Using the GPU version of Clawpack¶
GPU versions of the two-dimensional AmrClaw and GeoClaw codes have been developed primarily by Xinsheng Qin, as described in the references below.
This is still under development and has not yet been fully merged in Clawpack, but there is a gpu branch of most of the Clawpack repositories and checking those out will give a working version of the GPU code.
You can do this by checking out the gpu branch of the clawpack/clawpack module and then doing git module update.
To create a new clone clawpack_gpu with the proper branches checked out, you can use these commands:
git clone https://github.com/clawpack/clawpack.git clawpack_gpu
git checkout -b gpu origin/gpu
git submodule init
git submodule update
Note that this version of the GPU code is roughly based on version 5.5.0 of Clawpack but had some other changes merged in as well (in particular adjoint flagging, see Guiding AMR with adjoint flagging), and so it is not exactly equivalent in capabilities.
The GPU version has some new libraries of source code. In particular, $CLAW/amrclaw/src/2d/GPU contains .H, .cpp and .f90 files for the 2d amrclaw code. Many of the .f90 files replace those normally used from $CLAW/amrclaw/src/2d and those files are removed from this branch. This means that the pure CPU version of amrclaw cannot be run from this branch, instead check out a specific version such as v5.5.0 to run the CPU code for comparisons.
Similarly, $CLAW/geoclaw/src/2d/shallow/GPU contains replacement .f90 files for many of the library routines in $CLAW/geoclaw/src/2d/shallow.
Efficient Tsunami Modeling on Adaptive Grids with Graphics Processing Units (GPUs) by X. Qin, R. J. LeVeque, and M. Motley, Journal of Advances in Modeling Earth Systems, 2019, DOI:10.1029/2019MS001635
Accelerating wave-propagation algorithms with adaptive mesh refinement using the Graphics Processing Unit (GPU), by X. Qin, R. J. LeVeque, and M. R. Motley, https://arxiv.org/abs/1808.02638
See also the older instructions and links to Xinsheng’s original branches at https://github.com/xinshengqin/geoclaw/tree/geo_gpu_paper