cuElim/include/gf256/gf256_mat.cuh

#ifndef GF256_MAT_CUH
#define GF256_MAT_CUH

#include "gf256_header.cuh"

#include <random>
#include <vector>
#include <algorithm>

struct ElimResult
{
    size_t rank;
    vector<size_t> pivot;
    vector<size_t> swap_row;
};

class MatGF256
{
public:
    enum MatType
    {
        root,
        window,
        moved,
    };
    // 只能构造root矩阵
    MatGF256(size_t nrows, size_t ncols) : nrows(nrows), ncols(ncols), type(root)
    {
        width = (ncols - 1) / gf256_num + 1;
        rowstride = ((width - 1) / 4 + 1) * 4; // 以32字节（4*64bit）为单位对齐
        CUDA_CHECK(cudaMallocManaged((void **)&data, nrows * rowstride * sizeof(base_t)));
        CUDA_CHECK(cudaMemset(data, 0, nrows * rowstride * sizeof(base_t)));
    }
    // 只能以base_t为单位建立window矩阵
    MatGF256(const MatGF256 &src, size_t begin_ri, size_t begin_wi, size_t end_rj, size_t end_wj) : nrows(end_rj - begin_ri), ncols((end_wj == src.width ? src.ncols : end_wj * gf256_num) - begin_wi * gf256_num), width(end_wj - begin_wi), rowstride(src.rowstride), type(window), data(src.at_base(begin_ri, begin_wi))
    {
        assert(begin_ri < end_rj && end_rj <= src.nrows && begin_wi < end_wj && end_wj <= src.width);
    }
    // 只能拷贝构造root矩阵
    MatGF256(const MatGF256 &m) : MatGF256(m.nrows, m.ncols)
    {
        CUDA_CHECK(cudaMemcpy2D(data, rowstride * sizeof(base_t), m.data, m.rowstride * sizeof(base_t), m.width * sizeof(base_t), nrows, cudaMemcpyDefault));
    }
    MatGF256(MatGF256 &&m) noexcept : nrows(m.nrows), ncols(m.ncols), width(m.width), rowstride(m.rowstride), type(m.type), data(m.data)
    {
        m.type = moved;
        m.data = nullptr;
    }
    MatGF256 &operator=(const MatGF256 &m)
    {
        if (this == &m)
        {
            return *this;
        }
        assert(nrows == m.nrows && ncols == m.ncols);
        CUDA_CHECK(cudaMemcpy2D(data, rowstride * sizeof(base_t), m.data, m.rowstride * sizeof(base_t), m.width * sizeof(base_t), nrows, cudaMemcpyDefault));
        return *this;
    }
    MatGF256 &operator=(MatGF256 &&m) noexcept
    {
        if (this == &m)
        {
            return *this;
        }
        if (type == root)
        {
            CUDA_CHECK(cudaFree(data));
        }
        nrows = m.nrows;
        ncols = m.ncols;
        width = m.width;
        rowstride = m.rowstride;
        type = m.type;
        data = m.data;
        m.type = moved;
        m.data = nullptr;
        return *this;
    }

    ~MatGF256()
    {
        if (type == root)
        {
            CUDA_CHECK(cudaFree(data));
        }
    }

    inline base_t *at_base(size_t r, size_t w) const
    {
        return data + r * rowstride + w;
    }

    void randomize(uint_fast32_t seed)
    {
        assert(type == root);
        static default_random_engine e(seed);
        static uniform_int_distribution<base_t> d;
        base_t lastmask = base_fullmask >> (width * base_len - ncols * gf256_len);
        for (size_t r = 0; r < nrows; r++)
        {
            for (size_t w = 0; w < width; w++)
            {
                *at_base(r, w) = d(e);
            }
            *at_base(r, width - 1) &= lastmask;
        }
    }

    // 生成随机最简化行阶梯矩阵 前rank_col中选择nrows个主元列
    void randomize(size_t rank_col, uint_fast32_t seed)
    {
        assert(nrows <= rank_col && rank_col <= ncols);
        randomize(seed);
        vector<size_t> pivot(rank_col);
        iota(pivot.begin(), pivot.end(), 0);
        random_shuffle(pivot.begin(), pivot.end());
        pivot.resize(nrows);
        sort(pivot.begin(), pivot.end());

        vector<base_t> pivotmask(width, base_fullmask);
        for (size_t r = 0; r < nrows; r++)
        {
            del8(pivotmask[pivot[r] / gf256_num], pivot[r] % gf256_num);
        }

        for (size_t r = 0; r < nrows; r++)
        {
            for (size_t w = 0; w < pivot[r] / gf256_num; w++)
            {
                *at_base(r, w) = base_zero;
            }
            base_t *now = at_base(r, pivot[r] / gf256_num);
            *now = concat8(base_zero, pivot[r] % gf256_num + 1, *now & pivotmask[pivot[r] / gf256_num]);
            set8(*now, gf256_one, pivot[r] % gf256_num);
            for (size_t w = pivot[r] / gf256_num + 1; w < rank_col / gf256_num + 1; w++)
            {
                *at_base(r, w) &= pivotmask[w];
            }
        }
    }

    bool operator==(const MatGF256 &m) const
    {
        if (nrows != m.nrows || ncols != m.ncols)
        {
            return false;
        }
        for (size_t r = 0; r < nrows; r++)
        {
            for (size_t w = 0; w < width; w++)
            {
                if (*at_base(r, w) != *m.at_base(r, w))
                {
                    return false;
                }
            }
        }
        return true;
    }

    bool operator==(const base_t base) const
    {
        for (size_t r = 0; r < nrows; r++)
        {
            for (size_t w = 0; w < width; w++)
            {
                if (*at_base(r, w) != base)
                {
                    return false;
                }
            }
        }
        return true;
    }
    void operator^=(const MatGF256 &m)
    {
        assert(nrows == m.nrows && ncols == m.ncols);
        for (size_t r = 0; r < nrows; r++)
        {
            for (size_t w = 0; w < width; w++)
            {
                *at_base(r, w) ^= *m.at_base(r, w);
            }
        }
    }
    MatGF256 operator^(const MatGF256 &m) const
    {
        MatGF256 temp(*this);
        temp ^= m;
        return temp;
    }

    void gpu_addmul(const MatGF256 &a, const MatGF256 &b, const GF256 &gf);
    friend MatGF256 gpu_mul(const MatGF256 &a, const MatGF256 &b, const GF256 &gf);

    // size_t cpu_elim_base(base_t *base_col, size_t st_r, size_t w, vector<size_t> &p_col, vector<size_t> &p_row, base_t step[gf256_num], const GF256 &gf);
    void cpu_swap_row(size_t r1, size_t r2);
    // void cpu_mul_row(size_t r, gf256_t val, const GF256 &gf);
    ElimResult gpu_elim(const GF256 &gf);

    friend ostream &operator<<(ostream &out, const MatGF256 &m);

    size_t nrows, ncols, width;

private:
    MatGF256() : nrows(0), ncols(0), width(0), rowstride(0), type(moved), data(nullptr) {}

    size_t rowstride;
    MatType type;
    base_t *data;
};

ostream &operator<<(ostream &out, const MatGF256 &m)
{
    for (size_t r = 0; r < m.nrows; r++)
    {
        for (size_t w = 0; w < m.width; w++)
        {
            printf("%016lX ", rev8(*m.at_base(r, w)));
        }
        printf("\n");
    }
    return out;
}

#endif