row_to_column.hpp

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#ifndef TATAMI_MULT_DENSE_MATRIX_DENSE_COLUMN_ROW_TO_COLUMN_HPP
#define TATAMI_MULT_DENSE_MATRIX_DENSE_COLUMN_ROW_TO_COLUMN_HPP
 
#include <cstddef>
#include <vector>
#include <optional>
 
#include "tatami/tatami.hpp"
#include "sanisizer/sanisizer.hpp"
 
#include "../../utils.hpp"
 
namespace tatami_mult {
 
/* See https://github.com/tatami-inc/test-multiplication/tree/master/dense_column/dense_matrix
 * for an explanation of the choice of algorithm.
 */
 
struct MultiplyDenseColumnWithDenseRowMatrixToColumnOutputOptions {
    int num_threads = 1;
 
    int primary_block_size = 16;
 
    int secondary_block_size = 64;
};
 
template<typename LeftValue_, typename LeftIndex_, typename RightColumns_, typename GetRightRow_, typename Output_>
void multiply_dense_column_with_dense_row_matrix_to_column_output(
    const tatami::Matrix<LeftValue_, LeftIndex_>& left,
    const RightColumns_ right_columns,
    GetRightRow_ get_right_row,
    Output_* const output,
    const MultiplyDenseColumnWithDenseRowMatrixToColumnOutputOptions& options
) {
    const auto left_NR = left.nrow();
    const auto common_dim = left.ncol();
 
    // Product must fit in a size_t in order for output to have been allocated correctly in the first place.
    // Technically, right_columns could be larger than a size_t if left_NR == 0, but the product after wraparound would still be zero, so it's fine.
    std::fill_n(output, sanisizer::product_unsafe<std::size_t>(left_NR, right_columns), 0);
 
    const bool do_parallel = options.num_threads > 1;
    std::optional<std::vector<std::optional<std::vector<Output_> > > > tmp_results;
    if (do_parallel) {
        tmp_results.emplace(sanisizer::cast<I<decltype(tmp_results->size())> >(options.num_threads - 1));
    }
 
    const auto num_used = tatami::parallelize([&](int t, LeftIndex_ start, LeftIndex_ length) -> void {
        auto left_ext = tatami::consecutive_extractor<false>(left, false, start, length);
 
        std::optional<std::vector<Output_> > tmp_output;
        Output_* outptr; 
        if (!do_parallel || t == 0) {
            outptr = output;
        } else {
            tmp_output.emplace(sanisizer::product<I<decltype(tmp_output->size())> >(left_NR, right_columns));
            outptr = tmp_output->data();
        }
 
        if (options.primary_block_size == 1) {
            auto left_buffer = tatami::create_container_of_Index_size<std::vector<Output_> >(left_NR);
            for (LeftIndex_ cd = 0; cd < length; ++cd) {
                const auto left_ptr = left_ext->fetch(left_buffer.data());
                const auto right_ptr = get_right_row(start + cd);
                for (RightColumns_ rc = 0; rc < right_columns; ++rc) {
                    const Output_ mult = right_ptr[rc];
                    for (LeftIndex_ lr = 0; lr < left_NR; ++lr) {
                        outptr[sanisizer::nd_offset<std::size_t>(lr, left_NR, rc)] += mult * static_cast<Output_>(left_ptr[lr]);
                    }
                }
            }
 
        } else {
            std::vector<std::vector<LeftValue_> > left_buffers;
            std::vector<const LeftValue_*> left_ptrs;
            {
                const LeftIndex_ max_block_cols = sanisizer::min(length, options.primary_block_size);
                left_buffers.reserve(max_block_cols);
                tatami::resize_container_to_Index_size(left_ptrs, max_block_cols);
                for (LeftIndex_ cd = 0; cd < max_block_cols; ++cd) {
                    left_buffers.emplace_back(tatami::cast_Index_to_container_size<std::vector<LeftValue_> >(left_NR));
                }
            }
 
            LeftIndex_ cd = 0;
            while (cd < length) {
                const auto cd_num = sanisizer::min(options.primary_block_size, length - cd);
                for (LeftIndex_ cd_counter = 0; cd_counter < cd_num; ++cd_counter) {
                    left_ptrs[cd_counter] = left_ext->fetch(left_buffers[cd_counter].data());
                }
 
                RightColumns_ rc = 0;
                while (rc < right_columns) {
                    const RightColumns_ rc_end = rc + sanisizer::min(options.primary_block_size, right_columns - rc);
                    LeftIndex_ lr = 0;
                    while (lr < left_NR) {
                        const LeftIndex_ lr_end = lr + sanisizer::min(options.secondary_block_size, left_NR - lr);
 
                        for (LeftIndex_ cd_counter = 0; cd_counter < cd_num; ++cd_counter) {
                            const auto leftcol = left_ptrs[cd_counter];
                            const auto rightrow = get_right_row(start + cd + cd_counter);
                            for (auto rc_copy = rc; rc_copy < rc_end; ++rc_copy) {
                                const Output_ mult = rightrow[rc_copy];
                                for (auto lr_copy = lr; lr_copy < lr_end; ++lr_copy) {
                                    outptr[sanisizer::nd_offset<std::size_t>(lr_copy, left_NR, rc_copy)] += mult * static_cast<Output_>(leftcol[lr_copy]);
                                }
                            }
                        }
 
                        lr = lr_end;
                    }
                    rc = rc_end;
                }
                cd += cd_num;
            }
        }
 
        if (do_parallel && t > 0) {
            (*tmp_results)[t - 1] = std::move(tmp_output);
        }
    }, common_dim, options.num_threads);
 
    if (do_parallel) {
        for (int u = 1; u < num_used; ++u) {
            const auto& tmp = *((*tmp_results)[u - 1]);
            const auto N = tmp.size();
            for (I<decltype(N)> x = 0; x < N; ++x) {
                output[x] += tmp[x];
            }
        }
    }
}
 
template<typename LeftValue_, typename LeftIndex_, typename RightValue_, typename RightIndex_, typename Output_>
void multiply_dense_column_with_dense_row_matrix_to_column_output(
    const tatami::Matrix<LeftValue_, LeftIndex_>& left,
    const tatami::Matrix<RightValue_, RightIndex_>& right,
    Output_* const output,
    const MultiplyDenseColumnWithDenseRowMatrixToColumnOutputOptions& options
) {
    const auto left_NR = left.nrow();
    const auto common_dim = left.ncol();
    const auto right_NC = right.ncol();
    std::fill_n(output, sanisizer::product_unsafe<std::size_t>(left_NR, right_NC), 0);
 
    const bool do_parallel = options.num_threads > 1;
    std::optional<std::vector<std::optional<std::vector<Output_> > > > tmp_results;
    if (do_parallel) {
        tmp_results.emplace(sanisizer::cast<I<decltype(tmp_results->size())> >(options.num_threads - 1));
    }
 
    const auto num_used = tatami::parallelize([&](int t, LeftIndex_ start, LeftIndex_ length) -> void {
        auto left_ext = tatami::consecutive_extractor<false>(left, false, start, length);
        auto right_ext = tatami::consecutive_extractor<false>(right, true, start, length);
 
        std::optional<std::vector<Output_> > tmp_output;
        Output_* outptr; 
        if (!do_parallel || t == 0) {
            outptr = output;
        } else {
            tmp_output.emplace(sanisizer::product<I<decltype(tmp_output->size())> >(left_NR, right_NC));
            outptr = tmp_output->data();
        }
 
        if (options.primary_block_size == 1) {
            auto left_buffer = tatami::create_container_of_Index_size<std::vector<Output_> >(left_NR);
            auto right_buffer = tatami::create_container_of_Index_size<std::vector<Output_> >(right_NC);
 
            for (LeftIndex_ cd = 0; cd < length; ++cd) {
                const auto left_ptr = left_ext->fetch(left_buffer.data());
                const auto right_ptr = right_ext->fetch(right_buffer.data());
                for (RightIndex_ rc = 0; rc < right_NC; ++rc) {
                    const Output_ mult = right_ptr[rc];
                    for (LeftIndex_ lr = 0; lr < left_NR; ++lr) {
                        outptr[sanisizer::nd_offset<std::size_t>(lr, left_NR, rc)] += mult * static_cast<Output_>(left_ptr[lr]);
                    }
                }
            }
 
        } else {
            std::vector<std::vector<LeftValue_> > left_buffers;
            std::vector<std::vector<RightValue_> > right_buffers;
            std::vector<const LeftValue_*> left_ptrs;
            std::vector<const RightValue_*> right_ptrs;
            {
                const LeftIndex_ max_block_cols = sanisizer::min(length, options.primary_block_size);
                left_buffers.reserve(max_block_cols);
                tatami::resize_container_to_Index_size(left_ptrs, max_block_cols);
                right_buffers.reserve(max_block_cols);
                tatami::resize_container_to_Index_size(right_ptrs, max_block_cols);
                for (LeftIndex_ cd = 0; cd < max_block_cols; ++cd) {
                    left_buffers.emplace_back(tatami::cast_Index_to_container_size<std::vector<LeftValue_> >(left_NR));
                    right_buffers.emplace_back(tatami::cast_Index_to_container_size<std::vector<RightValue_> >(right_NC));
                }
            }
 
            LeftIndex_ cd = 0;
            while (cd < length) {
                const auto cd_num = sanisizer::min(options.primary_block_size, length - cd);
                for (LeftIndex_ cd_counter = 0; cd_counter < cd_num; ++cd_counter) {
                    left_ptrs[cd_counter] = left_ext->fetch(left_buffers[cd_counter].data());
                    right_ptrs[cd_counter] = right_ext->fetch(right_buffers[cd_counter].data());
                }
 
                RightIndex_ rc = 0;
                while (rc < right_NC) {
                    const RightIndex_ rc_end = rc + sanisizer::min(options.primary_block_size, right_NC - rc);
                    LeftIndex_ lr = 0;
                    while (lr < left_NR) {
                        const LeftIndex_ lr_end = lr + sanisizer::min(options.secondary_block_size, left_NR - lr);
 
                        for (LeftIndex_ cd_counter = 0; cd_counter < cd_num; ++cd_counter) {
                            const auto leftcol = left_ptrs[cd_counter];
                            const auto rightrow = right_ptrs[cd_counter];
                            for (auto rc_copy = rc; rc_copy < rc_end; ++rc_copy) {
                                const Output_ mult = rightrow[rc_copy];
                                for (auto lr_copy = lr; lr_copy < lr_end; ++lr_copy) {
                                    outptr[sanisizer::nd_offset<std::size_t>(lr_copy, left_NR, rc_copy)] += mult * static_cast<Output_>(leftcol[lr_copy]);
                                }
                            }
                        }
 
                        lr = lr_end;
                    }
                    rc = rc_end;
                }
                cd += cd_num;
            }
        }
 
        if (do_parallel && t > 0) {
            (*tmp_results)[t - 1] = std::move(tmp_output);
        }
    }, common_dim, options.num_threads);
 
    if (do_parallel) {
        for (int u = 1; u < num_used; ++u) {
            const auto& tmp = *((*tmp_results)[u - 1]);
            const auto N = tmp.size();
            for (I<decltype(N)> x = 0; x < N; ++x) {
                output[x] += tmp[x];
            }
        }
    }
}
 
}
 
#endif