On the necessity of explicit cross-layer data formats in near-data processing systems release_h67mfp76yng4je3vfez5xytfaq

by Lukas Max Weber, Tobias Vincon, Christian Knödler, Leonardo Solis Vasquez, Arthur Bernhardt, Ilia Petrov, Andreas Koch

Published in Distributed and parallel databases by Springer Science and Business Media LLC.

2021  

Abstract

<jats:title>Abstract</jats:title>Massive data transfers in modern data-intensive systems resulting from low data-locality and data-to-code system design hurt their performance and scalability. Near-Data processing (NDP) and a shift to <jats:italic>code-to-data</jats:italic> designs may represent a viable solution as packaging combinations of storage and compute elements on the same device has become feasible. The shift towards NDP system architectures calls for revision of established principles. Abstractions such as <jats:italic>data formats and layouts</jats:italic> typically spread multiple layers in traditional DBMS, the way they are processed is encapsulated within these layers of abstraction. The NDP-style processing requires an explicit definition of cross-layer data formats and accessors to ensure in-situ executions optimally utilizing the properties of the underlying NDP storage and compute elements. In this paper, we make the case for such data format definitions and investigate the performance benefits under RocksDB and the COSMOS hardware platform.
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