Maggioli, FilippoMarin, RiccardoMelzi, SimoneRodolà, EmanueleUmetani, NobuyukiWojtan, ChrisVouga, Etienne2022-10-042022-10-0420221467-8659https://doi.org/10.1111/cgf.14697https://diglib.eg.org:443/handle/10.1111/cgf14697The slime mold algorithm has recently been under the spotlight thanks to its compelling properties studied across many disciplines like biology, computation theory, and artificial intelligence. However, existing implementations act only on planar surfaces, and no adaptation to arbitrary surfaces is available. Inspired by this gap, we propose a novel characterization of the mold algorithm to work on arbitrary curved surfaces. Our algorithm is easily parallelizable on GPUs and allows to model the evolution of millions of agents in real-time over surface meshes with several thousand triangles, while keeping the simplicity proper of the slime paradigm. We perform a comprehensive set of experiments, providing insights on stability, behavior, and sensibility to various design choices. We characterize a broad collection of behaviors with a limited set of controllable and interpretable parameters, enabling a novel family of heterogeneous and high-quality procedural textures. The appearance and complexity of these patterns are well-suited to diverse materials and scopes, and we add another layer of generalization by allowing different mold species to compete and interact in parallel.Keywords: Procedural texturing, animated texture, slime mould, GPU algorithm CCS Concepts: Computing methodologies → Texturing; Theory of computation → Parallel algorithms; Mathematics of computing → Geometric topologyProcedural texturinganimated textureslime mouldGPU algorithm CCS ConceptsComputing methodologies → TexturingTheory of computation → Parallel algorithmsMathematics of computing → Geometric topology10.1111/cgf.14697519-5279 pages