| Cache-oblivious streaming B-trees |
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ACM Symposium on Parallel Algorithms and Architectures
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Proceedings of the nineteenth annual ACM symposium on Parallel algorithms and architectures
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San Diego, California, USA
SESSION: Cache-oblivious/cache-aware algorithms
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Pages: 81 - 92
Year of Publication: 2007
ISBN:978-1-59593-667-7
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Authors
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Michael A. Bender
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Stony Brook University, Stony Brook, NY
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Martin Farach-Colton
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Rutgers University, Piscataway, NJ
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Jeremy T. Fineman
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MIT CSAIL, Cambridge, MA
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Yonatan R. Fogel
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Stony Brook University, Stony Brook, NY
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Bradley C. Kuszmaul
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MIT CSAIL, Cambridge, MA
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Jelani Nelson
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MIT CSAIL, Cambridge, MA
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Downloads (6 Weeks): 19, Downloads (12 Months): 125, Citation Count: 1
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ABSTRACT
A streaming B-tree is a dictionary that efficiently implements insertions and range queries. We present two cache-oblivious streaming B-trees, the shuttle tree, and the cache-oblivious lookahead array (COLA). For block-transfer size B and on N elements, the shuttle tree implements searches in optimal O(log B+1N) transfers, range queries of L successive elements in optimal O(log B+1N +L/B) transfers, and insertions in O((log B+1N)/BΘ(1/(log log B)2)+(log2N)/B) transfers, which is an asymptotic speedup over traditional B-trees if B ≥ (log N)1+c log log log2 N for any constant c >1. A COLA implements searches in O(log N) transfers, range queries in O(log N + L/B) transfers, and insertions in amortized O((log N)/B) transfers, matching the bounds for a (cache-aware) buffered repository tree. A partially deamortized COLA matches these bounds but reduces the worst-case insertion cost to O(log N) if memory size M = Ω(log N). We also present a cache-aware version of the COLA, the lookahead array, which achieves the same bounds as Brodal and Fagerberg's (cache-aware) Bε-tree. We compare our COLA implementation to a traditional B-tree. Our COLA implementation runs 790 times faster for random inser-tions, 3.1 times slower for insertions of sorted data, and 3.5 times slower for searches.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Lars Arge , Michael A. Bender , Erik D. Demaine , Bryan Holland-Minkley , J. Ian Munro, Cache-oblivious priority queue and graph algorithm applications, Proceedings of the thiry-fourth annual ACM symposium on Theory of computing, May 19-21, 2002, Montreal, Quebec, Canada
[doi> 10.1145/509907.509950]
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3
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4
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R. Bayer and E. M. McCreight. Organization and maintenance of large ordered indexes. Acta Inf., 1(3):173--189, Feb. 1972.
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5
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6
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7
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8
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9
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J. L. Bentley and J. B. Saxe. Decomposable searching problems i: Static-to-dynamic transformation. J. Algorithms, 1(4):301--358, 1980.
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10
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11
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12
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Adam L. Buchsbaum , Michael Goldwasser , Suresh Venkatasubramanian , Jeffery R. Westbrook, On external memory graph traversal, Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms, p.859-860, January 09-11, 2000, San Francisco, California, United States
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13
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B. Chazelle and L. J. Guibas. Fractional cascading: I. a data structuring technique. Algorithmica, 1(2):133--162, 1986.
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14
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| |
15
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16
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I. Katriel. Implicit data structures based on local reorganizations. Master's thesis, Technion, Israel Inst. of Tech., Haifa, May 2002.
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17
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D. E. Knuth. Sorting and Searching, volume 3 of The Art of Computer Programming. Addison-Wesley, Reading, Massachusetts, 1973.
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18
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|
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19
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20
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H. Prokop. Cache-oblivious algorithms. Master's thesis, Department of Electrical Engineering and Computer Science, Massachusetts Inst. of Tech., June 1999.
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21
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Sleepycat Software. The Berkeley Database. http://www.sleepycat.com, 2005.
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CITED BY
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Andrew W. Leung , Minglong Shao , Timothy Bisson , Shankar Pasupathy , Ethan L. Miller, Spyglass: fast, scalable metadata search for large-scale storage systems, Proccedings of the 7th conference on File and stroage technologies, p.153-166, February 24-27, 2009, San Francisco, California
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