Class ParallelGaussSeidelSolver

java.lang.Object
org.ojalgo.matrix.task.iterative.IterativeSolverTask
org.ojalgo.matrix.task.iterative.ParallelGaussSeidelSolver
All Implemented Interfaces:
MatrixTask<Double>, SolverTask<Double>

public final class ParallelGaussSeidelSolver extends IterativeSolverTask
Experimental parallelised stationary iteration based on Gauss–Seidel-style in-place updates.

Concurrency and convergence

  • Targets systems where diagonal dominance or SPD structure makes Gauss–Seidel-type updates effective.
  • Parallel execution may introduce small differences compared to strictly sequential updates.
Configuration
  • Ignores any configured Preconditioner; use the relaxation factor to influence convergence.
When to use
  • To utilise multiple cores for simple in-place iterative sweeps.
  • As a smoother or pre-relaxation when approximate iterations are acceptable.
  • For challenging SPD problems prioritising convergence speed/robustness, Krylov methods are often preferable.