Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework
| Autor: | Krste Asanovic, Tae Jun Ham, Brendan Sweeney, Seong Hoon Seo, Jae W. Lee, David Bruns-Smith, U Gyeong Song, Yejin Lee, Young H. Oh, Lisa Wu Wills |
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| Rok vydání: | 2021 |
| Předmět: |
Domain-specific language
SQL business.industry Relational database Computer science Data manipulation language 02 engineering and technology Pipeline (software) 020202 computer hardware & architecture Hardware and Architecture Analytics 0202 electrical engineering electronic engineering information engineering Hardware acceleration Electrical and Electronic Engineering Software engineering business computer Software Dataflow architecture computer.programming_language |
| Zdroj: | IEEE Micro. 41:42-49 |
| ISSN: | 1937-4143 0272-1732 |
| DOI: | 10.1109/mm.2021.3072385 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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