ReProVide: Query Optimization and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis - Hahn, Tobias; Langohr, Maximilian; Becher, Andreas; Beena Gopalakrishnan Nair, Lekshmi; Meyer-Wegener, Klaus; Teich, Jürgen; Wildermann, Stefan (Scalable Data Management for Future Hardware, 2025)
The available parallelism and heterogeneity of emerging computer systems must be exploited for being able to process the huge amounts of data produced every day. As a consequence, we observe an increasing research interest in accelerating database query processing on multi-cores and attached co-processors like Graphics Processing Units (GPUs) and Field-Programmable Gate Arrays (FPGAs). This chapter presents ReProVide, an approach combining near-data processing and FPGA-based acceleration. The System-on-Chip (SoC) architecture of ReProVide including a flexibly reconfigurable FPGA can load and execute hardware accelerators for various operators on relational and streaming data. Moreover, we present novel Database Management System (DBMS) techniques for partitioning query execution plans between a host and Reconfigurable data-Provider Units (RPUs) and for mapping operators onto RPUs by means of hardware reconfiguration.<br