Centaur: A Framework for Hybrid CPU-FPGA Databases

Abstract

Accelerating relational databases in general and SQL in particular has become an important topic given thechallenges arising from large data collections and increasinglycomplex workloads. Most existing work, however, has beenfocused on either accelerating a single operator (e.g., a join) orin 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 theFPGA that allows the dynamic allocation of FPGA operatorsto query plans, pipelining these operators among themselveswhen needed, and the hybrid execution of operator pipelinesrunning on the CPU and the FPGA. Centaur is fully compatiblewith relational engines as we demonstrate through its seamlessintegration with MonetDB, a popular column store database. Inthe paper, we describe how this integration is achieved, andempirically demonstrate the advantages of such an approach. The main contribution of the paper is to provide a realisticsolution for accelerating SQL that is compatible with existingdatabase architectures, thereby opening up the possibilities forfurther exploration of FPGA based data processing.