3D Parallel Mesh Adaptation

ParMmg is an open source software (L-GPL) that performs 3D parallel mesh adaptation using MPI parallelization.

Mesh adaptation is an iterative process that allows to optimize the density and orientation of the elements of a computational mesh with repect to user needs (maximal admissible error over numerical solutions, boundaries representation, etc…). ParMmg is built on top of the Mmg software and aims at having the same capabilities, both in term of options than in term of usability:

  – mesh quality improvement;

  – isotropic and anisotropic mesh adaptation with respect to a user size-map;

  – isosurface discretization;

  – user friendly API.

The ParMmg developement is currently founded by the ExaQUte european project in which ParMmg will provide parallel mesh adaptation for the massively parallel simulations of the partners (few thousands of cores).

You can already use, download and try ParMmg, either as a standalone application, either through other software that interface us:

  – the AeroSol library;

  – the freefem++ solver;

  – the Kratos multiphysics framework;

Thanks to PlaFRIM, we have the possibility to develop, test and profile ParMmg… and of course, to continuously improve it.

Example of parallel mesh adaptation using ParMmg
Example of parallel mesh adaptation using ParMmg: cut through initial mesh with user size map (left) and ParMmg output (right).

Contact: Algiane Froehly algiane.froehly AT inria.fr

Building A High-Performance Solver Stack on Top of a Runtime System

The teams HiePACS, Storm and Tadaam have been cooperating for more than a decade now, on developing the idea of building numerical solvers on top of parallel runtime systems.

From the precursory static/dynamic scheduling experiments explored in the PhD of Mathieu Faverge defended in 2009 to the full-featured SolverStack suite of numerical solvers running on modern, task-based runtime systems such as StarPU and PaRSEC, this idea of delegating part of the optimization process from solvers to external system as been successful. The communication library NewMadeleine is also part of this HPC software stack.

PlaFRIM has always been a key enabling component of these collaborations. Thanks to its heterogeneous computing units (standard nodes, GPU, Intel KNL, Numa nodes, …), the development and validation of our software stack have been made easier. Multiple collaborations with national and international universities and industrials have also been made thanks to our use of the platform.

Contact : Olivier Aumage oliver.aumage AT inria.fr

Predictive Rendering

To generate photo-realistic images, one needs to simulate the light transport inside a chosen virtual scene observed from a virtual viewpoint (i.e., a virtual camera). A virtual scene is obtained by modelling (or measuring from the real-world) the:

– shapes of the objects and the light sources,

– the materials reflectance and transmittance

– the spectral emittance of the light sources.

Simulating the light transport is done by solving the recursive Rendering Equation. This equation states that the equilibrium radiance (in Wm-2sr-1 per wavelength) leaving a point is the sum of emitted and reflected radiance under a geometric optics approximation.

The Rendering Equation is therefore directly related to the law of conservation of energy.The rendering equation is solved with Monte-Carlo computations In the context of Computer Graphics, a Monte-Carlo sample is a geometric ray carrying radiance along its path, which is stochastically (e.g., using Russian roulette) constructed.

PlaFRIM permits researchers in Computer Graphics to simulate billion of light paths/rays to generate reference images for a given virtual scene.

These data can be used to validate:

– new models that predicts how light is scattered by a material

– new rendering algorithm that are more efficient in terms of variance but also in terms of parallelism.

Indeed, PlaFRIM offers a large palette of computing nodes (CPU, bi-GPU) that permit us to develop, test and validate the whole rendering pipeline.

Contact: Romain Pacanowski romain.pacanowski AT inria.fr