The increasing number of ICP variants leads to an explosion of algorithms and parameters. This renders difficult the selection of the appropriate combination for a given application. In this paper, we propose a state-of-the-art, modular, and efficient implementation of an ICP library. We take advantage of the recent availability of fast depth cameras to demonstrate one application example: a 3D pose tracker running at 30 Hz. For this application, we demonstrate the modularity of our ICP library by optimizing the use of lean and simple descriptors in order to ease the matching of 3D point clouds. This tracker is then evaluated using datasets recorded along a ground truth of millimeter accuracy. We provide both source code and datasets to the community in order to accelerate further comparisons in this field.