Interleaved Multi-Vectorizing
Summary: Interleaved multi-vectorizing (IMV) hides memory latency by interleaving multiple vectorized executions. Residual vectorized states combat control-flow divergence, enabling reduced cache/branch misses and applying to full query pipelines; achieves up to 4.23x vs scalar and 3.17x vs pure SIMD. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zhuhe Fang
- 2. Beilei Zheng
- 3. Chuliang Weng
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 488 | TiDB: A Raft-based HTAP Database | 2020 | VLDB | 0.000220409 |
| 4,184 | CoroBase: Coroutine-Oriented Main-Memory Database Engine | 2021 | VLDB | 6.3779731e-05 |
| 5,312 | The Art of Latency Hiding in Modern Database Engines | 2024 | VLDB | 5.5734224e-05 |
| 6,221 | Charting the Design Space of Query Execution using VOILA | 2021 | VLDB | 5.1512158e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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