Large-scale HPC evaluation of Qdrant, Milvus, and Weaviate reveals that workload patterns limit scaling and extra cores can reduce throughput, exposing a cloud-to-HPC design mismatch.
Wells, Salman Habib, and John Wise
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Pretraining data composition can be used to engineer neural scaling laws in hadronic jet classification toward data-heavy rather than model-size-heavy regimes.
citing papers explorer
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When More Cores Hurts: The Vector Database Scaling Paradox in HPC
Large-scale HPC evaluation of Qdrant, Milvus, and Weaviate reveals that workload patterns limit scaling and extra cores can reduce throughput, exposing a cloud-to-HPC design mismatch.
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Towards Engineering Scaling Laws with Pretraining Data Composition
Pretraining data composition can be used to engineer neural scaling laws in hadronic jet classification toward data-heavy rather than model-size-heavy regimes.