t8code: A C repository from LucienPan0903

Introduction

t8code (spoken as "tetcode") is a C/C++ library to manage parallel adaptive meshes with various element types. t8code uses a collection (a forest) of multiple connected adaptive space-trees in parallel and scales to at least one million MPI ranks and over 1 Trillion mesh elements. It is licensed under the GNU General Public License 2.0 or later. Copyright (c) 2015 the developers.

t8code is intended to be used as a thirdparty library for numerical simulation codes or any other applications that require meshes.

t8code, or T8 for short, supports the following element types (also different types in the same mesh):

0D: vertices
1D: lines
2D: quadrilaterals and triangles
3D: hexahedra, tetrahedra, prisms (pyramids currently in development).

Among others, t8code offers the following functionalities:

Create distributed adaptive meshes over complex domain geometries
Adapt meshes according to user given refinement/coarsening criteria
Establish a 2:1 balance
(Re-)partition a mesh (and associated data) among MPI ranks
Manage ghost (halo) elements and data
Hierarchical search in the mesh

t8code uses space-filling curves (SFCs) to manage the adaptive refinement and efficiently store the mesh elements and associated data. A modular approach makes it possible to exchange the underlying SFC without changing the high-level algorithms. Thus, we can use and compare different refinement schemes and users can implement their own refinement rules if so desired.

Currently,

lines use a 1D Morton curve with 1:2 refinement
quadrilateral/hexahedral elements are inherited from the p4est submodule, using the Morton curve 1:4, 1:8 refinement;
triangular/tetrahedral are implemented using the Tetrahedral Morton curve, 1:4, 1:8 refinement;
prisms are implemented using the triangular TM curve and a line curve, 1:8 refinement.
The code supports hybrid meshes including any of the above element types (of the same dimension).

You find more information on t8code in the t8code Wiki.

Setup

We provide a short guide to install t8code.

For a more detailed description, please see the Installation guide in our Wiki.

Requirements

libsc (Included in t8code's git repository)
p4est (Included in t8code's git repository)
automake
libtool
make

Optional

The VTK library for advanced VTK output (basic VTK output is provided without linking against VTK)
The netcdf library for netcdf file output

Steps

To setup the project perform the following steps

1.) If you cloned from github, initialize and download the git submodules
   p4est and sc.
  - git submodule init
  - git submodule update      
2.) Call the bootstrap script in the source directory
  - ./bootstrap        
3.) Goto your installation folder and call configure and make
  - cd /path/to/install
  - /path/to/source/configure [OPTIONS]
  - make 
  - make check
  - make install

To see a list of possible configure options, call

./configure -h

or visit the Wiki.

Most commonly used for t8code are

--enable-mpi (enables MPI parallelization)

--enable-debug (enables debugging mode - massively reduces performance)

--with-LIB/--without-LIB (enable/disable linking with LIB)

Example configurations

For a parallel release mode with local installation path $HOME/t8code_install:

configure --enable-mpi CFLAGS=-O3 CXXFLAGS=-O3 --prefix=$HOME/t8code_install

For a debugging mode with static linkage (makes using gdb and valgrind more comfortable):

configure --enable-mpi --enable-debug --enable-static --disable-shared CFLAGS="-Wall -O0 -g" CXXFLAGS="-Wall -O0 -g"

Getting started

To get familiar with t8code and its algorithms and data structures we recommend executing the tutorial examples in example/tutorials and read the corresponding Wiki pages starting with Step 0 - Helloworld.

A sophisticated example of a complete numerical simulation is our finite volume solver of the advection equation in example/advection.

Publications

An (incomplete) list of publications related to t8code:

[1] Johannes Holke, Scalable algorithms for parallel tree-based adaptive mesh refinement with general element types, PhD thesis at University of Bonn, 2018, Full text available

[2] Carsten Burstedde and Johannes Holke, A Tetrahedral Space-Filling Curve for Nonconforming Adaptive Meshes, SIAM Journal on Scientific Computing, 2016, 10.1137/15M1040049

[3] Carsten Burstedde and Johannes Holke, Coarse mesh partitioning for tree-based AMR, SIAM Journal on Scientific Computing, 2017, 10.1137/16M1103518

[4] Johannes Holke and David Knapp and Carsten Burstedde, An Optimized, Parallel Computation of the Ghost Layer for Adaptive Hybrid Forest Meshes, Submitted to SIAM Journal on Scientific Computing, Preprint available 2019

Citing t8code

If you use t8code in any of your publications, please cite the github repository and [1]. For publications specifically related to

the TM index, please cite [2].
coarse mesh partitioning, please cite [3].
construction and handling of the ghost layer, please cite [4].

LucienPan0903/t8code