Particle methods provide a powerful vocabulary to describe a wide range of deterministic and stochastic processes exhibiting multi-scale characteristics.

In this talk we introduce wavelet adapted particle methods for the Navier-Stokes equations and Adaptive Mesh Refinement for stochastic simulations of reaction-diffusion processes. We discuss the coupling of deterministic and stochastic algorithms and emphasize the mapping of these algorithms to multi/many-core architectures. We demonstrate the capabilities of particle methods by presenting applications ranging from fish swimming, to cancer induced angiogenesis and nano-fluidics.