8899

Optimized GPU Implementation and Performance Analysis of HC Series of Stream Ciphers

Ayesha Khalid, Deblin Bagchi, Goutam Paul, Anupam Chattopadhyay
Institute for Communication Technologies and Embedded Systems, RWTH Aachen University, Aachen 52074, Germany
Cryptology ePrint Archive: Report 2013/059, 2013
@misc{cryptoeprint:2013:059,

   author={Ayesha Khalid and Deblin Bagchi and Goutam Paul and Anupam Chattopadhyay},

   title={Optimized GPU Implementation and Performance Analysis of HC Series of Stream Ciphers},

   howpublished={Cryptology ePrint Archive, Report 2013/059},

   year={2013},

   note={url{http://eprint.iacr.org/}}

}

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The ease of programming offered by the CUDA programming model attracted a lot of programmers to try the platform for acceleration of many non-graphics applications. Cryptography, being no exception, also found its share of exploration efforts, especially block ciphers. In this contribution we present a detailed walk-through of effective mapping of HC-128 and HC-256 stream ciphers on GPUs. Due to inherent inter-S-Box dependencies, intra-S-Box dependencies and a high number of memory accesses per keystream word generation, parallelization of HC series of stream ciphers remains challenging. For the first time, we present various optimization strategies for HC-128 and HC-256 speedup in tune with CUDA device architecture. The peak performance achieved with a single data-stream for HC-128 and HC-256 is 0.95 Gbps and 0.41 Gbps respectively. Although these throughput figures do not beat the CPU performance (10.9 Gbps for HC-128 and 7.5 Gbps for HC-256), our multiple parallel data-stream implementation is benchmarked to reach approximately 31 Gbps for HC-128 and 14 Gbps for HC-256 (with 32768 parallel data-streams). To the best of our knowledge, this is the first reported effort of mapping HC-Series of stream ciphers on GPUs.
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