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			199 lines
		
	
	
	
		
			5.3 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			199 lines
		
	
	
	
		
			5.3 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
/*
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    This file is part of TON Blockchain Library.
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    TON Blockchain Library is free software: you can redistribute it and/or modify
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    it under the terms of the GNU Lesser General Public License as published by
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    the Free Software Foundation, either version 2 of the License, or
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    (at your option) any later version.
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    TON Blockchain Library is distributed in the hope that it will be useful,
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    but WITHOUT ANY WARRANTY; without even the implied warranty of
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    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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    GNU Lesser General Public License for more details.
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    You should have received a copy of the GNU Lesser General Public License
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    along with TON Blockchain Library.  If not, see <http://www.gnu.org/licenses/>.
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    Copyright 2017-2020 Telegram Systems LLP
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*/
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#pragma once
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#include "td/fec/algebra/Octet.h"
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#include "td/fec/algebra/Simd.h"
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#include "td/utils/Span.h"
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#include "td/utils/format.h"
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namespace td {
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class MatrixGF256 {
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 public:
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  MatrixGF256(size_t rows, size_t cols) : rows_(rows), cols_(cols) {
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    stride_ = (cols_ + Simd::alignment() - 1) / Simd::alignment() * Simd::alignment();
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    storage_ = std::make_unique<uint8[]>(stride_ * rows + Simd::alignment() - 1);
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    matrix_ = storage_.get();
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    while (!Simd::is_aligned_pointer(matrix_)) {
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      matrix_++;
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    }
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    CHECK(Simd::is_aligned_pointer(matrix_));
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    CHECK(Simd::is_aligned_pointer(matrix_ + stride_));
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    CHECK(static_cast<size_t>(matrix_ - storage_.get()) < Simd::alignment());
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  }
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  void set_zero() {
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    std::fill(matrix_, matrix_ + stride_ * rows_, 0);
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  }
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  size_t rows() const {
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    return rows_;
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  }
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  size_t cols() const {
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    return cols_;
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  }
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  MatrixGF256 apply_row_permutation(Span<uint32> permutation) {
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    MatrixGF256 res(rows_, cols_);
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    for (size_t row = 0; row < rows_; row++) {
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      res.row(row).copy_from(this->row(permutation[row]));
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    }
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    return res;
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  }
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  Octet get(size_t row, size_t col) const {
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    DCHECK(row < rows_ && col < cols_);
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    return Octet(matrix_[row * stride_ + col]);
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  }
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  void set(size_t row, size_t col, Octet o) {
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    DCHECK(row < rows_ && col < cols_);
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    matrix_[row * stride_ + col] = o.value();
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  }
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  void row_multiply(size_t row, Octet o) {
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    uint8* p = row_ptr(row);
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    Simd::gf256_mul(p, o.value(), stride_);
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  }
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  Slice row(size_t row) const {
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    return Slice(row_ptr(row), cols());
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  }
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  MutableSlice row(size_t row) {
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    return MutableSlice(row_ptr(row), cols());
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  }
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  template <class M>
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  void set_from(const M& m, size_t row_offset, size_t col_offset) {
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    auto to = block_view(row_offset, col_offset, rows() - row_offset, cols() - col_offset);
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    for (size_t i = 0; i < m.rows(); i++) {
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      to.row(i).copy_from(m.row(i));
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    }
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  }
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  MatrixGF256 copy() {
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    MatrixGF256 res(rows(), cols());
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    res.set_from(*this, 0, 0);
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    return res;
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  }
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  void add(const MatrixGF256& m) {
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    CHECK(m.rows() == rows());
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    CHECK(m.cols() == cols());
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    for (size_t i = 0; i < m.rows(); i++) {
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      auto* to = row_ptr(i);
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      auto* from = m.row_ptr(i);
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      row_add(to, from);
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    }
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  }
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  // row(a) += row(b) * m
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  void row_add_mul(size_t a, size_t b, Octet m) {
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    row_add_mul(row_ptr(a), row_ptr(b), m);
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  }
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  void row_add_mul(size_t a, Slice b, Octet m) {
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    row_add_mul(row_ptr(a), b.ubegin(), m);
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  }
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  // row(a) += row(b)
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  void row_add(size_t a, size_t b) {
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    row_add(row_ptr(a), row_ptr(b));
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  }
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  void row_add(size_t a, Slice b) {
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    row_add(row_ptr(a), b.ubegin());
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  }
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  void row_set(size_t a, Slice b) {
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    row(a).copy_from(b);
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  }
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  class BlockView {
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   public:
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    BlockView(size_t row_offset, size_t col_offset, size_t row_size, size_t col_size, MatrixGF256& m)
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        : row_offset_(row_offset), col_offset_(col_offset), row_size_(row_size), col_size_(col_size), m_(m) {
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    }
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    size_t cols() const {
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      return col_size_;
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    }
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    size_t rows() const {
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      return row_size_;
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    }
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    Slice row(size_t row) const {
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      return m_.row(row_offset_ + row).remove_prefix(col_offset_);
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    }
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    MutableSlice row(size_t row) {
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      return m_.row(row_offset_ + row).remove_prefix(col_offset_);
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    }
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   private:
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    size_t row_offset_;
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    size_t col_offset_;
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    size_t row_size_;
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    size_t col_size_;
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    MatrixGF256& m_;
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  };
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  BlockView block_view(size_t row_offset, size_t col_offset, size_t row_size, size_t col_size) {
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    return BlockView(row_offset, col_offset, row_size, col_size, *this);
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  }
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 private:
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  uint8* matrix_;
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  size_t rows_;
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  size_t cols_;
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  size_t stride_;
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  std::unique_ptr<uint8[]> storage_;
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  uint8* row_ptr(size_t row) {
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    return matrix_ + stride_ * row;
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  }
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  const uint8* row_ptr(size_t row) const {
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    return matrix_ + stride_ * row;
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  }
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  void row_add_mul(uint8* ap, const uint8* bp, Octet m) {
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    uint8 u = m.value();
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    if (u == 0) {
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      return;
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    }
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    if (u == 1) {
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      return row_add(ap, bp);
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    }
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    Simd::gf256_add_mul(ap, bp, u, stride_);
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  }
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  void row_add(uint8* ap, const uint8* bp) {
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    Simd::gf256_add(ap, bp, stride_);
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  }
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};
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inline StringBuilder& operator<<(StringBuilder& sb, const MatrixGF256& m) {
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  sb << "\n";
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  for (uint32 i = 0; i < m.rows(); i++) {
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    auto row = m.row(i);
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    for (uint32 j = 0; j < m.cols(); j++) {
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      uint8 x = row[j];
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      sb << " " << format::hex_digit(x / 16) << format::hex_digit(x % 16);
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    }
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    sb << "\n";
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  }
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  return sb;
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}
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}  // namespace td
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