A Memory-Efficient FM-Index Constructor for Next-Generation Sequencing Applications on FPGAs Article Swipe
Nae-Chyun Chen
,
Yucheng Li
,
Yi-Chang Lu
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1109/iscas.2018.8350897
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1109/iscas.2018.8350897
FM-index is an efficient data structure for string search and is widely used in next-generation sequencing (NGS) applications such as sequence alignment and de novo assembly. Recently, FM-indexing is even performed down to the read level, raising a demand of an efficient algorithm for FM-index construction. In this work, we propose a hardware-compatible Self-Aided Incremental Indexing (SAII) algorithm and its hard-ware architecture. This novel algorithm builds FM-index with no memory overhead, and the hardware system for realizing the algorithm can be very compact. Parallel architecture and a special prefetch controller is designed to enhance computational efficiency. An SAII-based FM-index constructor is implemented on an Altera Stratix V FPGA board. The presented constructor can support DNA sequences of sizes up to 131,072-bp, which is enough for small-scale references and reads obtained from current major platforms. Because the proposed constructor needs very few hardware resource, it can be easily integrated into different hardware accelerators designed for FM-index-based applications.
Related Topics
Concepts
Stratix
Computer science
Instruction prefetch
Field-programmable gate array
Search engine indexing
Index (typography)
Overhead (engineering)
String searching algorithm
Parallel computing
Computer hardware
Embedded system
Computer architecture
Data structure
Operating system
Programming language
Information retrieval
Cache
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/iscas.2018.8350897
- https://ieeexplore.ieee.org/ielx7/8334884/8350884/08350897.pdf
- OA Status
- gold
- Cited By
- 5
- References
- 11
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2800798181
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2800798181Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/iscas.2018.8350897Digital Object Identifier
- Title
-
A Memory-Efficient FM-Index Constructor for Next-Generation Sequencing Applications on FPGAsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-05-01Full publication date if available
- Authors
-
Nae-Chyun Chen, Yucheng Li, Yi-Chang LuList of authors in order
- Landing page
-
https://doi.org/10.1109/iscas.2018.8350897Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/8334884/8350884/08350897.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/8334884/8350884/08350897.pdfDirect OA link when available
- Concepts
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Stratix, Computer science, Instruction prefetch, Field-programmable gate array, Search engine indexing, Index (typography), Overhead (engineering), String searching algorithm, Parallel computing, Computer hardware, Embedded system, Computer architecture, Data structure, Operating system, Programming language, Information retrieval, CacheTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2021: 2, 2020: 3Per-year citation counts (last 5 years)
- References (count)
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11Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.compact. | 82 |
| abstract_inverted_index.designed | 91, 152 |
| abstract_inverted_index.hardware | 73, 141, 150 |
| abstract_inverted_index.obtained | 129 |
| abstract_inverted_index.prefetch | 88 |
| abstract_inverted_index.proposed | 136 |
| abstract_inverted_index.sequence | 20 |
| abstract_inverted_index.Recently, | 26 |
| abstract_inverted_index.algorithm | 42, 57, 64, 78 |
| abstract_inverted_index.alignment | 21 |
| abstract_inverted_index.assembly. | 25 |
| abstract_inverted_index.different | 149 |
| abstract_inverted_index.efficient | 3, 41 |
| abstract_inverted_index.hard-ware | 60 |
| abstract_inverted_index.overhead, | 70 |
| abstract_inverted_index.performed | 30 |
| abstract_inverted_index.presented | 110 |
| abstract_inverted_index.realizing | 76 |
| abstract_inverted_index.resource, | 142 |
| abstract_inverted_index.sequences | 115 |
| abstract_inverted_index.structure | 5 |
| abstract_inverted_index.SAII-based | 97 |
| abstract_inverted_index.Self-Aided | 53 |
| abstract_inverted_index.controller | 89 |
| abstract_inverted_index.integrated | 147 |
| abstract_inverted_index.platforms. | 133 |
| abstract_inverted_index.references | 126 |
| abstract_inverted_index.sequencing | 15 |
| abstract_inverted_index.131,072-bp, | 120 |
| abstract_inverted_index.FM-indexing | 27 |
| abstract_inverted_index.Incremental | 54 |
| abstract_inverted_index.constructor | 99, 111, 137 |
| abstract_inverted_index.efficiency. | 95 |
| abstract_inverted_index.implemented | 101 |
| abstract_inverted_index.small-scale | 125 |
| abstract_inverted_index.accelerators | 151 |
| abstract_inverted_index.applications | 17 |
| abstract_inverted_index.architecture | 84 |
| abstract_inverted_index.applications. | 155 |
| abstract_inverted_index.architecture. | 61 |
| abstract_inverted_index.computational | 94 |
| abstract_inverted_index.construction. | 45 |
| abstract_inverted_index.FM-index-based | 154 |
| abstract_inverted_index.next-generation | 14 |
| abstract_inverted_index.hardware-compatible | 52 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 93 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.79513528 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |