# GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Model (DG-SWEM) with OpenACC

## TL;DR

This paper demonstrates how using OpenACC and Unified Memory simplifies porting the DG-SWEM storm surge model to GPUs, achieving significant performance improvements on NVIDIA hardware while maintaining a unified codebase.

## Contribution

It introduces a GPU porting approach for DG-SWEM using OpenACC and Unified Memory, avoiding complex code conversions and enabling efficient storm surge simulations.

## Key findings

- GPU implementation outperforms CPU version in storm surge scenarios
- OpenACC simplifies GPU porting process for complex models
- Unified Memory enables seamless CPU-GPU code compatibility

## Abstract

This paper presents a porting of {DG-SWEM}, a first-order discontinuous Galerkin solver for storm surge based on the Advanced Circulation Model (ADCIRC), to NVIDIA GPUs. Time-explicit discontinuous Galerkin methods contain a large number of degrees of freedom but have been shown to exhibit a large amount of data parallelism due to the loose coupling between elements, and thus are naturally mapped to the GPU architecture. A previous framework in porting DG-SWEM to GPUs required converting subroutines from Fortran to C++ to be used with CUDA C++. By using OpenACC and Unified Memory, we simplify the porting process and maintain a single codebase for both CPU and GPU versions. We test the code using a large Hurricane Harvey scenario on NVIDIA's Grace Hopper chip, and compare the GPU code's performance on multiple H200 nodes to the CPU version on the same amount of Grace CPU nodes.