Increasing the simulation performance of large-scale evacuations using parallel computing techniques based on domain decomposition

Evacuation simulation has the potential to be used as part of a decision support system during large-scale incidents to provide advice to incident commanders. To be viable in these applications, it is essential that the simulation can run many times faster than real time. Parallel processing is a method of reducing run times for very large computational simulations by distributing the workload amongst a number of processors. This paper presents the development of a parallel version of the rule based evacuation simulation software buildingEXODUS using domain decomposition. Four Case Studies (CS) were tested using a cluster, consisting of 10 Intel Core 2 Duo (dual core) 3.16 GHz CPUs. CS-1 involved an idealised large geometry, with 20 exits, intended to illustrate the peak computational speed up performance of the parallel implementation, the population consisted of 100,000 agents; the peak computational speedup (PCS) was 14.6 and the peak real-time speedup (PRTS) was 4.0. CS-2 was a long area with a single exit area with a population of 100,000 agents; the PCS was 13.2 and the PRTS was 17.2. CS-3 was a 50 storey high rise building with a population of 8000/16,000 agents; the PCS was 2.48/4.49 and the PRTS was 17.9/12.9. CS-4 is a large realistic urban area with 60,000/120,000 agents; the PCS was 5.3/6.89 and the PRTS was 5.31/3.0. This type of computational performance opens evacuation simulation to a range of new innovative application areas such as real-time incident support, dynamic signage in smart buildings and virtual training environments