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Framework for the automatic generation of FPGA-based Near-Data Processing accelerators in smart storage systems

  • Near-Data Processing is a promising approach to overcome the limitations of slow I/O interfaces in the quest to analyze the ever-growing amount of data stored in database systems. Next to CPUs, FPGAs will play an important role for the realization of functional units operating close to data stored in non-volatile memories such as Flash.It is essential that the NDP-device understands formats and layouts of the persistent data, to perform operations in-situ. To this end, carefully optimized format parsers and layout accessors are needed. However, designing such FPGA-based Near-Data Processing accelerators requires significant effort and expertise. To make FPGA-based Near-Data Processing accessible to non-FPGA experts, we will present a framework for the automatic generation of FPGA-based accelerators capable of data filtering and transformation for key-value stores based on simple data-format specifications.The evaluation shows that our framework is able to generate accelerators that are almost identical in performance compared to the manually optimized designs of prior work, while requiring little to no FPGA-specific knowledge and additionally providing improved flexibility and more powerful functionality.

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Metadaten
Author of HS ReutlingenPetrov, Ilia; Vinçon, Tobias; Knödler, Christian; Bernhardt, Arthur
DOI:https://doi.org/10.1109/IPDPSW52791.2021.00028
Erschienen in:IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 17-21 June 2021, Portland, USA, proceedings
Publisher:IEEE
Place of publication:Piscataway, NJ
Document Type:Conference proceeding
Language:English
Publication year:2021
Tag:COSMOS; FPGA; Near-Data Processing; OpenSSD; automatic generation; database; key-value store
Page Number:8
First Page:136
Last Page:143
DDC classes:004 Informatik
Open access?:Nein
Licence (German):License Logo  In Copyright - Urheberrechtlich geschützt