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DOE OSTI · 2571755

Data Structure Alchemy

Idreos, Stratos [Harvard Univ., Cambridge, MA (United States)] (ORCID:0000000282719187)
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Abstract

In an increasingly more data-driven world, the project set out to uncover the first principles of data-structure design, chart the immense design space they form, and build automation that can synthesize an optimal structure, or even a whole storage engine, for any given workload, hardware platform, and cost target. Data structures are at the center of every computational system and are directly responsible for its performance. Two core technical thrusts were defined: 1) Mapping design spaces for key data-centric abstractions (filters, hash functions, storage-engine layouts, neural-network topologies, blockchain protocols, image layouts, etc.). 2) Developing search & synthesis algorithms, initially analytical cost models, later neural-guided bi-level optimisers that navigate sextillions of candidate designs in seconds and materialise the best one as ready‐to-run code. This report distills the key insights, accomplishments, and impact.

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Idreos, Stratos [Harvard Univ., Cambridge, MA (United States)] (ORCID:0000000282719187). 2025-07-15. Data Structure Alchemy. https://doi.org/10.2172/2571755

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