Cholesky factorization factors an , symmetric, positive-definite matrix into the product of a lower triangular matrix and its transpose, i.e., (or , where is upper triangular). It is assumed that the lower triangular portion of is stored in the lower triangle of a two-dimensional array and that the computed elements of overwrite the given elements of . At the -th step, we partition the matrices , , and , and write the system as
where the block is , is , and is . and are lower triangular.
The block-partitioned form of Cholesky factorization may be inferred inductively as follows. If we assume that , the lower triangular Cholesky factor of , is known, we can rearrange the block equations,
A snapshot of the block Cholesky factorization algorithm in Figure 5 shows how the column panel ( and ) is computed and how the trailing submatrix is updated. The factorization can be done by recursively applying the steps outlined above to the matrix .
Figure 5: A snapshot of block Cholesky factorization.
In the right-looking version of the LAPACK routine, the computation of the above steps involves the following operations:
The parallel implementation of the corresponding ScaLAPACK routine, PDPOTRF, proceeds as follows: