FPGA-accelerated information retrieval: high-efficiency document filtering

Power consumption in data centres is a growing issue as the cost of the power for computation and cooling has become dominant. An emerging challenge is the development of ldquoenvironmentally friendlyrdquo systems. In this paper we present a novel application of FPGAs for the acceleration of information retrieval algorithms, specifically, filtering streams/collections of documents against topic profiles. Our results show that FPGA acceleration can result in speed-ups of up to a factor 20 for large profiles

Transit Node Routing Reconsidered

Transit Node Routing (TNR) is a fast and exact distance oracle for road networks. We show several new results for TNR. First, we give a surprisingly simple implementation fully based on Contraction Hierarchies that speeds up preprocessing by an order of magnitude approaching the time for just finding a CH (which alone has two orders of magnitude larger query time). We also develop a very effective purely graph theoretical locality filter without any compromise in query times. Finally, we show that a specialization to the online many-to-one (or one-to-many) shortest path further speeds up query time by an order of magnitude. This variant even has better query time than the fastest known previous methods which need much more space.Comment: 19 pages, submitted to SEA'201