Biological system behaviors are often the outcome of complex interactions among a large number of cells and their biotic and abiotic environment. Discrete agent based modeling (in combination with high-resolution grids to model the extracellular environment) is a popular approach for building high fidelity biological system models. However, the computational complexity of this approach forces computational biologists to resort to coarser resolution approaches to simulate large biological systems. High-performance parallel computers have the potential to address the computing challenge, but writing efficient software for parallel computers is difficult and time consuming.

We have developed Biocellion to lower the programming burden in efficiently using parallel computers to simulate high-fidelity biological system models at scale. Biocellion targets computational biologists with strong mathematical modeling background but without parallel computing expertise. Biocellion asks users to provide their model specific rules by filling the function body of pre-defined model routines. Biocellion is responsible for efficiently executing these rules in parallel. This presentation will cover key design principles of the framework, examples of the model routines, results from early adopters, and the future roadmap.