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ArrayMorph: Optimizing Hyperslab Queries on the Cloud for Machine Learning Pipelines

Summary: Cost-based multi-phase optimizer for cloud hyperslab (subtensor) reads that models array serialization, chunking, and platform costs to auto-select chunk reads, byte-ranges, or server-side lambdas. Integrates with PyTorch; reduces transferred data up to 9.8×, speeds pipelines up to 1.7× and lowers monetary cost up to 9×. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13952
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,662 | 25.83%
DOI
10.14778/3746405.3746437

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