AnySeq/GPU: a novel approach for faster sequence alignment on GPUs

DOI:	https://doi.org/10.1145/3524059.3532376
URL:	https://dl.acm.org/doi/10.1145/3524059.3532376
Document Type:	Conference or workshop publication
Year of publication:	2022
Book title:	Proceedings of the 36th ACM International Conference on Supercomputing (ICS' 22)
Page range:	1-11
Conference title:	CS '22: 2022 International Conference on Supercomputing
Location of the conference venue:	New York, NY, Online
Date of the conference:	28.-30.06.2022
Publisher:	Rauchwerger, Lawrence ; Cameron, Kirk
Place of publication:	New York
Publishing house:	Association for Computing Machinery
ISBN:	978-1-4503-9281-5
Related URLs:	https://www.researchgate.net/publication... https://dl.acm.org/doi/proceedings/10.11...
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Programmiersprachen und Compilerdesign (Juniorprofessur) (Leißa 2021-)
Subject:	004 Computer science, internet

Dieser Eintrag ist Teil der Universitätsbibliographie.

BASE: Müller, André ; Schmidt, Bertil ; Membarth, Richard ; Leißa, Roland ; Hack, Sebastian

Google Scholar: Müller, André ; Schmidt, Bertil ; Membarth, Richard ; Leißa, Roland ; Hack, Sebastian

ORCID: Müller, André ; Schmidt, Bertil ; Membarth, Richard ; Leißa, Roland

; Hack, Sebastian

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