Centaur: A Framework for Hybrid CPU-FPGA Databases

Abstract

Accelerating relational databases in general and SQL in particular has become an important topic given the challenges arising from large data collections and increasingly complex workloads. Most existing work, however, has been focused on either accelerating a single operator (e.g., a join) or in data reduction along the data path (e.g., from disk to CPU). In this paper we focus instead on the system aspects of accelerating a relational engine in hybrid CPU-FPGA architectures. In particular, we present Centaur, a framework running on the FPGA that allows the dynamic allocation of FPGA operators to query plans, pipelining these operators among themselves when needed, and the hybrid execution of operator pipelines running on the CPU and the FPGA. Centaur is fully compatible with relational engines as we demonstrate through its seamless integration with MonetDB, a popular column store database. In the paper, we describe how this integration is achieved, and empirically demonstrate the advantages of such an approach. The main contribution of the paper is to provide a realistic solution for accelerating SQL that is compatible with existing database architectures, thereby opening up the possibilities for further exploration of FPGA based data processing.