libflame
revision_anchor
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Functions | |
FLA_Error | FLA_Bidiag_UT_create_T (FLA_Obj A, FLA_Obj *TU, FLA_Obj *TV) |
FLA_Error FLA_Bidiag_UT_create_T | ( | FLA_Obj | A, |
FLA_Obj * | TU, | ||
FLA_Obj * | TV | ||
) |
References FLA_Obj_create(), FLA_Obj_datatype(), FLA_Obj_min_dim(), FLA_Obj_row_stride(), and FLA_Query_blocksize().
Referenced by FLA_Svd_ext_u_unb_var1(), FLA_Svd_uv_unb_var1(), and FLA_Svd_uv_unb_var2().
{ FLA_Datatype datatype; dim_t b_alg, k; dim_t rs_T, cs_T; // Query the datatype of A. datatype = FLA_Obj_datatype( A ); // Query the blocksize from the library. b_alg = FLA_Query_blocksize( datatype, FLA_DIMENSION_MIN ); // Scale the blocksize by a pre-set global constant. b_alg = ( dim_t )( ( ( double ) b_alg ) * FLA_BIDIAG_INNER_TO_OUTER_B_RATIO ); // Query the minimum dimension of A. k = FLA_Obj_min_dim( A ); b_alg = 5; // Adjust the blocksize with respect to the min-dim of A. b_alg = min( b_alg, k ); // Figure out whether TU and TV should be row-major or column-major. if ( FLA_Obj_row_stride( A ) == 1 ) { rs_T = 1; cs_T = b_alg; } else // if ( FLA_Obj_col_stride( A ) == 1 ) { rs_T = k; cs_T = 1; } // Create two b_alg x k matrices to hold the block Householder transforms // that will be accumulated within the bidiagonal reduction algorithm. // If the matrix dimension has a zero dimension, apply_q complains it. if ( TU != NULL ) FLA_Obj_create( datatype, b_alg, k, rs_T, cs_T, TU ); if ( TV != NULL ) FLA_Obj_create( datatype, b_alg, k, rs_T, cs_T, TV ); return FLA_SUCCESS; }