This study investigates the optimization of authenticated encryption algorithms, focusing on ChaCha20 and Blake3. Our analysis demonstrates that the ChaCha20 single-threaded implementation achieves a notable 1.25× speedup over the libsodium library. The parallel version of ChaCha20 exhibits impressive scalability, reaching a peak throughput of 130 GB/s and showing linear speedups up to 32 threads, constrained by CPU memory bandwidth. In comparison, the Blake3 implementation, both single-threaded and parallelized, exhibits performance on par with the reference implementation. The stack approach for Blake3 offers substantial performance improvements over traditional methods, while the divide-and-conquer approach shows scalability with increasing core counts, promising efficiency for large-scale file sizes. Future research will explore advanced vectorization strategies, multi-CPU scalability, and thorough security analysis to further enhance performance and robustness.

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Optimizing Authenticated Encryption: Enhancements and Performance Analysis of ChaCha20 and Blake3 Algorithms

  • Sameeruddin Shaik

摘要

This study investigates the optimization of authenticated encryption algorithms, focusing on ChaCha20 and Blake3. Our analysis demonstrates that the ChaCha20 single-threaded implementation achieves a notable 1.25× speedup over the libsodium library. The parallel version of ChaCha20 exhibits impressive scalability, reaching a peak throughput of 130 GB/s and showing linear speedups up to 32 threads, constrained by CPU memory bandwidth. In comparison, the Blake3 implementation, both single-threaded and parallelized, exhibits performance on par with the reference implementation. The stack approach for Blake3 offers substantial performance improvements over traditional methods, while the divide-and-conquer approach shows scalability with increasing core counts, promising efficiency for large-scale file sizes. Future research will explore advanced vectorization strategies, multi-CPU scalability, and thorough security analysis to further enhance performance and robustness.