ppbsv

The ppbsv solver supports the following input types.

• data type: DSZC
• index type: std::int32_t, std::int64_t

The ppbsv solves a square real banded symmetric positive definite distributed matrix with bandwidth \(KLU\) using Cholesky factorization. The matrix of size \(N\) is stored in a memory block of size \(N \times (KLU+1)\).

Constructor

There are three template arguments.

1. data type, e.g., double, float, std::complex<double>, std::complex<float>.
2. index type, e.g., std::int32_t, std::int64_t.
3. UPLO flag indicating which triangular half is stored, U (upper) or L (lower).

This solver uses a 1D process grid. It takes a single argument that represents the number of rows in the grid.

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auto solver = ppbsv<double, int, 'U'>(np_row);

Since the matrix is symmetric, ScaLAPACK expects only half of the matrix. Thus the caller must provide the matrix exactly stored in a contiguous memory block of size \(N \times (KLU+1)\). For different UPLO flags, the internal storage layout varies.

Indexer

A nested indexer converts logical 2D indices \((i, j)\) into the correct 1D offset for the symmetric band storage layout, respecting the UPLO flag.

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const auto IDX = par_dpbsv<int>::indexer{N, KLU};
A.resize(N * (KLU + 1), 0.);
for(auto I = 0; I < N; ++I) A[IDX(I, I)] = I + 1;

Solving

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constexpr auto N = 6, NRHS = 2, KLU = 2;
// storage for the matrices A and B
std::vector<double> A, B;
// ...
// ... storage is populated by some utility on the root process
// ...
const auto info = solver.solve({N, N, KLU, A.data()}, {N, NRHS, B.data()});