Yasmina Mohedeen
2011
This thesis presents a parallel approach to evacuation modelling in order to
aid real-time, largescale procedure development. An extensive investigation into
which partitioning strategy to employ with the parallel version of the software
was researched so as to maximise its performance.
The use of evacuation
modelling is well established as part of building design to ensure buildings
meet performance based safety and comfort criteria (such as the placements of
windows or stairs so as to ease people‘s comfort) . A novel approach to using
evacuation modelling is during live evacuations from various disasters.
Disasters may be fast developing in large areas and incident commanders can use
the model to plan safe escape routes to avoid danger areas. For this type of
usage, very fast results must be obtainable in order for the incident commanders
to optimise the evacuation plan along with the software‘s capability to simulate
large-scale evacuation scenarios. buildingEXODUS provides very fast results for
small-scale cases but struggles to give quick results for large-scale
simulations. In addition, the loading up of large-scale cases are dependent on
the specifications of the processor used thus making the problem case
unscalable. A solution to address these shortcomings is the use of parallel
computing. Large-scale cases can be partitioned and run by a network of
processors, thus reducing the running time of the simulations as well as the
ability to represent a large geometry by loading parts of the domain on each
processor. This scheme was attempted and buildingEXODUS was successfully
parallelised to cope with large-scale evacuation simulations.
Various
partitioning methods were attempted and due to the stochastic nature of every
evacuation scenario, no definite partitioning strategy could be found. The
efficiency values ranged from 230% (with both cores being used from 10 dual-core
processors) when an idealised case was run to 23% for another test case. The
results obtained were highly dependent on the test case‘s geometry, the scenario
being applied, whether all the cores are being used in case of multi-cores
processors, as well as the partitioning method used. However, the use of any
partitioning method will produce an improvement from running the case in serial.
On the other hand, the speedups obtained were not scalable to warrant the
adoption of any particular partitioning method. The dominant criteria inhibiting
the parallel system was processor idleness or overload rather than communication
costs, thus degrading the performance of the parallel system. Hence an
intelligent partition strategy was devised, which dynamically assesses the
current situation of the parallel system and repartitions the problem
accordingly to prevent processor idleness and overloading. A dynamic load
reallocation method was implemented within the parallelised buildingEXODUS to
cater for any degradation of the parallel system. At its best, the dynamic
reallocation strategy produced an efficiency value of 93.55% and a value of
36.81% at its worse. As a direct comparison to the static partitioning strategy,
an improvement was observed in most cases run. A maximum improvement of 96.48%
was achieved from using the dynamic reallocation strategy compared to using a
static partitioning approach. Hence the parallelisation of the buildingEXODUS
evacuation software was successfully implemented with most cases achieving
encouraging speedup values when a dynamic repartitioning strategy was employed.