dannliuu/conways-gol

Conway's Game of Life on Python

Objectives & Approach

We need to implement Conway's GoL in 64-bit integer space!

1. To create a program to play Conway's GoL, we can use Python3 as a testbed for exploring algorithmic solutions! Since Python can store arbitrarily large integers only bounded by system RAM it serves as an easy language for starters.

   We could use C/C++, though any board space larger that 64-bit space would not fit on modern CPU registry size (x64). We could use a library like GMP to accept arbitrary precision integers for future development.

A trivial solution following the execution of Conway's GoL can be found in the "1. Python/ConwaysGoL.ipynb" folder.

Interesting follow-ups to think about!

1. What happens if the input file is 1TB? How can we import that into memory? Can we use generators to output graphics in realtime and throw-out old garbage values for that instant?
   • If we have an extremely sparse matrix, it would make much more sense to actually save the location of only the live cells and then apply the 4 rules accordingly using only these live cells!
2. Say we use Conway's GoL similar to a weather-forecasting simulator where a small input needs to be ran to produce a coherent picture of what happens over 1-million years of compute time. In this case, what would happen if we need even MORE integer space? What would this look like in a multi-GPU/multi-CPU exascale environment?
   • Perhaps we could use an HPC MPI Job Schedulers (e.g., SLURM, MPICH, MVAPICH, OpenMPI), WareWulf (cluster manager) to manage the configuration an exascale-large board simulation! Perhaps we could use database sharding to store fragments of the board space (e.g., Percona XtraDB Cluster, MariaDB Galera Cluster, Vitess row caching)!
3. Can we make this game into potentially a benchmarking tool :)?