High Level Synthesis Based Hardware Accelerator Design for Processing SQL Queries

About three exabytes of data is created and stored in databases each day, and this number is doubling approximately every forty months. Querying this enormous amount of data has been a challenge and new methods have been actively researched. In this paper, we present hardware accelerators which are designed to speed up database analytics for in-memory databases. Unlike traditional hardware accelerator designs, our hardware accelerators are composed using High Level Synthesis (HLS), which enables high level descriptions of functionality such as data filtering, sorting, equijoins to be targeted directly into RTL. We have simulated TPC-H benchmark queries using Xilinx Vivado HLS managed in our custom simulation software framework. Our results have demonstrated the capabilities of HLS in database acceleration domain; such that the 200MHz FPGA accelerator can provide two orders of magnitude performance improvement compared to PostgreSQL based full software implementation running on a modern multicore system.