pposv
The pposv solver supports the following input types.
- data type: DSZC
- index type:
std::int32_t,std::int64_t
pposv solves a square symmetric positive definite system A * X = B using Cholesky decomposition.
The matrix A of size \(N\) is stored in a memory block of size \(N^2\).
Constructor
The solver takes four template arguments.
- data type, e.g.,
double,float,std::complex<double>,std::complex<float>; - index type, e.g.,
std::int32_t,std::int64_t; - symmetry flag,
UorL; - process grid order,
RorC.
The solver uses a 2D process grid.
The grid order can be either Row major or Column major.
The symmetry flag indicates whether the Upper or Lower triangle of the matrix is stored.
If only half of the matrix is populated, this flag must be set properly.
If the whole symmetric matrix is populated, either value works.
With np_row and np_col denoting the numbers of rows and columns of the process grid, a solver is constructed as follows.
The library can also determine the grid dimensions automatically.
Solving
Prepare matrices \(A\) and \(B\) on the root process in whatever form is convenient.
The two matrices must be wrapped into template<data_t DT, index_t IT> struct full_mat objects, which require
- the number of rows of the matrix,
n_rows; - the number of columns of the matrix,
n_cols; - a pointer to the data,
data.
Then call the solver.
The factorization is stored internally as long as the solver object stays alive. A second solve reuses the stored factorization.
Calling solve(full_mat<DT, IT>&& A, full_mat<DT, IT>&& B) again clears the previous factorization automatically.
On return, B is replaced by the solution.
In the example above, std::vector<double> B then contains the solution.