An efficient method for in memory construction of suffix arrays

Itoh, Hidenori; Tanaka, Hiromi T.

doi:10.1109/spire.1999.796581

Cited by 44 publications

(44 citation statements)

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“…• DivSufSort by Yuta Mori is an optimized implementation of the two-stage algorithm [IT99]. DivSufSort is one of the fastest SACA for byte alphabets.…”

Section: Notable Implementationsmentioning

confidence: 99%

“…Using parallelRange we can parallelize the DivSufSort implementation by Mori of the twostage algorithm [IT99]. In this section we will first give an overview over our parallel DivSufSort algorithm.…”

Section: Parallel Divsufsortmentioning

confidence: 99%

“…Then we show how to parallelize induced sorting for byte alphabets in polylogarithmic depth. Finally we combine both techniques to generate a parallel version of the two-stage algorithm [IT99]. In the experimental evaluation we will see that the proposed algorithm uses very little additional space and is one of the fastest parallel suffix array construction algorithms on byte alphabets.…”

Section: Introductionmentioning

confidence: 99%

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Parallel Lightweight Wavelet Tree, Suffix Array and FM-Index Construction

Labeit

Shun

Blelloch

2016

2016 Data Compression Conference (DCC)

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“…• DivSufSort by Yuta Mori is an optimized implementation of the two-stage algorithm [IT99]. DivSufSort is one of the fastest SACA for byte alphabets.…”

Section: Notable Implementationsmentioning

confidence: 99%

Section: Parallel Divsufsortmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Parallel Lightweight Wavelet Tree, Suffix Array and FM-Index Construction

Labeit

Shun

Blelloch

2016

2016 Data Compression Conference (DCC)

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“…Induced copying SACAs are currently the fastest CPU implementations and we compare our results with the best one, libdivsufsort. To illustrate this approach, we describe the method of Itoh and Tanaka [25], two stage induced copying.…”

Section: Induced Copyingmentioning

confidence: 99%

Fast parallel skew and prefix‐doubling suffix array construction on the GPU

Wang

Baxter

Owens

2016

Concurrency and Computation

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Summary Suffix arrays are fundamental full‐text index data structures of importance to a broad spectrum of applications in such fields as bioinformatics, Burrows–Wheeler transform‐based lossless data compression, and information retrieval. In this work, we propose and implement two massively parallel approaches on the graphics processing unit (GPU) based on two classes of suffix array construction algorithms. The first, parallel skew, makes algorithmic improvements to the previous work of Deo and Keely to achieve a speedup of 1.45x over their work. The second, a hybrid skew and prefix‐doubling implementation, is the first of its kind on the GPU and achieves a speedup of 2.3–4.4x over Osipov's prefix‐doubling and 2.4–7.9x over our skew implementation on large datasets. Our implementations rely on two efficient parallel primitives, a merge and a segmented sort. We theoretically analyze the two formulations of suffix array construction algorithms and show performance comparisons on a large variety of practical inputs. We conclude that, with the novel use of our efficient segmented sort, prefix‐doubling is more competitive than skew on the GPU. We also demonstrate the effectiveness of our methods in our implementations of the Burrows‐Wheeler transform and in a parallel full‐text, minute‐space‐index for pattern searching. Copyright © 2016 John Wiley & Sons, Ltd.

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“…In 2003, three papers were published [58,75,26] that describe a worst-case linear time construction of a suffix array without the need of an initial construction of the respective suffix tree. Other algorithms for constructing suffix arrays can be found in [17,36,47,55,68]. Moreover, a recent line of research concerns compressed suffix arrays [46,38,39,35].…”

Section: Lcp(t S a T [L]···n T S A T [M]···n ) And Lcp(t S A T [M]·mentioning

confidence: 99%