Reiter's local cellular model for snow crystal growth

Reiter's local cellular model for snow crystal growth sped up using OpenMP and CUDA.

The idea is similar to Conway's Game of Life, but with different rules and using a hexagonal grid. For a description of the model and other interesting snow crystal parameters check out Reiter's paper.

The following solutions are implemented:

• serial serial version.
• openmp multi-threading using OpenMP.
• cuda-1 basic CUDA version.
• cuda-2 improved CUDA version using shared memory.
• cuda-3 splits computation among multiple GPUs (on a single node).

Benchmarks

Results for a 3200 x 3200 grid and 2000 iterations.

	serial	openmp	cuda-1	cuda-2	cuda-3
Iteration time [s]	3.2793	0.0991	0.0135	0.0099	0.0050
Iteration speedup	1	33.0855	242.2377	331.4498	661.0083
Image draw time [s]	0.4849	0.0185	0.0022	0.0022	0.0016
Image draw speedup	1	26.1455	220.9350	223.2132	296.4358
Total time [s]	6567.2559	200.9719	31.1356	23.6711	15.2646

Reproducing results

• The code for running benchmarks is written for a HPC cluster which uses SLURM. To run locally, you will need to modify the scripts manually.

1. Submit batch jobs: scripts/compare_all.sh and scripts/compare_cuda.sh
2. When all jobs are complete, create comparison plots using: python scripts/compare_all.py and python scripts/compare_cuda.py

Setup

You will need gcc and nvcc compilers.

For convenience you can compile the code with different constants using the -D compiler flag. Example:

./scripts/clean.sh  # prepare output directories
./scripts/cuda-2.sh -D ROWS=2000 -D COLS=2000 -D ITERS=2000