https://github.com/anjiang-wei/amr

https://github.com/anjiang-wei/amr

Science Score: 36.0%

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Repository

Basic Info
  • Host: GitHub
  • Owner: Anjiang-Wei
  • Language: Rouge
  • Default Branch: main
  • Size: 402 KB
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Created over 1 year ago · Last pushed 11 months ago
Metadata Files
Readme

README.md

Task-Based Programming for Adaptive Mesh Refinement in Compressible Flow Simulations

This repository contains the implementation for Task-Based Programming for Adaptive Mesh Refinement in Compressible Flow Simulations, a Regent-based framework (built on the Legion programming model) designed to implement adaptive mesh refinement (AMR) for high-order compressible flow solvers.

Installation

The code is built using Regent, a high-level programming language for the Legion programming model. Please follow the Regent installation guide:

  • Official language site: https://regent-lang.org/
  • Installation instructions: https://github.com/StanfordLegion/legion/tree/stable/language

Repository Overview

The AMR project is structured into three main parts:

  • Solver design and implementation
    Located at src/, this directory contains the core AMR solver code, including task-based mesh refinement/coarsening routines.

  • Compressible flow simulations
    Found in tests/, this folder includes canonical examples and tests for compressible flow problems (e.g., Euler equations).

  • Post-processing for animation
    Available in post/, this directory provides scripts to generate animations from simulation output.

Paper and Citation

This project is documented in this paper arXiv:2508.05020:

```bibtex @article{wei2025taskbased, title={Task-Based Programming for Adaptive Mesh Refinement in Compressible Flow Simulations}, author={Wei, Anjiang and Song, Hang and Hidayetoglu, Mert and Slaughter, Elliott and Lele, Sanjiva K. and Aiken, Alex}, journal={arXiv preprint arXiv:2508.05020}, year={2025}, url={https://arxiv.org/abs/2508.05020} }

Owner

  • Login: Anjiang-Wei
  • Kind: user

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