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Communication Dans Un Congrès Année : 2020

On optimizing scalar self-rebalancing trees

Résumé

Balanced trees are pervasive and very often found in databases or other systems which are built around querying non-static data. In this paper, we show that trees implemented as a collection of pointers shows bad data locality, poor cache performance and suffer from a lack of parallelism opportunities. We propose an alternative implementation based on arrays. Both implementations appear to be equivalently efficient time-wise. This new layout exposes new parallelism opportunities which can be then exploited by an optimizing polyhedral compiler.
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Dates et versions

hal-03048742 , version 1 (09-12-2020)

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  • HAL Id : hal-03048742 , version 1

Citer

Paul Iannetta, Laure Gonnord, Lionel Morel. On optimizing scalar self-rebalancing trees. COMPAS 2020 - Conférence francophone d'informatique en Parallélisme, Architecture et Système, Jun 2020, Lyon, France. pp.1-7. ⟨hal-03048742⟩
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