Traditional databases have focused on the issue of reducing I/O cost as it is the bottleneck in many operations. As databases become increasingly accepted in areas such as Geographic Information Systems (GIS) and Bioinformatics, commercial DBMS need to support data types for complex data such as spatial geometries and protein structures. These non-conventional data types and their associated operations present new challenges. In particular, the computational cost of some spatial operations can be orders of magnitude higher than the I/O cost. In order to improve the performance of spatial query processing, innovative solutions for reducing this computational cost are beginning to emerge. Recently, it has been proposed that hardware acceleration of an off-the-shelf graphics card can be used to reduce the computational cost of spatial operations. However, this proposal is preliminary in that it establishes the feasibility of the hardware assisted approach in a stand-alone setting but no...