TY - GEN
T1 - GenAx
T2 - 45th ACM/IEEE Annual International Symposium on Computer Architecture, ISCA 2018
AU - Fujiki, Daichi
AU - Subramaniyan, Arun
AU - Zhang, Tianjun
AU - Zeng, Yu
AU - Das, Reetuparna
AU - Blaauw, David
AU - Narayanasamy, Satish
N1 - Funding Information:
We thank our shepherd Mark Oskin and the anonymous reviewers for their suggestions which helped improved this paper. This work was supported in part by NSF CAREER-1149773, CAREER-1652294 and SHF-1527301 awards.
Funding Information:
ACKNOWLEDGMENT We thank our shepherd Mark Oskin and the anonymous reviewers for their suggestions which helped improved this paper. This work was supported in part by NSF CAREER-1149773, CAREER-1652294 and SHF-1527301 awards.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/19
Y1 - 2018/7/19
N2 - Genomics can transform health-care through precision medicine. Plummeting sequencing costs would soon make genome testing affordable to the masses. Compute efficiency, however, has to improve by orders of magnitude to sequence and analyze the raw genome data. Sequencing software used today can take several hundreds to thousands of CPU hours to align reads to a reference sequence. This paper presents GenAx, an accelerator for read alignment, a time-consuming step in genome sequencing. It consists of a seeding and seed-extension accelerator. The latter is based on an innovative automata design that was designed from the ground-up to enable hardware acceleration. Unlike conventional Levenshtein automata, it is string independent and scales quadratically with edit distance, instead of string length. It supports critical features commonly used in sequencing such as affine gap scoring and traceback. GenAx provides a throughput of 4,058K reads/s for Illumina 101 bp reads. GenAx achieves 31.7× speedup over the standard BWA-MEM sequence aligner running on a 56-thread dual-socket 14-core Xeon E5 server processor, while reducing power consumption by 12× and area by 5.6×.
AB - Genomics can transform health-care through precision medicine. Plummeting sequencing costs would soon make genome testing affordable to the masses. Compute efficiency, however, has to improve by orders of magnitude to sequence and analyze the raw genome data. Sequencing software used today can take several hundreds to thousands of CPU hours to align reads to a reference sequence. This paper presents GenAx, an accelerator for read alignment, a time-consuming step in genome sequencing. It consists of a seeding and seed-extension accelerator. The latter is based on an innovative automata design that was designed from the ground-up to enable hardware acceleration. Unlike conventional Levenshtein automata, it is string independent and scales quadratically with edit distance, instead of string length. It supports critical features commonly used in sequencing such as affine gap scoring and traceback. GenAx provides a throughput of 4,058K reads/s for Illumina 101 bp reads. GenAx achieves 31.7× speedup over the standard BWA-MEM sequence aligner running on a 56-thread dual-socket 14-core Xeon E5 server processor, while reducing power consumption by 12× and area by 5.6×.
KW - Accelerator
KW - Automaton
KW - Sequence alignment
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U2 - 10.1109/ISCA.2018.00017
DO - 10.1109/ISCA.2018.00017
M3 - Conference contribution
AN - SCOPUS:85055865368
T3 - Proceedings - International Symposium on Computer Architecture
SP - 69
EP - 82
BT - Proceedings - 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture, ISCA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 June 2018 through 6 June 2018
ER -