AES Encryption Implementation and Analysis on Commodity Graphics Processing Units

Abstract

Abstract. Graphics Processing Units (GPUs) present large potential performance gains within stream processing applications over the standard CPU. These performance gains are best realised when high computational intensity is required across large amounts of mostly independent input elements. The GPU's success in general purpose stream processing has been demonstrated in many diverse fields, though attempts to port cryptographic algorithms to the GPU have thus far met little success. In recent years, GPU architectures have continued to develop a more flexible and uniform programming environment. These developments have overcome a lot of previously encountered restrictions in cipher implementations. We present novel approaches for the implementation of the AES block cipher encryption algorithm on these GPUs. This work also serves as a precursor for future cipher implementations on the most advanced GPU architecture, the recently released Nvidia G80, which now includes integer support and a simplified programming interface.

Design of a parallel AES for graphics hardware using the CUDA framework

“…The use of GPUs to speed up the computation of AES has been pioneered by D. Cook et al in [16], and further developed by Harrison and Waldron [17]. Both works faced major limitations imposed by GPU hardware and software: on one hand, the GPU instruction set architectures were mostly geared towards floating point computation -thus lacking support for integer and logical operations; on the other hand, GPUs exposed to the programmer a set of operations only mapping typical rendering API, thus resulting unwieldy to program in a general purpose context.…”

High Throughput Parallelization of AES-CTR Algorithm

“…Bo, et al [2] presented a software speed record for both the encryption and the decryption using AES on 8-bit microcontroller, Nvidia GPUs, and the Cell Broadband Engine. Harrison and Waldron [9] proposed a study of AES implementation on the GPU hardware, using Nvidia GeForce 6 and 7 series. This implementation is based on the OpenGL library which is not geared towards a general purpose computing.…”

Cofactorization on Graphics Processing Units

“…Cryptologic applications of GPUs have been considered before: symmetric cryptography in [33,20,56,21,44,11,18], asymmetric cryptography in [39,54,22] for RSA and in [54,1,9] for ECC, and enhancing symmetric [8] and asymmetric [7,5,6,10] cryptanalysis.…”