FPGA Acceleration for the Frequent Item Problem
Field-Programmable Gate Arrays (FPGAs) can provide performance advantages with lower resource consumption (e.g., energy) than conventional CPUs. In this paper, the authors show how to employ FPGAs to provide an efficient and high-performance solution for the frequent item problem. They discuss three design alternatives, each one of them exploiting different FPGA features, and they provide an exhaustive evaluation of their performance characteristics. The first design is a one-to-one mapping of the space-saving algorithm (shown to be the best approach in software), built on special features of FPGAs: content-addressable memory and dual-ported BRAM.