The analysis of noise and acoustics in indoor spaces is often performed with geometrical methods from the ray-tracing family, such as the sound particle method. In general, these offer an acceptable balance between physical accuracy and computational effort, but models with large numbers of objects and high levels of detail can lead to long waits for results. In this paper, we consider methods to assist with the efficient analysis of such situations in the context of the sound particle diffraction model. A modern open-plan office and a large cathedral are used as example projects. We look at space partitioning strategies, adaptive placement of receivers in the form of mesh noise maps, and graphics-card-style hardware acceleration techniques, along with iterative modelling methods. The role of geometrical detail in the context of uncertainties in the input data, such as absorption and scattering coefficients, is also studied. From this, we offer a range of recommendations regarding the level-of-detail in acoustic modelling, including consideration of issues such as seating, tables, and curved surfaces.