Performance Evaluation of Parallel AES Algorithm Implementing GPU
Suman Goyat1, Shri Kant2
1Suman Goyat, Department of Computer Science and Engineering, Sharda University, Greater Noida, U.P, India.
2Dr Shri Kant, Department of Computer Science and Engineering, Sharda University, Greater Noida, U.P, India.
Manuscript received on 10 April 2019 | Revised Manuscript received on 17 April 2019 | Manuscript Published on 04 May 2019 | PP: 1-7 | Volume-8 Issue-6S2 April 2019 | Retrieval Number: F22010486S219/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Graphics Processing Unit (GPU) was initially intended for the purpose of allowing video GPUs are competent for taking extensive measure of information and playing out a similar task again and again rapidly, in contrast to CPU, which will in general skip activities everywhere. In recent, GPU are used in many multimedia tasks, such as accelerating Adobe Flash video, translating video between different formats, national security, emergency services, image recognition, virus pattern matching, sector like medicine, natural resources, financial modelling, cutting-edge scientific research and oil and gas exploration, automobiles and data mining in data centers. The very parallel structure of GPUs makes handling more powerful than universally useful CPUs for calculations where processing of large blocks of data is done in parallel. This paper sought to continue the work of other researchers in applying these general-purpose computing capabilities of GPUs to cryptographic systems as well Encryption Standard (AES) cryptosystem, which is the current standard. As we know AES on large blocks is computationally escalated and to a great extent byte-parallel. The main objective of this paper is to study and analyze the performance of GPU accelerating AES cryptosystem. The investigation demonstrates that our methodology can quicken the speed of AES encryption essentially. At last, this achieve will analyze the execution between the GPU usage and the CPU usage with the end goal to investigate the likelihood of enhancing the execution of calculations.
Keywords: SIMD; Advanced Encryption Standard (AES); Data Encryption Standard (DES); CUDA and Cryptography; Graphics Processing Unit (GPU).
Scope of the Article: Computer Science and Its Applications