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International Conference on Pairing-Based Cryptography

Pairing 2013: Pairing-Based Cryptography – Pairing 2013 pp 1–19Cite as

EAGL: An Elliptic Curve Arithmetic GPU-Based Library for Bilinear Pairing

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8365))

Abstract

In this paper we present the Elliptic curve Arithmetic GPU-based Library (EAGL), a self-contained GPU library, to support parallel computing of bilinear pairings based on the Compute Unified Device Architecture (CUDA) programming model. It implements parallelized point arithmetic, arithmetic functions in the 1-2-4-12 tower of extension fields. EAGL takes full advantage of the parallel processing power of GPU, with no shared memory bank conflict and minimal synchronization and global memory accesses, to compute some most expensive computational steps, especially the conventional-Montgomery-based multi-precision multiplications. At the 128-bit security level, EAGL can perform 3350.9 R-ate pairings/sec on one GTX-680 controlled by one CPU thread. Extensive experiments suggest that performance tradeoffs between utilization of GPU pipeline vs. memory access latency are highly complex for parallelization of pairing computations. Overall, on-chip memory is the main performance bottleneck for pairing computations on the tested GPU device, and the lazy reduction in \( \mathbb{F}_{q^{2}} \) gives the best performance. Increasing the size of on-chip memory, together with caching and memory prefetching modules are expected to offer substantial performance improvement for GPU-based pairing computations.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Texas A&M University, TAMU 3112, College Station, TX, 77843-3112, USA

    Shi Pu & Jyh-Charn Liu

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  1. Shi Pu
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  1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, No. 800, Dongchuan Road, 200240, Shanghai, China

    Zhenfu Cao

  2. School of Information Science and Technology, Sun Yat-sen University, No. 135, Xingang Xi Road, 510275, Guangzhou, China

    Fangguo Zhang

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Pu, S., Liu, JC. (2014). EAGL: An Elliptic Curve Arithmetic GPU-Based Library for Bilinear Pairing. In: Cao, Z., Zhang, F. (eds) Pairing-Based Cryptography – Pairing 2013. Pairing 2013. Lecture Notes in Computer Science, vol 8365. Springer, Cham. https://doi.org/10.1007/978-3-319-04873-4_1

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