getrf_recursive.hpp

Go to the documentation of this file.

 
//
// Copyright (c) 2025, University of Colorado Denver. All rights reserved.
//
// This file is part of <T>LAPACK.
// <T>LAPACK is free software: you can redistribute it and/or modify it under
// the terms of the BSD 3-Clause license. See the accompanying LICENSE file.
 
#ifndef TLAPACK_GETRF_RECURSIVE_HH
#define TLAPACK_GETRF_RECURSIVE_HH
 
#include "tlapack/base/utils.hpp"
#include "tlapack/blas/gemm.hpp"
#include "tlapack/blas/iamax.hpp"
#include "tlapack/blas/swap.hpp"
#include "tlapack/blas/trsm.hpp"
#include "tlapack/lapack/rscl.hpp"
 
namespace tlapack {
 
template <TLAPACK_SMATRIX matrix_t, TLAPACK_SVECTOR piv_t>
int getrf_recursive(matrix_t& A, piv_t& piv)
{
    using idx_t = size_type<matrix_t>;
    using T = type_t<matrix_t>;
    using real_t = real_type<T>;
    using range = pair<idx_t, idx_t>;
 
    // Using the following lines to pass the abs function to iamax
    IamaxOpts optsIamax([](const T& x) -> real_t { return abs(x); });
 
    // constants
    const idx_t m = nrows(A);
    const idx_t n = ncols(A);
    const idx_t k = min(m, n);
 
    // check arguments
    tlapack_check((idx_t)size(piv) >= k);
 
    // quick return
    if (m <= 0 || n <= 0) return 0;
 
    // base case of recursion; one column matrices or one row matrices
    // one-row matrices
    if (m == 1) {
        // piv has one element
        piv[0] = idx_t(0);
        if (A(piv[0], 0) == real_t(0)) {
            // in case which A(0,0) is zero, then we return 1 since in the first
            // iteration we stopped
            return 1;
        }
 
        return 0;
    }
 
    // one-column matrices
    else if (n == 1) {
        // when n==1, piv has one element, piv[0] needs to be swapped by the
        // first row
        piv[0] = iamax(col(A, 0), optsIamax);
 
        // in the following case all elements are zero, and we return 1
        if (A(piv[0], 0) == real_t(0)) return 1;
 
        // in this case, we can safely swap since A(piv[0],0) is not zero
        if (piv[0] != 0) {
            const T aux = A(piv[0], 0);
            A(piv[0], 0) = A(0, 0);
            A(0, 0) = aux;
        }
 
        // by the previous comment, we can safely scale all elements of 0th
        // column by 1/A(0,0)
        auto l = slice(A, range(1, m), 0);
        rscl((T)A(0, 0), l);
 
        return 0;
    }
 
    // the case where m<n, we simply slice A into two parts, A0, a square matrix
    // and A1 where A=[A0 , A1]
    else if (m < n) {
        auto A0 = tlapack::cols(A, range(0, m));
        auto A1 = tlapack::cols(A, range(m, n));
 
        int info = getrf_recursive(A0, piv);
        if (info != 0) return info;
 
        // swap the rows of A1 according to piv
        for (idx_t j = 0; j < k; j++) {
            if ((idx_t)piv[j] != j) {
                auto vect1 = tlapack::row(A1, j);
                auto vect2 = tlapack::row(A1, piv[j]);
                tlapack::swap(vect1, vect2);
            }
        }
 
        // Solve triangular system A0 X = A1 and update A1
        trsm(LEFT_SIDE, LOWER_TRIANGLE, NO_TRANS, UNIT_DIAG, T(1), A0, A1);
 
        return 0;
    }
    else {
        // Dimensions for the submatrices
        idx_t k0 = k / 2;
 
        // in this step, we break A into two matrices, A=[A0 , A1]
        auto A0 = tlapack::cols(A, range(0, k0));
        auto A1 = tlapack::cols(A, range(k0, n));
 
        // piv0 is the first k0 elements of piv
        auto piv0 = tlapack::slice(piv, range(0, k0));
 
        // Apply getrf on the left of half of the matrix
        int info = getrf_recursive(A0, piv0);
        if (info != 0) return info;
 
        // swap the rows of A1
        for (idx_t j = 0; j < k0; j++) {
            if ((idx_t)piv0[j] != j) {
                auto vect1 = tlapack::row(A1, j);
                auto vect2 = tlapack::row(A1, piv0[j]);
                tlapack::swap(vect1, vect2);
            }
        }
 
        // partition A into the following four blocks:
        auto A00 = tlapack::slice(A, range(0, k0), range(0, k0));
        auto A01 = tlapack::slice(A, range(0, k0), range(k0, n));
        auto A10 = tlapack::slice(A, range(k0, m), range(0, k0));
        auto A11 = tlapack::slice(A, range(k0, m), range(k0, n));
 
        // Take piv1 to be the second slice of of piv, meaning piv= [piv0, piv1]
        auto piv1 = tlapack::slice(piv, range(k0, k));
 
        // Solve the triangular system of equations given by A00 X = A01
        trsm(LEFT_SIDE, LOWER_TRIANGLE, NO_TRANS, UNIT_DIAG, T(1), A00, A01);
 
        // A11 <---- A11 - (A10 * A01)
        gemm(NO_TRANS, NO_TRANS, real_t(-1), A10, A01, real_t(1), A11);
 
        // Finding LU factorization of A11 in place
        info = getrf_recursive(A11, piv1);
        if (info != 0) return info + k0;
 
        // swap the rows of A10 according to the swapped rows of A11 by refering
        // to piv1
        for (idx_t j = 0; j < k - k0; j++) {
            if ((idx_t)piv1[j] != j) {
                auto vect1 = tlapack::row(A10, j);
                auto vect2 = tlapack::row(A10, piv1[j]);
                tlapack::swap(vect1, vect2);
            }
        }
 
        // Shift piv1, so piv will have the accurate representation of overall
        // pivots
        for (idx_t i = 0; i < k - k0; i++) {
            piv1[i] += k0;
        }
 
        return 0;
    }
 
}  // getrf_recursive
int getrf_recursive(matrix_t& A, piv_t& piv) {…}
 
}  // namespace tlapack
 
#endif  // TLAPACK_GETRF_RECURSIVE_HH