TY - GEN
T1 - Seedex
T2 - 53rd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2020
AU - Fujiki, Daichi
AU - Wu, Shunhao
AU - Ozog, Nathan
AU - Goliya, Kush
AU - Blaauw, David
AU - Narayanasamy, Satish
AU - Das, Reetuparna
N1 - Funding Information:
ACKNOWLEDGMENT We thank the anonymous reviewers for their suggestions which helped improve this paper. This work was supported in part by the NSF under the CAREER-1652294 award and the Applications Driving Architectures (ADA) Research Center, a JUMP Center co-sponsored by SRC and DARPA.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - Innovations in genome sequencing techniques are enabling remarkably fast and low cost production of raw genome data. As Moore's law tapers off, bottlenecks in genome sequencing are shifting to computational resources for mapping reads to reference DNA. This paper presents SeedEx, a read-alignment accelerator focused on the seed-extension step. SeedEx is based on the observation that only a small fraction of reads require large edit distance for alignment, hence an area efficient narrow-band seed-extension accelerator can suffice in practice. However, due to the highly error-sensitive nature of genomic workloads, guaranteeing optimality of alignment result is of cardinal importance. Towards this end, we propose a speculation-and-test based framework by using strict but powerful optimality checking mechanisms. We demonstrate SeedEx by an implementation on a cloud FPGA. SeedEx achieves 6.0× iso-area throughput speedup when compared to a banded Smith-Waterman baseline, and achieving 43.9 M seed extentions/s on AWS f1.2xlarge instance. Integration with BWA-MEM2 improves the execution time by 2.3×.
AB - Innovations in genome sequencing techniques are enabling remarkably fast and low cost production of raw genome data. As Moore's law tapers off, bottlenecks in genome sequencing are shifting to computational resources for mapping reads to reference DNA. This paper presents SeedEx, a read-alignment accelerator focused on the seed-extension step. SeedEx is based on the observation that only a small fraction of reads require large edit distance for alignment, hence an area efficient narrow-band seed-extension accelerator can suffice in practice. However, due to the highly error-sensitive nature of genomic workloads, guaranteeing optimality of alignment result is of cardinal importance. Towards this end, we propose a speculation-and-test based framework by using strict but powerful optimality checking mechanisms. We demonstrate SeedEx by an implementation on a cloud FPGA. SeedEx achieves 6.0× iso-area throughput speedup when compared to a banded Smith-Waterman baseline, and achieving 43.9 M seed extentions/s on AWS f1.2xlarge instance. Integration with BWA-MEM2 improves the execution time by 2.3×.
KW - Accelerator
KW - FPGA
KW - Genome sequencing
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U2 - 10.1109/MICRO50266.2020.00080
DO - 10.1109/MICRO50266.2020.00080
M3 - Conference contribution
AN - SCOPUS:85097339405
T3 - Proceedings of the Annual International Symposium on Microarchitecture, MICRO
SP - 937
EP - 950
BT - Proceedings - 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2020
PB - IEEE Computer Society
Y2 - 17 October 2020 through 21 October 2020
ER -