Accelerating Genomic Data Analytics With Composable Hardware Acceleration Framework
Tae Jun Ham, Yejin Lee, Seong Hoon Seo, Ui-Sung Song, Jae Wook Lee, David Bruns-Smith, Brendan Sweeney, Krste Asanović, Young H. Oh, Lisa Wu Wills · IEEE Micro · 2021
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.