# Hardware-Accelerated Data Readout Platform Using Heterogeneous Computing for DNA Data Storage
## 6 Experimental Results and Analysis
### Readout Performance Analysis  
To further evaluate the capability of the proposed heterogeneous acceleration system for DNA data storage, we performed recovery tests under varying error rates and sequencing coverages. First, the hardware acceleration platform was built using a data-center-grade FPGA, specifically, an Alveo U200 series card. Host-side development was carried out using the Vitis unified software platform. The host server was equipped with an Intel Xeon(r) Gold 5220R CPU (2.2 GHz) featuring 96 cores and 256 GB of memory.  
Figure 11: Proportions of correct primer sequence identification, passed index checks, and correctly matched reads at different base error rates.  
Then, a channel simulation model was developed to emulate sequencing data with varying error rates. The model incorporated insertion, deletion, and substitution errors (\(P_{i},\ P_{d},\ \text{and}\ P_{s}\), respectively) to reflect common sequencing noise. It also included an average coverage parameter to model sequencing depth. The number of DNA molecule copies generated during sequencing was simulated using a Poisson distribution. A mutation probability \(P_{\text{sum}}=P_{i}+P_{d}+P_{s}\) was defined to represent the overall error intensity.  
Figure 12 illustrates the data recovery performance under realistic conditions based on the proposed channel simulation model. Multiple datasets were generated using random input data under varying coverage and error scenarios. At a fixed coverage of 15x, four base error rates (1.2%, 1.5%, 1.8%, and 2.1%) were simulated. When the error rate was below 1.5%, the codeword error rate after majority voting remained within the error-correction capability of the LDPC decoder. However, at 1.8%, the codeword error rate increased to 1.9%, exceeding the correction limit and resulting in decoding failure. Additionally, at a 1% error rate, recovery was tested at coverages of 7x, 8x, 9x, and 10x. As the coverage increased to 9x, the codeword error rate decreased to within the correctable range.  
Figure 13 shows the performance of the proposed heterogeneous computing system against a pure software implementation. Under average sequencing coverages of 15x and 25x, 100 independent experiments were conducted for both implementations across varying error rates. The experimental results show that error-free recovery was achieved at 15x coverage under a maximum base error rate of 1.5%, and at 25x coverage under a maximum base error rate of 2%. Furthermore, the hardware-accelerated heterogeneous solution exhibited readout performance comparable to that of its software counterpart. These findings confirmed the effectiveness and reliability of the proposed system under typical sequencing error conditions.  
Figure 14 shows the impact of increasing sequencing coverage under a fixed base error rate of 1%. The results indicate that, at this error rate, the proposed heterogeneous platform could achieve error-free data recovery with a minimum coverage of 10x. To further verify the performance of the proposed heterogeneous system in the second-generation high-throughput sequencing scenario, we generated simulation data according to the Illumina sequencing error rate reported by [PERSON] et al. [10]. The results demonstrate that, under this realistic error model, the proposed system can still achieve error-free recovery with a minimum coverage of 8x. This indicates its effectiveness in handling typical errors in second-generation high-throughput DNA sequencing. Moreover, the readout reliability provided by the hardware-accelerated design is comparable to that of the software implementation.  
Figure 12: Error rates after majority voting. (**a**) Codeword error rates under varying base error rates. (**b**) Codeword error rates under varying coverage.