GPU Accelerated AES Algorithm
Canhui Wang, Xiaowen Chu

TL;DR
This paper presents a GPU-based implementation of AES encryption and decryption using a novel approach that leverages the Electronic Code Book mode, lookup tables, and fine-grained thread scheduling to improve performance.
Contribution
It introduces a new GPU-accelerated AES method with optimized thread granularity and lookup tables, enhancing encryption speed and efficiency.
Findings
Achieved significant speedup over CPU implementations
Demonstrated effective use of GPU architecture for cryptography
Provided open-source code and comprehensive experimental data
Abstract
It has been widely accepted that Graphics Processing Units (GPU) is one of promising schemes for encryption acceleration, in particular, the support of complex mathematical calculations such as integer and logical operations makes the implementation easier; however, complexes such as parallel granularity, memory allocation still imposes a burden on real world implementations. In this paper, we propose a new approach for Advanced Encryption Standard accelerations, including both encryption and decryption. Specifically, we adapt the Electronic Code Book mode for cryptographic transformation, look up table scheme for fast lookup, and a granularity of one state per thread for thread scheduling. Our experimental results offer researchers a good understanding on GPU architectures and software accelerations. In addition, both our source code and experimental results are freely available.
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Taxonomy
TopicsCryptographic Implementations and Security · Advanced Malware Detection Techniques · DNA and Biological Computing
