Lessons learned from restructuring a hydraulic solver for parallel computing

Hydraulic network software has to solve a set of linear equations repeatedly in an iterative process making them computationally intensive for large systems. The objective of this study was to restructure the Porteau hydraulic freeware by using parallel computational techniques. The method used consists of comparing two linear solver algorithms, a direct Cholesky kind method with nested dissection renumbering and an indirect preconditioned Conjugate Gradient. A message-passing interface C++ tool called from Java is used for the parallelism. Numerical tests and experimental performance curves on networks on medium and large sizes confirm the computational time decreases for systems with more than 4,500 nodes.