Dendro: parallel algorithms for multigrid and AMR methods on 2:1 balanced octrees

  • Authors:

  • Rahul S. Sampath;Santi S. Adavani;Hari Sundar;Ilya Lashuk;George Biros

  • Affiliations:

  • Georgia Institute of Technology, Atlanta, GA;University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA

  • Venue:
  • Proceedings of the 2008 ACM/IEEE conference on Supercomputing
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this article, we present Dendro, a suite of parallel algorithms for the discretization and solution of partial differential equations (PDEs) involving second-order elliptic operators. Dendro uses trilinear finite element discretizations constructed using octrees. Dendro, comprises four main modules: a bottom-up octree generation and 2:1 balancing module, a meshing module, a geometric multiplicative multigrid module, and a module for adaptive mesh refinement (AMR). Here, we focus on the multigrid and AMR modules. The key features of Dendro are coarsening/refinement, inter-octree transfers of scalar and vector fields, and parallel partition of multilevel octree forests. We describe a bottom-up algorithm for constructing the coarser multigrid levels. The input is an arbitrary 2:1 balanced octree-based mesh, representing the fine level mesh. The output is a set of octrees and meshes that are used in the multigrid sweeps. Also, we describe matrix-free implementations for the discretized PDE operators and the intergrid transfer operations. We present results on up to 4096 CPUs on the Cray XT3 ("BigBen"), the Intel 64 system ("Abe"), and the Sun Constellation Linux cluster ("Ranger").