Algorithms for trie compaction
ACM Transactions on Database Systems (TODS)
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Journal of the ACM (JACM)
Text compression
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Stride directed prefetching in scalar processors
MICRO 25 Proceedings of the 25th annual international symposium on Microarchitecture
An efficient implementation of trie structures
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The art of computer programming, volume 3: (2nd ed.) sorting and searching
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Effective jump-pointer prefetching for linked data structures
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Cache-conscious structure layout
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Heuristics for trie index minimization
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A Space-Economical Suffix Tree Construction Algorithm
Journal of the ACM (JACM)
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ACM Computing Surveys (CSUR)
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Information Processing Letters
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VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
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FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
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Experimental algorithmics
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FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
Cache-conscious sorting of large sets of strings with dynamic tries
Journal of Experimental Algorithmics (JEA)
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ACM Transactions on Architecture and Code Optimization (TACO)
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SPIRE'05 Proceedings of the 12th international conference on String Processing and Information Retrieval
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Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
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Journal of Experimental Algorithmics (JEA)
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The Journal of Supercomputing
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Information Processing and Management: an International Journal
Engineering scalable, cache and space efficient tries for strings
The VLDB Journal — The International Journal on Very Large Data Bases
Redesigning the string hash table, burst trie, and BST to exploit cache
Journal of Experimental Algorithmics (JEA)
| Hi-index | 0.00 |
Tries are the fastest tree-based data structures for managing strings in-memory, but are space-intensive. The burst-trie is almost as fast but reduces space by collapsing trie-chains into buckets. This is not however, a cache-conscious approach and can lead to poor performance on current processors. In this paper, we introduce the HAT-trie, a cache-conscious trie-based data structure that is formed by carefully combining existing components. We evaluate performance using several real-world datasets and against other high-performance data structures. We show strong improvements in both time and space; in most cases approaching that of the cache-conscious hash table. Our HAT-trie is shown to be the most efficient trie-based data structure for managing variable-length strings in-memory while maintaining sort order.