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DANSEN: Database acceleration on native computational storage by exploiting NDP

  • This paper introduces DANSEN, the hardware accelerator component for neoDBMS, a full-stack computational storage system designed to manage on-device execution of database queries/transactions as a Near-Data Processing (NDP)-operation. The proposed system enables Database Management Systems (DBMS) to oload NDP-operations to the storage while maintaining control over data through a native storage interface. DANSEN provides an NDP-engine that enables DBMS to perform both low-level database tasks, such as performing database administration, as well as high-level tasks like executing SQL, on the smart storage device while observing the DBMS concurrency control. Furthermore, DANSEN enables the incorporation of custom accelerators as an NDP-operation, e.g., to perform hardware-accelerated ML inference directly on the stored data. We built the DANSEN storage prototype and interface on an Ultrascale+HBM FPGA and fully integrated it with PostgreSQL 12. Experimental results demonstrate that the proposed NDP approach outperforms software-only PostgreSQL using a fast of-the-shelf NVMe drive, and signiicantly improves the end-to-end execution time of an aggregation operation (similar to Q6 from CH-benCHmark, 150 million records) by ≈10.6×. The versatility of the proposed approach is also validated by integrating a compute-intensive data analytics application with multi-row results, outperforming PostgreSQL by ≈1.5×.

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Author of HS ReutlingenPetrov, Ilia; Bernhardt, Arthur
Erschienen in:ACM Transactions on reconfigurable technology and systems : TRETS
Place of publication:New York, NY
Document Type:Journal article
Publication year:2024
Tag:FPGA; computational storage; database management systems; near-data processing
Page Number:32
First Page:1
Last Page:32
PPN:Im Katalog der Hochschule Reutlingen ansehen
DDC classes:510 Mathematik
004 Informatik
Open access?:Ja
Licence (German):License Logo  In Copyright - Urheberrechtlich geschützt