# BioDynamo v2 Brings GPU Acceleration to Large-Scale Cell Simulations

#programming #tech

The latest release of BioDynamo, a high-performance simulation engine for biological development and disease modeling, introduces full GPU acceleration. Developed by a collaboration between CERN and academic partners, BioDynamo v2 allows researchers to simulate millions of interacting cells with real-time performance on modern hardware.

Key Features

CUDA backend for particle-based cellular simulations
Modular physics engine for modeling proliferation, adhesion, and migration
New APIs for importing experimental single-cell datasets
Visualizer for 3D output in Jupyter or standalone tools

Code Sample

from biodynamo import Simulation, Cell, run_simulation

class ImmuneCell(Cell):

    def behavior(self):

        self.grow(rate=0.05)

        self.move_random()

sim = Simulation(cell_type=ImmuneCell, num_cells=10000, backend="gpu")

sim.run(steps=500)

run_simulation(sim)

Why It Matters

Simulating complex cellular behavior over large populations has traditionally required HPC infrastructure or approximations. With GPU acceleration, BioDynamo reduces simulation time from hours to minutes. This makes it feasible for individual labs to model processes like immune responses, tumor growth, and neural development without massive compute budgets.

Version 2 also includes improved integration with real biological datasets, allowing validation of hypotheses at scale. It is already being used in EU-funded cancer modeling projects and university-level developmental biology labs.