/* -*- mode: C++; tab-width: 8; indent-tabs-mode: t; c-basic-offset: 8 -*- */
// vim:sts=8:sw=8:ts=8:noet:sr:cino=>s,f0,{0,g0,(0,\:0,t0,+0,=s
/*
 * Copyright (C) 2014 the FFLAS-FFPACK group
 *
 * Written by   Bastien Vialla <bastien.vialla@lirmm.fr>
 *
 *
 * ========LICENCE========
 * This file is part of the library FFLAS-FFPACK.
 *
 * FFLAS-FFPACK is free software: you can redistribute it and/or modify
 * it under the terms of the  GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301 USA
 * ========LICENCE========
 *.
 */

#ifndef __FFLASFFPACK_fflas_sparse_sell_pspmv_INL
#define __FFLASFFPACK_fflas_sparse_sell_pspmv_INL

#ifdef __FFLASFFPACK_USE_TBB
#include "tbb/parallel_for.h"
#include "tbb/blocked_range.h"
#endif

namespace FFLAS {
namespace sparse_details_impl {
template <class Field>
inline void pfspmv(const Field &F, const Sparse<Field, SparseMatrix_t::SELL> &A, typename Field::ConstElement_ptr x_,
                   typename Field::Element_ptr y_, FieldCategories::GenericTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(dat, A.dat, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, col, st, dat, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            index_t j = 0;
            for (; j < size; j++) {
                for (index_t k = 0; k < A.chunk; ++k) {
                    F.axpyin(y[i * A.chunk + k], dat[start + j * A.chunk + k], x[col[start + j * A.chunk + k]]);
                }
            }
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        index_t j = 0;
        for (; j < size; j++) {
            for (index_t k = 0; k < A.chunk; ++k) {
                F.axpyin(y[i * A.chunk + k], dat[start + j * A.chunk + k], x[col[start + j * A.chunk + k]]);
            }
        }
    }
#endif
}

#ifdef __FFLASFFPACK_HAVE_SSE4_1_INSTRUCTIONS

template <class Field>
inline void pfspmv_simd(const Field &F, const Sparse<Field, SparseMatrix_t::SELL> &A,
                        typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                        FieldCategories::UnparametricTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(dat, A.dat, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
    using simd = Simd<typename Field::Element>;
    using vect_t = typename simd::vect_t;
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, dat, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            vect_t x1, x2, y1, y2, dat1, dat2;
            y1 = simd::zero();
            y2 = simd::zero();
            index_t j = 0;
            for (; j < ROUND_DOWN(size, 2); j += 2) {
                dat1 = simd::load(dat + start + j * A.chunk);
                dat2 = simd::load(dat + start + (j + 1) * A.chunk);
                x1 = simd::gather(x, col + start + j * A.chunk);
                x2 = simd::gather(x, col + start + (j + 1) * A.chunk);
                y1 = simd::fmadd(y1, dat1, x1);
                y2 = simd::fmadd(y2, dat2, x2);
            }
            if (size % 2 != 0) {
                dat1 = simd::load(dat + start + j * A.chunk);
                x1 = simd::gather(x, col + start + j * A.chunk);
                y1 = simd::fmadd(y1, dat1, x1);
            }
            simd::store(y + i * A.chunk, simd::add(simd::load(y + i * A.chunk), simd::add(y1, y2)));
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        vect_t x1, x2, y1, y2, dat1, dat2;
        y1 = simd::zero();
        y2 = simd::zero();
        index_t j = 0;
        for (; j < ROUND_DOWN(size, 2); j += 2) {
            dat1 = simd::load(dat + start + j * A.chunk);
            dat2 = simd::load(dat + start + (j + 1) * A.chunk);
            x1 = simd::gather(x, col + start + j * A.chunk);
            x2 = simd::gather(x, col + start + (j + 1) * A.chunk);
            y1 = simd::fmadd(y1, dat1, x1);
            y2 = simd::fmadd(y2, dat2, x2);
        }
        if (size % 2 != 0) {
            dat1 = simd::load(dat + start + j * A.chunk);
            x1 = simd::gather(x, col + start + j * A.chunk);
            y1 = simd::fmadd(y1, dat1, x1);
        }
        simd::store(y + i * A.chunk, simd::add(simd::load(y + i * A.chunk), simd::add(y1, y2)));
    }
#endif // TBB
}

#endif // SIMD

template <class Field>
inline void pfspmv(const Field &F, const Sparse<Field, SparseMatrix_t::SELL> &A, typename Field::ConstElement_ptr x_,
                   typename Field::Element_ptr y_, FieldCategories::UnparametricTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(dat, A.dat, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, dat, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            for (index_t j = 0; j < size; ++j) {
                size_t k = 0;
                for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                    y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                    y[i * A.chunk + k + 1] += dat[start + j * A.chunk + k + 1] * x[col[start + j * A.chunk + k + 1]];
                    y[i * A.chunk + k + 2] += dat[start + j * A.chunk + k + 2] * x[col[start + j * A.chunk + k + 2]];
                    y[i * A.chunk + k + 3] += dat[start + j * A.chunk + k + 3] * x[col[start + j * A.chunk + k + 3]];
                }
                for (; k < size; ++k) {
                    y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                }
            }
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        for (index_t j = 0; j < size; ++j) {
            size_t k = 0;
            for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                y[i * A.chunk + k + 1] += dat[start + j * A.chunk + k + 1] * x[col[start + j * A.chunk + k + 1]];
                y[i * A.chunk + k + 2] += dat[start + j * A.chunk + k + 2] * x[col[start + j * A.chunk + k + 2]];
                y[i * A.chunk + k + 3] += dat[start + j * A.chunk + k + 3] * x[col[start + j * A.chunk + k + 3]];
            }
            for (; k < size; ++k) {
                y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
            }
        }
    }
#endif // TBB
}

#ifdef __FFLASFFPACK_HAVE_SSE4_1_INSTRUCTIONS
template <class Field>
inline void pfspmv_simd(const Field &F, const Sparse<Field, SparseMatrix_t::SELL> &A,
                        typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_, const int64_t kmax) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(dat, A.dat, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
    index_t chunk = A.chunk;
    using simd = Simd<typename Field::Element>;
    using vect_t = typename simd::vect_t;

    vect_t X, Y, D, C, Q, TMP, NEGP, INVP, MIN, MAX, P;
    double p = (typename Field::Element)F.characteristic();

    P = simd::set1(p);
    NEGP = simd::set1(-p);
    INVP = simd::set1(1 / p);
    MIN = simd::set1(F.minElement());
    MAX = simd::set1(F.maxElement());

#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, dat, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t j = 0;
            index_t j_loc = 0;
            Y = simd::load(y + i * A.chunk);
            index_t size = chunkSize[i];
            index_t start = st[i];
            index_t block = size / kmax;
            for (size_t l = 0; l < block; ++l) {
                j_loc += kmax;
                for (; j < j_loc; ++j) {
                    D = simd::load(dat + start + j * A.chunk);
                    X = simd::gather(x, col + start + j * A.chunk);
                    Y = simd::fmadd(Y, D, X);
                }
                simd::mod(Y, P, INVP, NEGP, MIN, MAX, Q, TMP);
            }
            for (; j < size; ++j) {
                D = simd::load(dat + start + j * A.chunk);
                X = simd::gather(x, col + start + j * A.chunk);
                Y = simd::fmadd(Y, D, X);
            }
            simd::mod(Y, P, INVP, NEGP, MIN, MAX, Q, TMP);
            simd::store(y + i * A.chunk, Y);
        }
    });
#else
#pragma omp parallel for
    for (size_t i = 0; i < A.nChunks; ++i) {
        index_t j = 0;
        index_t j_loc = 0;
        Y = simd::load(y + i * A.chunk);
        index_t size = chunkSize[i];
        index_t start = st[i];
        index_t block = size / kmax;
        for (size_t l = 0; l < block; ++l) {
            j_loc += kmax;
            for (; j < j_loc; ++j) {
                D = simd::load(dat + start + j * A.chunk);
                X = simd::gather(x, col + start + j * A.chunk);
                Y = simd::fmadd(Y, D, X);
            }
            simd::mod(Y, P, INVP, NEGP, MIN, MAX, Q, TMP);
        }
        for (; j < size; ++j) {
            D = simd::load(dat + start + j * A.chunk);
            X = simd::gather(x, col + start + j * A.chunk);
            Y = simd::fmadd(Y, D, X);
        }
        simd::mod(Y, P, INVP, NEGP, MIN, MAX, Q, TMP);
        simd::store(y + i * A.chunk, Y);
    }
#endif // TBB
}

#endif // SIMD

template <class Field>
inline void pfspmv(const Field &F, const Sparse<Field, SparseMatrix_t::SELL> &A, typename Field::ConstElement_ptr x_,
                   typename Field::Element_ptr y_, const int64_t kmax) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(dat, A.dat, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
    index_t chunk = A.chunk;
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, &x, &y, st, col, dat, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t j = 0;
            index_t j_loc = 0;
            index_t size = chunkSize[i];
            index_t start = st[i];
            index_t block = size / kmax;
            for (size_t l = 0; l < block; ++l) {
                j_loc += kmax;
                for (; j < j_loc; ++j) {
                    size_t k = 0;
                    for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                        y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                        y[i * A.chunk + k + 1] +=
                            dat[start + j * A.chunk + k + 1] * x[col[start + j * A.chunk + k + 1]];
                        y[i * A.chunk + k + 2] +=
                            dat[start + j * A.chunk + k + 2] * x[col[start + j * A.chunk + k + 2]];
                        y[i * A.chunk + k + 3] +=
                            dat[start + j * A.chunk + k + 3] * x[col[start + j * A.chunk + k + 3]];
                    }
                    for (; k < size; ++k) {
                        y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                    }
                }
                for (size_t k = 0; k < size; ++k) {
                    F.reduce(y[i * A.chunk + k]);
                }
            }
            for (; j < size; ++j) {
                size_t k = 0;
                for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                    y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                    y[i * A.chunk + k + 1] += dat[start + j * A.chunk + k + 1] * x[col[start + j * A.chunk + k + 1]];
                    y[i * A.chunk + k + 2] += dat[start + j * A.chunk + k + 2] * x[col[start + j * A.chunk + k + 2]];
                    y[i * A.chunk + k + 3] += dat[start + j * A.chunk + k + 3] * x[col[start + j * A.chunk + k + 3]];
                }
                for (; k < size; ++k) {
                    y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                }
            }
            for (size_t k = 0; k < size; ++k) {
                F.reduce(y[i * A.chunk + k]);
            }
        }
    });

#else
#pragma omp parallel for
    for (size_t i = 0; i < A.nChunks; ++i) {
        index_t j = 0;
        index_t j_loc = 0;
        index_t size = chunkSize[i];
        index_t start = st[i];
        index_t block = size / kmax;
        for (size_t l = 0; l < block; ++l) {
            j_loc += kmax;
            for (; j < j_loc; ++j) {
                size_t k = 0;
                for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                    y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                    y[i * A.chunk + k + 1] += dat[start + j * A.chunk + k + 1] * x[col[start + j * A.chunk + k + 1]];
                    y[i * A.chunk + k + 2] += dat[start + j * A.chunk + k + 2] * x[col[start + j * A.chunk + k + 2]];
                    y[i * A.chunk + k + 3] += dat[start + j * A.chunk + k + 3] * x[col[start + j * A.chunk + k + 3]];
                }
                for (; k < size; ++k) {
                    y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                }
            }
            for (size_t k = 0; k < size; ++k) {
                F.reduce(y[i * A.chunk + k]);
            }
        }
        for (; j < size; ++j) {
            size_t k = 0;
            for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
                y[i * A.chunk + k + 1] += dat[start + j * A.chunk + k + 1] * x[col[start + j * A.chunk + k + 1]];
                y[i * A.chunk + k + 2] += dat[start + j * A.chunk + k + 2] * x[col[start + j * A.chunk + k + 2]];
                y[i * A.chunk + k + 3] += dat[start + j * A.chunk + k + 3] * x[col[start + j * A.chunk + k + 3]];
            }
            for (; k < size; ++k) {
                y[i * A.chunk + k] += dat[start + j * A.chunk + k] * x[col[start + j * A.chunk + k]];
            }
        }
        for (size_t k = 0; k < size; ++k) {
            F.reduce(y[i * A.chunk + k]);
        }
    }
#endif // TBB
}

template <class Field>
inline void pfspmv_one(const Field &F, const Sparse<Field, SparseMatrix_t::SELL_ZO> &A,
                       typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                       FieldCategories::GenericTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            index_t j = 0;
            for (; j < size; j++) {
                for (index_t k = 0; k < A.chunk; ++k) {
                    F.addin(y[i * A.chunk + k], x[col[start + j * A.chunk + k]]);
                }
            }
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        index_t j = 0;
        for (; j < size; j++) {
            for (index_t k = 0; k < A.chunk; ++k) {
                F.addin(y[i * A.chunk + k], x[col[start + j * A.chunk + k]]);
            }
        }
    }
#endif
}

template <class Field>
inline void pfspmv_mone(const Field &F, const Sparse<Field, SparseMatrix_t::SELL_ZO> &A,
                        typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                        FieldCategories::GenericTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            index_t j = 0;
            for (; j < size; j++) {
                for (index_t k = 0; k < A.chunk; ++k) {
                    F.subin(y[i * A.chunk + k], x[col[start + j * A.chunk + k]]);
                }
            }
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        index_t j = 0;
        for (; j < size; j++) {
            for (index_t k = 0; k < A.chunk; ++k) {
                F.subin(y[i * A.chunk + k], x[col[start + j * A.chunk + k]]);
            }
        }
    }
#endif
}

#ifdef __FFLASFFPACK_HAVE_SSE4_1_INSTRUCTIONS

template <class Field>
inline void pfspmv_one_simd(const Field &F, const Sparse<Field, SparseMatrix_t::SELL_ZO> &A,
                            typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                            FieldCategories::UnparametricTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
    using simd = Simd<typename Field::Element>;
    using vect_t = typename simd::vect_t;
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            vect_t x1, x2, y1, y2;
            y1 = simd::zero();
            y2 = simd::zero();
            index_t j = 0;
            for (; j < ROUND_DOWN(size, 2); j += 2) {
                x1 = simd::gather(x, col + start + j * A.chunk);
                x2 = simd::gather(x, col + start + (j + 1) * A.chunk);
                y1 = simd::add(y1, x1);
                y2 = simd::add(y2, x2);
            }
            if (size % 2 != 0) {
                x1 = simd::gather(x, col + start + j * A.chunk);
                y1 = simd::add(y1, x1);
            }
            simd::store(y + i * A.chunk, simd::add(simd::load(y + i * A.chunk), simd::add(y1, y2)));
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        vect_t x1, x2, y1, y2;
        y1 = simd::zero();
        y2 = simd::zero();
        index_t j = 0;
        for (; j < ROUND_DOWN(size, 2); j += 2) {
            x1 = simd::gather(x, col + start + j * A.chunk);
            x2 = simd::gather(x, col + start + (j + 1) * A.chunk);
            y1 = simd::add(y1, x1);
            y2 = simd::add(y2, x2);
        }
        if (size % 2 != 0) {
            x1 = simd::gather(x, col + start + j * A.chunk);
            y1 = simd::add(y1, x1);
        }
        simd::store(y + i * A.chunk, simd::add(simd::load(y + i * A.chunk), simd::add(y1, y2)));
    }
#endif // TBB
}

template <class Field>
inline void pfspmv_mone_simd(const Field &F, const Sparse<Field, SparseMatrix_t::SELL_ZO> &A,
                             typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                             FieldCategories::UnparametricTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
    using simd = Simd<typename Field::Element>;
    using vect_t = typename simd::vect_t;
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            vect_t x1, x2, y1, y2;
            y1 = simd::zero();
            y2 = simd::zero();
            index_t j = 0;
            for (; j < ROUND_DOWN(size, 2); j += 2) {
                x1 = simd::gather(x, col + start + j * A.chunk);
                x2 = simd::gather(x, col + start + (j + 1) * A.chunk);
                y1 = simd::add(y1, x1);
                y2 = simd::add(y2, x2);
            }
            if (size % 2 != 0) {
                x1 = simd::gather(x, col + start + j * A.chunk);
                y1 = simd::add(y1, x1);
            }
            simd::store(y + i * A.chunk, simd::sub(simd::load(y + i * A.chunk), simd::add(y1, y2)));
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        vect_t x1, x2, y1, y2;
        y1 = simd::zero();
        y2 = simd::zero();
        index_t j = 0;
        for (; j < ROUND_DOWN(size, 2); j += 2) {
            x1 = simd::gather(x, col + start + j * A.chunk);
            x2 = simd::gather(x, col + start + (j + 1) * A.chunk);
            y1 = simd::add(y1, x1);
            y2 = simd::add(y2, x2);
        }
        if (size % 2 != 0) {
            x1 = simd::gather(x, col + start + j * A.chunk);
            y1 = simd::add(y1, x1);
        }
        simd::store(y + i * A.chunk, simd::sub(simd::load(y + i * A.chunk), simd::add(y1, y2)));
    }
#endif // TBB
}

#endif // SIMD

template <class Field>
inline void pfspmv_one(const Field &F, const Sparse<Field, SparseMatrix_t::SELL_ZO> &A,
                       typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                       FieldCategories::UnparametricTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            for (index_t j = 0; j < size; j++) {
                size_t k = 0;
                for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                    y[i * A.chunk + k] += x[col[start + j * A.chunk + k]];
                    y[i * A.chunk + k + 1] += x[col[start + j * A.chunk + k + 1]];
                    y[i * A.chunk + k + 2] += x[col[start + j * A.chunk + k + 2]];
                    y[i * A.chunk + k + 3] += x[col[start + j * A.chunk + k + 3]];
                }
                for (; k < size; ++k) {
                    y[i * A.chunk + k] += x[col[start + j * A.chunk + k]];
                }
            }
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        for (index_t j = 0; j < size; j++) {
            size_t k = 0;
            for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                y[i * A.chunk + k] += x[col[start + j * A.chunk + k]];
                y[i * A.chunk + k + 1] += x[col[start + j * A.chunk + k + 1]];
                y[i * A.chunk + k + 2] += x[col[start + j * A.chunk + k + 2]];
                y[i * A.chunk + k + 3] += x[col[start + j * A.chunk + k + 3]];
            }
            for (; k < size; ++k) {
                y[i * A.chunk + k] += x[col[start + j * A.chunk + k]];
            }
        }
    }
#endif // TBB
}

template <class Field>
inline void pfspmv_mone(const Field &F, const Sparse<Field, SparseMatrix_t::SELL_ZO> &A,
                        typename Field::ConstElement_ptr x_, typename Field::Element_ptr y_,
                        FieldCategories::UnparametricTag) {
    assume_aligned(st, A.st, (size_t)Alignment::CACHE_LINE);
    assume_aligned(chunkSize, A.chunkSize, (size_t)Alignment::CACHE_LINE);
    assume_aligned(col, A.col, (size_t)Alignment::CACHE_LINE);
    assume_aligned(x, x_, (size_t)Alignment::DEFAULT);
    assume_aligned(y, y_, (size_t)Alignment::DEFAULT);
#ifdef __FFLASFFPACK_USE_TBB
    tbb::parallel_for(tbb::blocked_range<index_t>(0, A.nbChunks, 2),
                      [&F, &A, x, y, st, col, chunkSize](const tbb::blocked_range<index_t> &r) {
        for (index_t i = r.begin(), end = r.end(); i < end; ++i) {
            index_t start = st[i];
            index_t size = chunkSize[i];
            for (index_t j = 0; j < size; j++) {
                size_t k = 0;
                for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                    y[i * A.chunk + k] -= x[col[start + j * A.chunk + k]];
                    y[i * A.chunk + k + 1] -= x[col[start + j * A.chunk + k + 1]];
                    y[i * A.chunk + k + 2] -= x[col[start + j * A.chunk + k + 2]];
                    y[i * A.chunk + k + 3] -= x[col[start + j * A.chunk + k + 3]];
                }
                for (; k < size; ++k) {
                    y[i * A.chunk + k] -= x[col[start + j * A.chunk + k]];
                }
            }
        }
    });
#else
#pragma omp parallel for
    for (index_t i = 0; i < A.nChunks; ++i) {
        index_t start = st[i];
        index_t size = chunkSize[i];
        for (index_t j = 0; j < size; j++) {
            size_t k = 0;
            for (; k < ROUND_DOWN(A.chunk, 4); k += 4) {
                y[i * A.chunk + k] -= x[col[start + j * A.chunk + k]];
                y[i * A.chunk + k + 1] -= x[col[start + j * A.chunk + k + 1]];
                y[i * A.chunk + k + 2] -= x[col[start + j * A.chunk + k + 2]];
                y[i * A.chunk + k + 3] -= x[col[start + j * A.chunk + k + 3]];
            }
            for (; k < size; ++k) {
                y[i * A.chunk + k] -= x[col[start + j * A.chunk + k]];
            }
        }
    }
#endif // TBB
}

} // SELL_details

} // FFLAS

#endif //  __FFLASFFPACK_fflas_SELL_spmv_INL