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The Cellular Potts Model (CPM) is a widely used simulation paradigm forsystems of interacting cells that has been used to study scenarios ranging fromplant development to morphogenesis, tumour growth and cell migration. Despitetheir wide use, CPM simulations are considered too computationally intensivefor three-dimensional (3D) models at organ scale. CPMs have been difficult toparallelise because of their inherently sequential update scheme. Here, wepresent a Graphical Processing Unit (GPU)-based parallelisation scheme thatpreserves local update statistics and is up to 3-4 orders of magnitude fasterthan serial implementations. We show several examples where our schemepreserves simulation behaviors that are drastically altered by existingparallelisation methods. We use our framework to construct tissue-scale modelsof liver and lymph node environments containing millions of cells that aredirectly based on microscopy-imaged tissue structures. Thus, our GPU-based CPMframework enables in silico studies of multicellular systems of unprecedentedscale.

A parallelized cellular Potts model that enables simulations at tissue scale