Network synthesis for database processing units

We explore on-chip network topologies for the Q100, an analytic query accelerator for relational databases. In such data-centric accelerators, interconnects play a critical role by moving large volumes of data. In this paper we show that various interconnect topologies can trade a factor of 2.5× in performance for 3.3× area. Moreover, standard topologies (e.g., ring or mesh) are not optimal. Significant prior work on network topology specialization augments generic topologies with additional dedicated links. In this paper, we present a network specialization algorithm that builds a specialized network first then introduces a generic network as a fallback. We find our algorithm produces networks that are 1.24× slower than the highest-performance generic topology considered (a fat tree), and 18% smaller than the least expensive (a double ring). Moreover, our method produces topologies that outperform those produced by others by 1.21× while being 25% smaller.