ReProVide: Query Optimization and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis

Hahn T, Langohr M, Becher A, Beena Gopalakrishnan Nair L, Meyer-Wegener K, Teich J, Wildermann S (2025)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2025

Original Authors: Tobias Hahn, Maximilian Langohr, Andreas Becher, Lekshmi Beena Gopalakrishnan Nair, Klaus Meyer-Wegener, Jürgen Teich, Stefan Wildermann

Edited Volumes: Scalable Data Management for Future Hardware

Pages Range: 171-197

ISBN: 9783031740961

DOI: 10.1007/978-3-031-74097-8_7

Abstract

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.

Authors with CRIS profile

Tobias Hahn Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design) Maximilian Langohr Chair for Computer Science 6 (Data Management) Lekshmi Beena Gopalakrishnan Nair Chair for Computer Science 6 (Data Management) Klaus Meyer-Wegener Chair for Computer Science 6 (Data Management) Jürgen Teich Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design) Stefan Wildermann Lehrstuhl für Informatik 12 (Hardware-Software-Co-Design)

Related research project(s)

Query Optimisation and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis (Phase II) (ReProVide II INF6) Aug. 1, 2021 - July 31, 2024 Query Optimisation and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis (ReProVide) DFG-Schwerpunktprogramm (SPP) 2037 - Skalierbares Datenmanagement für zukünftige Hardware Aug. 28, 2017 - March 1, 2023

Involved external institutions

Technische Universität Ilmenau DE Germany (DE)

How to cite

APA:

Hahn, T., Langohr, M., Becher, A., Beena Gopalakrishnan Nair, L., Meyer-Wegener, K., Teich, J., & Wildermann, S. (2025). ReProVide: Query Optimization and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis. In Scalable Data Management for Future Hardware. (pp. 171-197).

MLA:

Hahn, Tobias, et al. "ReProVide: Query Optimization and Near-Data Processing on Reconfigurable SoCs for Big Data Analysis." Scalable Data Management for Future Hardware. 2025. 171-197.

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