Origami: A High-Performance Mergesort Framework
Summary: Origami is an in-memory, SIMD-aware mergesort framework with an end-to-end pipeline. Key ideas: vector in-register sorters, a branchless streaming merge, a cache-residing quad-merge tree, and scalable parallel partitioning. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Arif Arman
- 2. Dmitri Loguinov
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 351 | Sort vs. Hash Revisited: Fast Join Implementation on Modern Multi-Core CPUs | 2009 | VLDB | 0.0002636504 |
| 930 | Fast Sort on CPUs and GPUs: A Case for Bandwidth Oblivious SIMD Sort | 2010 | SIGMOD | 0.00015238545 |
| 946 | Efficient Implementation of Sorting on Multi-Core SIMD CPU Architecture | 2008 | VLDB | 0.0001513324 |
| 1,607 | A Comprehensive Study of Main-Memory Partitioning and its Application to Large-Scale Comparison- and Radix-Sort | 2014 | SIGMOD | 0.00011162682 |
| 3,448 | Faster Set Intersection with SIMD instructions by Reducing Branch Mispredictions | 2015 | VLDB | 7.0844401e-05 |
| 4,655 | SIMD- and Cache-Friendly Algorithm for Sorting an Array of Structures | 2015 | VLDB | 6.0221672e-05 |
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