We address the challenge of efficiently rendering massive assemblies of grains within a forward path-tracing framework. Previous approaches exist for accelerating high-order scattering for a limited, and static, set of granular materials, often requiring scene-dependent pre-computation. We significantly expand the admissible regime of granular materials by considering heterogeneous and dynamic granular mixtures with spatially varying grain concentrations, pack rates, and sizes. Our method supports both proc
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