In many domains, high-resolution agent-based simulations require experiments with a large number (tens or hundreds of millions) of computationally complex agents. Such large-scale experiments are usually run for efficiency on high-performance computers or clusters, and therefore agent-based simulation frameworks must support parallel distributed computations. The development of experiments with a large number of interconnected agents and a shared environment running in parallel on multiple compute nodes is especially challenging because it introduces the overhead of cross-process communications.