Publication | Open Access
Utilizing the Double-Precision Floating-Point Computing Power of GPUs for RSA Acceleration
12
Citations
8
References
2017
Year
Hardware SecurityAsymmetric Cryptographic AlgorithmGpu ArchitectureEngineeringHardware AccelerationGpu BenchmarkingHardware AlgorithmUtilizing GpusComputer ArchitectureComputer EngineeringRsa AccelerationParallel ProgrammingComputer ScienceParallel ComputingElliptic Curve CryptographyGpu ComputingCryptography
Asymmetric cryptographic algorithm (e.g., RSA and Elliptic Curve Cryptography) implementations on Graphics Processing Units (GPUs) have been researched for over a decade. The basic idea of most previous contributions is exploiting the highly parallel GPU architecture and porting the integer-based algorithms from general-purpose CPUs to GPUs, to offer high performance. However, the great potential cryptographic computing power of GPUs, especially by the more powerful floating-point instructions, has not been comprehensively investigated in fact. In this paper, we fully exploit the floating-point computing power of GPUs, by various designs, including the floating-point-based Montgomery multiplication/exponentiation algorithm and Chinese Remainder Theorem (CRT) implementation in GPU. And for practical usage of the proposed algorithm, a new method is performed to convert the input/output between octet strings and floating-point numbers, fully utilizing GPUs and further promoting the overall performance by about 5%. The performance of RSA-2048/3072/4096 decryption on NVIDIA GeForce GTX TITAN reaches 42,211/12,151/5,790 operations per second, respectively, which achieves 13 times the performance of the previous fastest floating-point-based implementation (published in Eurocrypt 2009). The RSA-4096 decryption precedes the existing fastest integer-based result by 23%.
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