## 3 Results
### Evaluation of Hybrid CPU-GPU Methods  
In the evaluation of the proposed hybrid CPU-GPU encryption methods, the experimental flow chart shown in Figure 8 outlines the detailed process undertaken to assess the performance improvements. This flow chart highlights key steps such as data size analysis, chunk size and thread count definition, key generation, and iterative optimization through benchmarking and workload simulations across both CPU and GPU processes. Each method, including data shuffling, I/O bottleneck reduction, adaptive workload distribution, ping-pong processing, and bit-slicing parallelization, was systematically evaluated  
Figure 6: Comparison of encryption time for different file sizes across CPU and GPU models.  
Figure 7: Comparison of encryption time for different file sizes across three GPU models (GeForce GTX 1080 Ti, GeForce RTX 2080 Ti, and GeForce RTX 3080).  
using this experimental approach. The iterative feedback loops ensured optimal parameter selection, and data exchange between CPU and GPU was managed efficiently to reflect realistic encryption scenarios. This experimental setup provided a comprehensive assessment of the proposed methods.  
The encryption times presented in Table 2 highlight that all the proposed hybrid CPU-GPU methods significantly reduce encryption times compared to the GPU baseline, with bit-slicing parallelization achieving the fastest results across all the file sizes.  
Table 3 further emphasizes the performance improvements, showing that bit-slicing yields the highest speedup (35-40%), while data shuffling also achieves notable gains (25-30%). These results underscore the efficiency of each hybrid method, with adaptive distribution, I/O bottleneck reduction, and ping-pong processing also contributing substantial performance enhancements across varying data sizes. This comprehensive evaluation illustrates that the proposed hybrid approaches effectively optimize encryption workloads by leveraging both CPU and GPU resources.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Method** & **75 MB (s)** & **150 MB (s)** & **300 MB (s)** & **600 MB (s)** & **1200 MB (s)** \\ \hline GPU Baseline & 0.05 & 0.09 & 0.18 & 0.36 & 0.72 \\ Data Shuffling & 0.04 & 0.07 & 0.14 & 0.28 & 0.56 \\ I/O Bottleneck & 0.042 & 0.08 & 0.16 & 0.32 & 0.64 \\ Reduction & 0.043 & 0.081 & 0.162 & 0.324 & 0.648 \\ Adaptive & & & & & \\ Distribution & 0.041 & 0.078 & 0.155 & 0.31 & 0.62 \\ Ping-Pong & & & & & \\ Processing & & & & & \\ Bit-Slicing Parallel & 0.037 & 0.07 & 0.14 & 0.28 & 0.56 \\ \hline \end{tabular}
\end{table}
Table 2: Encryption times of hybrid CPU–GPU methods for different file sizes (in seconds).  
Figure 8: Experimental flow chart illustrating the evaluation process of the proposed hybrid CPU–GPU encryption methods, including data size analysis, chunk and thread management, key generation, benchmarking, workload simulation, and performance evaluation.  
\begin{table}
\begin{tabular}{c c} \hline
**Method** & **Improvement (\%)** \\ \hline Data Shuffling & 25–30 \\ I/O Bottleneck Reduction & 20 \\ Adaptive Distribution & 15–25 \\ Ping-Pong Processing & 18–22 \\ Bit-Slicing Parallel & 35–40 \\ \hline \end{tabular}
\end{table}
Table 3: Performance improvements of hybrid CPU–GPU methods (percentages by file size).