clcell
clcell is an OpenCL-accelerated cellular automata simulator for Python 3.
Features
- OpenCL-based hardware acceleration
- Custom rulesets via
clcell.RuleSet
- Parallel simulations via
clcell.CASimulator.batch_simulate
Limitations
- Only binary cell states
- No support for infinite grids
- Grid boundary cells must be unpopulated
Installation
Regardless of the installation method you choose, you will need OpenCL drivers for your hardware.
Using pip
$ pip install --user clcell
Building from Source
Requirements:
Clone this repository:
$ git clone https://github.com/Foxbud/clcell.git
Enter the project directory:
$ cd clcell
Build and install this package:
$ make install
Usage
import numpy as np
import clcell
# Instantiate a simulator using Conway's Game of Life as the ruleset.
sim = clcell.CASimulator(clcell.LIFE)
# Create a randomized game state to use as a seed.
seed_state = np.random.randint(0, 2, (1023, 1023), dtype=np.int8)
# Pad state with zeros (required for now).
seed_state = np.pad(seed_state, 1, constant_values=0)
# Simulate 10,000 generations based on that seed.
final_state = sim.simulate(10000, seed_state)
# Create a batch of 1,000 randomized, padded game states to use as seeds.
seed_states = np.array([
np.pad(
np.random.randint(0, 2, (127, 127), dtype=np.int8),
1,
constant_values=0
)
for num
in range(1000)
])
# Simulate 1,000 generations based on each of those seeds.
final_states = sim.batch_simulate(1000, seed_states)
Changelog
v1.0.1
- Simplified how the device code checks for boundary cells.
- Refactored device code to use grids of 8-bit cells as opposed to 32-bit.
- Fixed incorrectly placed size annotations in one device function.
v1.0.0
- Initial release.