Heterogeneous Gene Sequence Alignment System Based on 12-GHz Superconducting Chip

Due to power consumption and speed limitations, the development of CMOS-based large-scale integrated circuits has stagnated in the post-Moore era. While superconducting digital integrated circuit is a promising solution due to its low power consumption and latency. However, the lack of large-scale cryogenic storage units prevents most superconducting chips from being deployed in practical applications. To fully utilize the advantages of superconducting chips and successfully apply them in processing large datasets, we propose a novel heterogeneous processor based on CMOS-based circuits and superconducting chips for processing pattern-matching tasks. In our proposed architecture, a novel communication architecture that enables high-speed, reliable communication between 12 GHz superconducting chips and CMOS circuits is proposed. The hardware overhead for high-speed communication in superconducting chips can be minimized by this approach. In addition, the data communication rate of a single channel can reach 12 Gbps. Simultaneously, we present a 12 GHz, large-scale superconducting chip with 6286 Josephson Junctions that can perform 16-bit pattern matching using the SIMIT-Nb03 process. We have successfully applied our proposed heterogeneous processor to the gene sequence alignment. The processor that uses only one superconducting chip has a throughput of 1.5 Gbp/s (billion base pairs per second), whereas a processor with two superconducting chips has 3 Gbp/s.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Applied Superconductivity
Published
2024-09-16
DOI
https://doi.org/10.1109/tasc.2024.3461236
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Heterogeneous Gene Sequence Alignment System Based on 12-GHz Superconducting Chip

Pei-Yao Qu, Guang-Ming Tang, Gang Chen, Chenbo Yuan et al.
1 links
IEEE Transactions on Applied Superconductivity
Gene expression and cancer classification
article

Heterogeneous Gene Sequence Alignment System Based on 12-GHz Superconducting Chip

Pei-Yao Qu, Guang-Ming Tang, Gang Chen, Chenbo Yuan, Huanli Liu, Lingyun Li, Z.K. Jiang, Tianhang Liang
article en

Abstract

Due to power consumption and speed limitations, the development of CMOS-based large-scale integrated circuits has stagnated in the post-Moore era. While superconducting digital integrated circuit is a promising solution due to its low power consumption and latency. However, the lack of large-scale cryogenic storage units prevents most superconducting chips from being deployed in practical applications. To fully utilize the advantages of superconducting chips and successfully apply them in processing large datasets, we propose a novel heterogeneous processor based on CMOS-based circuits and superconducting chips for processing pattern-matching tasks. In our proposed architecture, a novel communication architecture that enables high-speed, reliable communication between 12 GHz superconducting chips and CMOS circuits is proposed. The hardware overhead for high-speed communication in superconducting chips can be minimized by this approach. In addition, the data communication rate of a single channel can reach 12 Gbps. Simultaneously, we present a 12 GHz, large-scale superconducting chip with 6286 Josephson Junctions that can perform 16-bit pattern matching using the SIMIT-Nb03 process. We have successfully applied our proposed heterogeneous processor to the gene sequence alignment. The processor that uses only one superconducting chip has a throughput of 1.5 Gbp/s (billion base pairs per second), whereas a processor with two superconducting chips has 3 Gbp/s.

IEEE Transactions on Applied SuperconductivityVol. 34(9)
Chinese Academy of Sciences (CN), Institute of Computing Technology (CN), Shanghai Institute of Microsystem and Information Technology (CN), Institute of Semiconductors (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 86%
Gene expression and cancer classification
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.