AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping-Reference-Cited by-同舟云学术

AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping

Published:2024-02-20 Issue: Volume: Page:431-444
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Container-title:Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
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Author:

Park Seongyeon¹^ORCID,Hong Junguk²^ORCID,Song Jaeyong¹^ORCID,Kim Hajin³^ORCID,Kim Youngsok⁴^ORCID,Lee Jinho¹^ORCID

Affiliation:

1. Seoul National University, Seoul, Korea, South ? Republic of Korea

2. Seoul National University, Seoul, Republic of Korea

3. Yonsei University, Seoul, Republic of Korea

4. Yonsei University, Seoul, Korea, South ? Republic of Korea

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3627535.3638474

Reference59 articles.

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5. Muaaz G Awan, Jack Deslippe, Aydin Buluc, Oguz Selvitopi, Steven Hofmeyr, Leonid Oliker, and Katherine Yelick. 2020. ADEPT: A domain independent sequence alignment strategy for GPU architectures. BMC bioinformatics 21, 1 (2020), 1--29.