OpenCL-accelerated cellular automata simulator
clcell is an OpenCL-accelerated cellular automata simulator for Python 3.
- OpenCL-based hardware acceleration
- Custom rulesets via
- Parallel simulations via
- Only binary cell states
- No support for infinite grids
- Grid boundary cells must be unpopulated
Regardless of the installation method you choose, you will need OpenCL drivers for your hardware.
$ pip install --user clcell
Building from Source
Clone this repository:
$ git clone https://github.com/Foxbud/clcell.git
Enter the project directory:
$ cd clcell
Build and install this package:
$ make install
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)
- 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.
- Initial release.
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