed version of the QP's constraint matrix
//  - A thread pool
//  - Various Sharder objects for doing sharded matrix and vector computations.
class ShardedQuadraticProgram {
 public:
  // Requires num_shards >= num_threads >= 1.
  // Note that the qp is intentionally passed by value.
  ShardedQuadraticProgram(QuadraticProgram qp, int num_threads, int num_shards);
 
  // Movable but not copyable.
  ShardedQuadraticProgram(const ShardedQuadraticProgram&) = delete;
  ShardedQuadraticProgram& operator=(const ShardedQuadraticProgram&) = delete;
  ShardedQuadraticProgram(ShardedQuadraticProgram&&) = default;
  ShardedQuadraticProgram& operator=(ShardedQuadraticProgram&&) = default;
 
  const QuadraticProgram& Qp() const { return qp_; }
 
  // Returns a reference to the transpose of the QP's constraint matrix.
  const Eigen::SparseMatrix<double, Eigen::ColMajor, int64_t>&
  TransposedConstraintMatrix() const {
    return transposed_constraint_matrix_;
  }
 
  // Returns a Sharder intended for the columns of the QP's constraint matrix.
  const Sharder& ConstraintMatrixSharder() const {
    return constraint_matrix_sharder_;
  }
  // Returns a Sharder intended for the rows of the QP's constraint matrix.
  const Sharder& TransposedConstraintMatrixSharder() const {
    return transposed_constraint_matrix_sharder_;
  }
  // Returns a Sharder intended for primal vectors.
  const Sharder& PrimalSharder() const { return primal_sharder_; }
  // Returns a Sharder intended for dual vectors.
  const Sharder& DualSharder() const { return dual_sharder_; }
 
  int64_t PrimalSize() const { return qp_.variable_lower_bounds.size(); }
  int64_t DualSize() const { return qp_.constraint_lower_bounds.size(); }
 
  // Rescale the QP (including objective, variable bounds, constraint bounds,
  // constraint matrix, and transposed constraint matrix) based on
  // col_scaling_vec and row_scaling_vec. That is, rescale the problem so that
  // each variable is rescaled as variable[i] <- variable[i] /
  // col_scaling_vec[i], and the j-th constraint is multiplied by
  // row_scaling_vec[j]. col_scaling_vec and row_scaling_vec must be positive.
  void RescaleQuadraticProgram(const Eigen::VectorXd& col_scaling_vec,
                               const Eigen::VectorXd& row_scaling_vec);
 
 private:
  QuadraticProgram qp_;
  Eigen::SparseMatrix<double, Eigen::ColMajor, int64_t>
      transposed_constraint_matrix_;
  std::unique_ptr<ThreadPool> thread_pool_;
  Sharder constraint_matrix_sharder_;
  Sharder transposed_constraint_matrix_sharder_;
  Sharder primal_sharder_;
  Sharder dual_sharder_;
};
 
}  // namespace operations_research::pdlp
 
#endif  // PDLP_SHARDED_QUADRATIC_PROGRAM_H_