Konferensartikel

To implement large-scale agent-based simulations, developers historically relied on C and C++ due to performance, while struggling to deal with tedious explicit memory management. This struggle translates into software defects and lower developer productivity. More recently, desire to harness multi-core systems via concurrent software complicates design and implementation when memory is shared among compute cores. When we faced this situation, we were looking for a system programming language as fast as C and C++ but without caveats around memory management. Between Go and Rust, we chose Rust language which guarantees safety in memory management even for concurrency, without a run-time or garbage collector. In this paper, we have shared our experience with Rust to build a framework named as EpiRust for agent-based epidemiological simulations. Our simulation experiments have shown some promising results for a population of a few million agents, using commodity-class hardware. Key outcomes of this whole exercise are thatEpiRust could achieve following quality goals: 1. Robustness 2. Flexibility 3. Performance.

agent-based modeling, agent-based simulations, epidemiology, large-scale simulations, Rust language