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Cited by 4Parallel Computing and Optimization TechniquesGenomics and Phylogenetic StudiesDistributed and Parallel Computing Systems

Large-Scale Neo-Heterogeneous Programming and Optimization of SNP Detection on Tianhe-2

Cui, Yingbo, Liao, Xiangke, Peng, Shaoliang, Lu, Yutong, Yang, Canqun, Wang, Bingqiang, Wu, Chengkun·2015·Lecture Notes in Computer Science
DOI 10.1007/978-3-319-20119-1_6
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Crossref · 10.1007/978-3-319-20119-1_6

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  • Tools like SOAP leverage hashing for rapid identification of potential SNP locations via quickly mapping reads to the reference genome.

    “Tools like SOAP leverage hashing for rapid identification of potential SNP locations via quickly mapping reads to the reference genome [54], a process integral to variant calling and genotyping studies;”

    From Whole-Genome Alignment: Methods, Challenges, and Future Directions (2024) · cites this paper as [54]

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Authors
Cui, Y., Liao, X., Peng, S., Lu, Y., Yang, C., Wang, B., & Wu, C.
Affiliations
  • National University of Defense Technology (CN)
  • National Supercomputing Center in Shenzhen (CN)
Corresponding author
Peng, Shaoliang
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer International Publishing
Published
2015
Pages
74-86
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/978-3-319-20119-1_6
OpenAlex
W788383209
Cited by
4
References
0
Citations by year
2024: 1 · 2019: 1 · 2018: 1 · 2017: 1
FWCI
0.44
Type
conference paper
Language
en
Open access
closed
Licence
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Computer Science › Computer Networks and Communications › Distributed and Parallel Computing Systems
Keywords
SNP detection, Tianhe-2, Intel Xeon Phi, CPU-GPU heterogeneous computing, memory cost reduction, scalability, human genome

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