Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage

被引:0
作者
Gou, Xiaopeng [1 ]
Ge, Qi [1 ]
Guo, Quan [1 ]
Ren, Menghui [1 ]
Qi, Tingting [1 ]
Qin, Rui [1 ]
Chen, Weigang [1 ,2 ,3 ]
机构
[1] Tianjin Univ, Sch Microelect, Tianjin 300072, Peoples R China
[2] Tianjin Univ, State Key Lab Synthet Biol, Tianjin 300072, Peoples R China
[3] Tianjin Univ, Frontier Sci Ctr Synthet Biol, Minist Educ, Tianjin 300072, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2025年 / 15卷 / 09期
关键词
heterogeneous computing; DNA data storage; hardware acceleration; FPGA; DIGITAL INFORMATION; LDPC; ARCHITECTURE; ALGORITHM; ROBUST; ACCESS;
D O I
10.3390/app15095050
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
DNA data storage has emerged as a promising alternative to traditional storage media due to its high density and durability. However, large-scale DNA storage systems generate massive sequencing reads, posing substantial computational complexity and latency challenges for data readout. Here, we propose a novel heterogeneous computing architecture based on a field-programmable gate array (FPGA) to accelerate DNA data readout. The software component, running on a general computing platform, manages data distribution and schedules acceleration kernels. Meanwhile, the hardware acceleration kernel is deployed on an Alveo U200 data center accelerator card, executing multiple logical computing units within modules and utilizing task-level pipeline structures between modules to handle sequencing reads step by step. This heterogeneous computing acceleration system enables the efficient execution of the entire readout process for DNA data storage. We benchmark the proposed system against a CPU-based software implementation under various error rates and coverages. The results indicate that under high-error, low-coverage conditions (error rate of 1.5% and coverage of 15x), the accelerator achieves a peak speedup of up to 373.1 times, enabling the readout of 59.4 MB of stored data in just 12.40 s. Overall, the accelerator delivers a speedup of two orders of magnitude. Our proposed heterogeneous computing acceleration strategy provides an efficient solution for large-scale DNA data readout.
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页数:19
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