July 11 – Jose Fonseca: Towards scalable parallel adaptive simulations with ParFlow

Jose Fonseca: Thursday 11 July at 11:00, A415 Inria Paris.

The accurate simulation of variably saturated flow in
a porous media is a valuable component in understanding
physical processes occurring in many water resources
problems. Such simulations require expensive and extensive
computations and efficient usage of the latest
high performance parallel computing systems becomes a necessity.

The simulation software ParFlow has been shown to have excellent solver
scalability for up to 16k processes. In order to scale the code
to the full size of current petascale systems, we have reorganized
its mesh subsystem to use state of the art mesh refinement and partition algorithms
provided by the parallel software library p4est.
Evaluating the scalability and performance of our modified version of ParFlow,
we demonstrate weak and strong scaling to over 458k processes of the Juqueen
supercomputer at the Jülich Supercomputing Centre.

In the first part of the talk we will briefly present the algorithmic approach
employed to couple both libraries. The enhanced scalability results of ParFlow’s modified
version were obtained for uniform meshes. Hence, without explicitly exploiting the
adaptive mesh refinement (AMR) capabilities of p4est. We will finish this first part
presenting our current efforts to enable the usage of locally refined meshes in ParFlow.

In an AMR framework. In such case, the finite difference (FD) method taken by ParFlow will
require modifications to correctly deal with different size elements. Mixed finite elements
(MFE) are on the other hand better suited for the usage of AMR. It is known that the cell centered FD
method used in ParFlow might be reinterpreted as a MFE discretization using Raviart-Thomas
elements of lower order. We conclude this talk presenting a block preconditioner for saddle point
problems arising from a MFE that retains its robustness in the case of locally refined meshes.

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