Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework

This article presents a framework, Genesis (genome analysis), to efficiently and flexibly accelerate generic data manipulation operations that have become performance bottlenecks in the genomic data processing pipeline utilizing FPGAs-as-a-service. Genesis conceptualizes genomic data as a very large...

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Bibliographic Details
Published in:IEEE MICRO 2021-05, Vol.41 (3), p.42-49
Main Authors: Ham, Tae Jun, Lee, Yejin, Seo, Seong Hoon, Song, U Gyeong, Lee, Jae W., Bruns-Smith, David, Sweeney, Brendan, Asanovic, Krste, Oh, Young H., Wills, Lisa Wu
Format: Article
Language:English
Subjects:
Bioinformatics
Computer Science
Data analysis
Data processing
DNA
Domain specific languages
Genomics
Hardware
Hardware acceleration
Micromechanical devices
Queries
Query languages
Relational data bases
Relational databases
Structured Query Language
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Summary:This article presents a framework, Genesis (genome analysis), to efficiently and flexibly accelerate generic data manipulation operations that have become performance bottlenecks in the genomic data processing pipeline utilizing FPGAs-as-a-service. Genesis conceptualizes genomic data as a very large relational database and uses extended SQL as a domain-specific language to construct data manipulation queries. To accelerate the queries, we designed a Genesis hardware library of efficient coarse-grained primitives that can be composed into a specialized dataflow architecture. This approach explores a systematic and scalable methodology to expedite domain-specific end-to-end accelerated system development and deployment.
ISSN:0272-1732
1937-4143
DOI:10.1109/MM.2021.3072385