Manifest Destiny

Manifest Destiny is a population growth simulator. It is based on a cellular automata model of the United States during its period of rapid Westward expansion from 1763 to 1863. It is implemented in C and uses MPI for both parallel processing and parallel I/O. Additionally, it uses CUDA to leverage the power of GPUs for the simulation.

Results

Manifest Destiny is able to produce accurate a simulation of population growth and distribution within tens of percentage points of historical values.

Our simulation can also take advantage of high-performance computing resources to run simulations in a fraction of the time it would take to run serially. We can simulate 1000 simulation iterations in less than 10 seconds when utilizing all available resources.

Quisk Start

Running Manifest Destiny requires several quick steps:

1. Create an input array using the Python helper script.

   • Different resolutions can be created by changing the --resolution_scale parameter. The default is 1.

    python scripts/visualize_data.py export data/img/usa_cities_1763_iso.png out/1763.npy --resolution_scale 1

2. Compile the code using make.

   • This will place the compiled binary in the ./bin/ directory.

   make release # compile the code with optimizations

3. Run the simulation using mpirun.

   • This will create a new output file in the ./out/ directory called 1763_out_<ckpt_iters>.npy for each checkpoint, where <ckpt_iters> is the number of iterations at each saved checkpoint.

   mpirun -np <num_processes> ./bin/manifest out/1763.npy out/1763_out.npy <iterations> <ckpt_iters>

4. Import the simulation output using the Python helper script.

   • This will create a new image in the ./data/img/ directory called 1763_output_<ckpt_iters>.png. This image is an easy way to visually inspect the output of the simulation.

   python scripts/visualize_data.py import out/1763_out_<ckpt_iters>.npy out/1763_output_<ckpt_iters>.png --resolution_scale 1

5. Tally the total population using the Python helper script.

   • This will print the total population of the simulation.

   python scripts/visualize_data.py tally out/1763_out_<ckpt_iters>.npy