Materials, such as snow, sand, metallic paints, rough plastics, and metals, often exhibit small-scale phenomena observed as bright sparkling or glittering surface features. These features become more pronounced under narrow-angle illumination and vary based on the orientation of the surface with respect to the viewer and light sources. Microfacet-based surface models, composed of a large finite number of microscopic mirror-like flakes, can mimic this effect. An associated microfacet BRDF and a memory-efficient stochastic algorithm are explored in [Jakob et al. 2014]. We present a new stochastic algorithm that inherits the good properties of the original algorithm, but does not require any precomputation; implements optimal importance sampling which is extended to efficiently sample wide and heavy-tailed microfacet distributions (i.e. GGX), and offers better overall performance. In addition, a triplanar mapping technique is employed to handle geometry without texture coordinates. The algorithm is both practical and easier to implement.