Abstract

The Advanced Encryption Standard (AES) is One of the most popular symmetric block cipher because it has better efficiency and security. The AES is computation intensive algorithm especially for massive transactions. The Graphics Processing Unit (GPU) is an amazing platform for accelerating AES. it has good parallel processing power. Traditional approaches for implementing AES using GPU use 16 byte per thread as a default granularity. In this paper, the AES-128 algorithm (ECB mode) is implemented on three different GPU architectures with different values of granularities (32,64 and 128 bytes/thread). Our results show that the throughput factor reaches 277 Gbps, 201 Gbps and 78 Gbps using the NVIDIA GTX 1080 (Pascal), the NVIDIA GTX TITAN X (Maxwell) and the GTX 780 (Kepler) GPU architectures.

Highlights

  • In this paper, we implement the Advanced Encryption Standard (AES) algorithm using Graphics Processing Unit (GPU) taking into consideration different granularity values of 32, 64, and 128 Bytes/thread seeking to increase the AES performance

  • Global memory-based chart, in Fig. 2(c), shows that the parallel granularity (i.e., 32 Bytes/thread) provides a higher average throughput compared to other granularities

  • Global memory-based chart, in Fig. 4(c), shows that the parallel granularity (i.e., 64 Bytes/thread) provides a higher average throughput compared to other granularities at most input file sizes

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Summary

Introduction

We implement the AES algorithm using GPU taking into consideration different granularity values of 32, 64, and 128 Bytes/thread seeking to increase the AES performance (i.e., throughput). All of those implementations use a 128-bit block input, with a key size of 128 bits, 192 bits, and 256 bits, respectively. The AES algorithm basically consists of two steps: key expansion and round transformations [1], as presented in Subsec. The result is a new matrix consisting of new 16 Bytes

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