Exploiting hardware reconfigurability on window join

Stream processing is attracting wider attention in recent years, and in order to get high efficiency, more people are now trying to leverage hardware for stream processing. In this paper, we clarify two issues by taking window join as an example application: (a) how a software engineer would efficiently utilize hardware, and (b) how adaptiveness will be achieved on it. We use a dynamically reconfigurable hardware with a C-based high level synthesis tool as our evaluation platform. The throughput improved by 216 times through software code optimization, and achieved 26 times higher throughput/power efficiency than an optimized software solution for a CPU. We conclude that a software engineer with certain hardware knowledge will be able to facilitate hardware, and dynamic reconfiguration capability improves the throughput/power efficiency of stream processing.