Summary: Given a planar subdivision whose coordinates are integers bounded by \(U\leq 2^w\), we present a linear-space data structure that can answer point-location queries in \(O(\min\{\text{lg } n/\text{lg lg }n,\sqrt{\text{lg }U/\text{lg lg } U}\})\) time on the unit-cost Random Access Machine (RAM) with word size \(w\). This is the first result to beat the standard \(\Theta(\lg n)\) bound for infinite precision models. As a consequence, we obtain the first \(o(n\lg n)\) (randomized) algorithms for many fundamental problems in computational geometry for arbitrary integer input on the word RAM, including: constructing the convex hull of a three-dimensional (3D) point set, computing the Voronoi diagram or the Euclidean minimum spanning tree of a planar point set, triangulating a polygon with holes, and finding intersections among a set of line segments. Higher-dimensional extensions and applications are also discussed. Though computational geometry with bounded precision input has been investigated for a long time, improvements have been limited largely to problems of an orthogonal flavor. Our results surpass this long-standing limitation, answering, for example, a question of Willard (SODA’92).