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

• Published in: IEEE transactions on very large scale integration (VLSI) systems 2023-10, Vol.31 (10), p.1-14
• Main Authors: Fu, Siqing, Li, Tiejun, Zhang, Chunyuan, Li, Hanqing, Ma, Sheng, Zhang, Jianmin, Zhang, Ruiyi, Wu, Lizhou
• Format: Article
• Language: English
• Subjects: Acceleration; Behavioral sciences; Circuit/system codesign; Circuits; Co-design; Cryptography; Entropy; Generators; High speed; Instruction sets (computers); magnetic tunnel junction (MTJ); Magnetic tunneling; Microprocessors; Monte Carlo; Monte Carlo methods; Power demand; Random numbers; Resilience; RISC; Sequences; Switches; Switching; true random number generator (TRNG); Tunnel junctions
• ISSN: 1063-8210; 1557-9999
• DOI: 10.1109/TVLSI.2023.3298327

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 3.4-12 \times higher performance in speeding up option pricing programs than software implementations of random number generation.