An Eight-Dimensional Systematic Evaluation of Optimized Search Algorithms on Modern Processors
Summary: Evaluates hardware-aware search algorithms (sequential, binary, k-ary) across an eight-dimensional optimization space on modern CPUs. Finds no universal winner; offers hardware- and size-driven guidance on variants to deploy for efficient index/search. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,460 | Benchmarking Learned Indexes | 2021 | VLDB | 0.00011887068 |
| 9,746 | Why Are Learned Indexes So Effective but Sometimes Ineffective? | 2025 | VLDB | 4.2897489e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 102 | The Case for Learned Index Structures | 2018 | SIGMOD | 0.00049545203 |
| 103 | Making B+-Trees Cache Conscious in Main Memory | 2000 | SIGMOD | 0.00049150032 |
| 343 | Implementing Database Operations Using SIMD Instructions | 2002 | SIGMOD | 0.00026768139 |
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