Fast and Energy-Efficient Block Ciphers Implementations in ARM Processors and Mali GPU

References

• J. Daemon, and V. Rijmen. “The design of Rijndael: AES: the advanced encryption standard”, 2012.
   Google Scholar
• T. Shirai, K. Shibutani, T. Akishita, S. Moriai, and T. Iwata, “The 128-bit blockcipher CLEFIA,” LNCS, Vol. 4593, pp. 181–95, 2007.
   Google Scholar
• A. Bogdanov, L. R. Knudsen, G. Leander, C. Paar, A. Poschmann, M. J. B. Robshaw, Y. Seurin, and C. Vikkelsoe, “PRESENT: An ultralightweight block cipher,” Cryptographic Hardware and Embedded Systems - CHES 2007, LNCS, Vol. 4727, 2007, pp. 450–66.
   Google Scholar
• R. Beaulieu, D. Shors, J. Smith, S. Treatman Clark, B. Weeks, and L. Wingers. “The SIMON and SPECK families of lightweight block ciphers”, Cryptology ePrint Archive, Report 2013/404, 2013.
   Google Scholar
• N. Nishikawa, K. Iwai, and T. Kurokawa. “High performance symmetric block ciphers on CUDA”, Second International Conference on Networking and Computing, pp. 221–227, 2011.
   Google Scholar
• J. Gilger, J. Barnickel, and U. Meyer. GPUAcceleration of block ciphers in the OpenSSL cryptographic library. Information Security Conference - ISC 2012, LNCS vol. 7483, pp. 338–353, 2012.
   Google Scholar
• W. K. Lee, H. S. Cheong, R. C.-W. Phan, and B. M. Goi, “Fast implementation of block ciphers and PRNGs in Maxwell GPU architecture:,” Cluster. Comput., Vol. 19, no. 1, pp. 335–47, 2016. doi: 10.1007/s10586-016-0536-2
   Web of Science ®Google Scholar
• H. Khanzadi, M. Eshghi, and S. E. Borujeni, “Design and FPGA implementation of a pseudo random bit generator using chaotic maps,” IETE. J. Res., Vol. 59, no. 1, pp. 63–73, 2013. doi: 10.4103/0377-2063.110633
   Web of Science ®Google Scholar
• ARM OpenCL. Mali-T600 series GPU OpenCL developer guide version 2.0 (2013). Available from http://malideveloper.arm.com/ [Accessed on 5 May 2016].
   Google Scholar
• ARM. Mali T628 GPU, 2014. Available from https://www.arm.com/products/multimedia/mali-performance-efficient-graphics/mali-t628.php [Accessed 5 May 2016].
   Google Scholar
• PowerVR graphics, 2013. Available from http://www.imgtec.com/powervr/powervr-graphics.asp [Accessed on 5 May 2016].
   Google Scholar
• AMD Radeon E6760 GPU for Embedded Applications, 2011. Available from: http://www.amd.com/en-us/products/embedded/graphics/e6760# [Accessed on 5 May 2016].
   Google Scholar
• R. Iakymchuk, and F. Trahay. “Performance analysis on energy efficient high performance architectures”, International Conference on Cluster Computing, Lviv, Ukraine, 2013.
   Google Scholar
• D. J. Bernstein, and P. Schwabe, “NEON crypto. cryptographic hardware and embedded systems – CHES 2012,” LNCS, vol. 7428, 2012, pp. 320-39.
   Google Scholar
• N. Rajovic, A. Ricoa, N. Puzovica, C. AdeniyiJonesc, and A. Ramireza, “Tibitabo making the case for an ARM-based HPC,” Future Gener. Comput. Syst., Vol. 36, pp. 322–34, 2014. doi: 10.1016/j.future.2013.07.013
   Web of Science ®Google Scholar
• N. Rajovic, P. M. Carpenter, I. Gelado, N. Puzovic, A. Ramirez, and M. Valero. “Supercomputing with commodity CPUs: are mobile SoCs ready for HPC”, Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, 2013.
   Google Scholar
• R. V. Aroca, and L. M. G. Gonçalves, “Towards green data centers: a comparison of x86 and ARM architectures power efficiency,” J. Parallel. Distrib. Comput., Vol. 72, no. 12, pp. 1770–8, 2012. doi: 10.1016/j.jpdc.2012.08.005
   Web of Science ®Google Scholar
• S. Davis, B. Jones, and H. Jiang. “Portable parallelized blowfish via RenderScript”, 16th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2015.
   Google Scholar
• ODROID-XU3, 2014. Available from: http://www.hardkernel.com/main/products/prdt_info.php?g_code=G140448267127&tab_idx=2 [Accessed 5 May 2016].
   Google Scholar
• L. Jóźwiak, “Embedded computing technology for highly-demanding cyber-physical systems,” IFAC-PapersOnLine, Vol. 48, no. 4, pp. 19–30, 2015. doi: 10.1016/j.ifacol.2015.07.002
   Google Scholar
• K. Kundu, April 20, 2015. Emerging markets and wearables to drive progress of next generation embedded GPUs. Available from: http://www.androidheadlines.com/2015/04/emerging-markets-and-wearables-to-drive-progress-of-next-generation-embedded-gpus.html [Accessed 13 June 2016].
   Google Scholar
• V. Sturén, and S. Hindefelt. “Fast GPU accelerated stereo correspondence for embedded surveillance camera systems”, Master Thesis, Department of Computer Science, Faculty of Engineering, Lunds Tekniska högskola, 2015.
   Google Scholar