Both serial and massively parallel computations on distributed memory architectures are possible.
Available numerical methods.
The concept of modularity applies not only to the type of equation being solved but also to the capability of enabling different numerical algorithms to be employed and combined in different contexts and different components.
PLUTO solves the fluid equations by means of shock-capturing Godunov-type methods adopting a conservative discretization based on finite volume or finite difference methods. In this formulation interface fluxes are computed by solving a Riemann problem between left and right interface states. A typical time step cycle consists of a i) an explicit time-marching algorithm, ii) a piece-wise reconstruction scheme, iii) a Riemann solver.
For each step, different options can be indipendently selected from:
- RK2, RK3, Characteristic Tracing, or MUSCL-Hancock.
- Super-Time-Stepping to speed-up explicit time-stepping for parabolic terms
- FARGO scheme for orbital advection of (magnetized) shear flows
Reconstruction: 2nd-order slope-limited TVD, PPM, WENO and MP5
Riemann Solvers: Two-Shocks, Roe, HLLD, HLLC, HLL and Lax-Friedrichs;
In addition, MHD and relativistic MHD are evolved by selecting different strategies to enforce the divergence-free condition, including Constrained transport (CT) / hyperbolic divergence cleaning / Powell's 8 wave formulation.