Depth-13 Sorting Networks for 28 Channels
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866917097997598720 |
|---|---|
| author | Wang, Chengu |
| author_facet | Wang, Chengu |
| contents | We establish new depth upper bounds for sorting networks on 27 and 28 channels, improving the previous best bound of 14 to 13. Our 28-channel network is constructed with reflectional symmetry by combining high-quality prefixes of 16- and 12-channel networks, extending them greedily one comparator at a time, and using a SAT solver to complete the remaining layers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_04107 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Depth-13 Sorting Networks for 28 Channels Wang, Chengu Data Structures and Algorithms Discrete Mathematics We establish new depth upper bounds for sorting networks on 27 and 28 channels, improving the previous best bound of 14 to 13. Our 28-channel network is constructed with reflectional symmetry by combining high-quality prefixes of 16- and 12-channel networks, extending them greedily one comparator at a time, and using a SAT solver to complete the remaining layers. |
| title | Depth-13 Sorting Networks for 28 Channels |
| topic | Data Structures and Algorithms Discrete Mathematics |
| url | https://arxiv.org/abs/2511.04107 |