  Equilibrium sampling of biomolecules remains an unmet challenge after more
than 30 years of atomistic simulation. Efforts to enhance sampling capability,
which are reviewed here, range from the development of new algorithms to
parallelization to novel uses of hardware. Special focus is placed on
classifying algorithms -- most of which are underpinned by a few key ideas --
in order to understand their fundamental strengths and limitations. Although
algorithms have proliferated, progress resulting from novel hardware use
appears to be more clear-cut than from algorithms alone, partly due to the lack
of widely used sampling measures.
