Modern Datalog engines are employed in industrial applications such as graph-databases, networks, and static program analysis. To cope with vast amount of data, Datalog engines must employ parallel execution strategies, for which specialized concurrent data structures are of paramount importance.
In this paper, we introduce a specialized B-tree data structure for an open-source Datalog compiler written in C++. Our data structure has been specialized for Datalog workloads running on shared-memory multi-core computers. It features (1) an optimistic locking protocol for scalability, (2) is highly tuned, and (3) uses the notion of ``hints'' to re-use the results of previously performed tree traversals to exploit data ordering properties exhibited by Datalog evaluation. In parallel micro-benchmarks, the new data structure achieves up to 59x higher performance than state-of-the-art industrial standards, while integrated into a Datalog engine it accounts for 3x higher, overall system performance.
Wed 20 FebDisplayed time zone: Guadalajara, Mexico City, Monterrey change
09:35 - 10:50
|Encapsulated Open Nesting for STM: Fine-Grained Higher-Level Conflict Detection|
|A Specialized B-Tree for Concurrent Datalog Evaluation|
Herbert Jordan University of Innsbruck, Pavle Subotic University College London, David Zhao The University of Sydney, Bernhard Scholz University of Sydney, AustraliaDOI
|Efficient Race Detection with Futures|
Robert Utterback Monmouth College, Kunal Agrawal Washington University in St. Louis, Jeremy Fineman , I-Ting Angelina Lee Washington University in St. LouisDOI