RHS-TRNG: A Resilient High-Speed True Random Number Generator Based on STT-MTJ Device

被引:9
作者
Fu, Siqing [1 ]
Li, Tiejun [1 ]
Zhang, Chunyuan [1 ]
Li, Hanqing [1 ]
Ma, Sheng [1 ]
Zhang, Jianmin [1 ]
Zhang, Ruiyi [2 ]
Wu, Lizhou [1 ]
机构
[1] Natl Univ Def Technol, Coll Comp Sci & Technol, Changsha 410073, Peoples R China
[2] Beijing Normal Univ Hong Kong Baptist Univ, United Int Coll, Div Sci & Technol, Zhuhai 519087, Peoples R China
关键词
Switches; Magnetic tunneling; Generators; Entropy; Power demand; Monte Carlo methods; Behavioral sciences; Circuit/system codesign; magnetic tunnel junction (MTJ); Monte Carlo; true random number generator (TRNG); MAGNETIC TUNNEL-JUNCTION; MRAM; DESIGN; CMOS; TIME; DRAM;
D O I
10.1109/TVLSI.2023.3298327
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
High-quality random numbers are very critical to many fields such as cryptography, finance, and scientific simulation, which calls for the design of reliable true random number generators (TRNGs). Limited by entropy source, throughput, reliability, and system integration, existing TRNG designs are difficult to be deployed in real computing systems to greatly accelerate target applications. This study proposes a TRNG circuit named resilient high-speed (RHS)-TRNG based on spin-transfer torque magnetic tunnel junction (STT-MTJ). RHS-TRNG generates resilient and high-speed random bit sequences exploiting the stochastic switching characteristics of STT-MTJ. By circuit/system codesign, we integrate RHS-TRNG into a reduced instruction set computer-V (RISC-V) processor as an acceleration component, which is driven by customized random number generation instructions. Our experimental results show that a single cell of RHS-TRNG has a random bit generation speed of up to 303 Mb/s, which is the highest among existing MTJ-based TRNGs. Higher throughput can be achieved by exploiting cell-level parallelism. RHS-TRNG also shows strong resilience against PVT variations thanks to our designs using bidirectional switching currents and dual generator units. In addition, our system evaluation results using gem5 simulator suggest that the system equipped with RHS-TRNG can achieve 3.4-12x higher performance in speeding up option pricing programs than software implementations of random number generation.
引用
收藏
页码:1578 / 1591
页数:14
相关论文
共 59 条
[1]  
Abboud R, 2021, Arxiv, DOI arXiv:2010.01179
[2]   True Random Number Generator for Reliable Hardware Security Modules Based on a Neuromorphic Variation-Tolerant Spintronic Structure [J].
Amirany, Abdolah ;
Jafari, Kian ;
Moaiyeri, Mohammad Hossein .
IEEE TRANSACTIONS ON NANOTECHNOLOGY, 2020, 19 :784-791
[3]  
[Anonymous], 2011, The boost C++ libraries
[4]  
Bassham L. E., 2010, document NIST SP 800-22 Rev. 1
[5]   STT-RAM Cell Design Considering CMOS and MTJ Temperature Dependence [J].
Bi, Xiuyuan ;
Li, Hai ;
Wang, Xiaobin .
IEEE TRANSACTIONS ON MAGNETICS, 2012, 48 (11) :3821-3824
[6]   Yoke-shaped MgO-barrier magnetic tunnel junction sensors [J].
Chen, J. Y. ;
Carroll, N. ;
Feng, J. F. ;
Coey, J. M. D. .
APPLIED PHYSICS LETTERS, 2012, 101 (26)
[7]   Tunable linear magnetoresistance in MgO magnetic tunnel junction sensors using two pinned CoFeB electrodes [J].
Chen, J. Y. ;
Feng, J. F. ;
Coey, J. M. D. .
APPLIED PHYSICS LETTERS, 2012, 100 (14)
[8]  
Chih YD, 2020, ISSCC DIG TECH PAP I, P222, DOI 10.1109/ISSCC19947.2020.9062955
[9]   Analysis of Ring-Oscillator-based True Random Number Generator on FPGAs [J].
Choi, Soyeon ;
Shin, Yerin ;
Yoo, Hoyoung .
2021 INTERNATIONAL CONFERENCE ON ELECTRONICS, INFORMATION, AND COMMUNICATION (ICEIC), 2021,
[10]  
Choi W. H., 2014, Electron Devices Meeting (IEDM), 2014 IEEE International, DOI 10.1109/IEDM.2014.7047039