Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage
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 propo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/9/5050 |
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| author | Xiaopeng Gou Qi Ge Quan Guo Menghui Ren Tingting Qi Rui Qin Weigang Chen |
| author_facet | Xiaopeng Gou Qi Ge Quan Guo Menghui Ren Tingting Qi Rui Qin Weigang Chen |
| author_sort | Xiaopeng Gou |
| collection | DOAJ |
| description | 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 15×), 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. |
| format | Article |
| id | doaj-art-007696c22dae4512a74514d2af2abd91 |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-007696c22dae4512a74514d2af2abd912025-08-20T03:52:56ZengMDPI AGApplied Sciences2076-34172025-05-01159505010.3390/app15095050Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data StorageXiaopeng Gou0Qi Ge1Quan Guo2Menghui Ren3Tingting Qi4Rui Qin5Weigang Chen6School of Microelectronics, Tianjin University, Tianjin 300072, ChinaSchool of Microelectronics, Tianjin University, Tianjin 300072, ChinaSchool of Microelectronics, Tianjin University, Tianjin 300072, ChinaSchool of Microelectronics, Tianjin University, Tianjin 300072, ChinaSchool of Microelectronics, Tianjin University, Tianjin 300072, ChinaSchool of Microelectronics, Tianjin University, Tianjin 300072, ChinaSchool of Microelectronics, Tianjin University, Tianjin 300072, ChinaDNA 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 15×), 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.https://www.mdpi.com/2076-3417/15/9/5050heterogeneous computingDNA data storagehardware accelerationFPGA |
| spellingShingle | Xiaopeng Gou Qi Ge Quan Guo Menghui Ren Tingting Qi Rui Qin Weigang Chen Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage Applied Sciences heterogeneous computing DNA data storage hardware acceleration FPGA |
| title | Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage |
| title_full | Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage |
| title_fullStr | Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage |
| title_full_unstemmed | Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage |
| title_short | Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage |
| title_sort | hardware accelerated data readout platform using heterogeneous computing for dna data storage |
| topic | heterogeneous computing DNA data storage hardware acceleration FPGA |
| url | https://www.mdpi.com/2076-3417/15/9/5050 |
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