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Stochastic computing (SC) is a promising technology that can be used for low-cost hardware designs. However, SC suffers from its long latency. Although parallel processing can efficiently shorten the latency, duplicated stochastic number generators (SNGs) are necessary, which cause substantial hardware overhead. This paper proposes a scalable SNG based on the spin-Hall-effect (SHE), which is capable of generating multiple independent stochastic streams simultaneously. The design takes advantages of the efficient charge-to-spin conversion from the Spin-Hall material and the intrinsic stochasticity of nanomagnets. Compared to previous spintronic SNGs, the SHE-SNG can reduce the area by $1.6\times -7.8\times $ and the power by $4.9\times -13\times $ while increasing the degree of parallelism from 1 to 16. Compared to CMOS-based SNGs, the proposed SNG obtained $24\times -120\times $ and $53\times $ reduction in terms of area and power, respectively. Finally, three benchmarks were implemented, and the results indicate that SC implementations with the proposed SHE-SNG can achieve $1.2\times -29\times $ reduction of hardware resources compared to implementations with previous CMOS- and spintronic-based designs while scaling the degree of parallelism from 1 to 64. [ABSTRACT FROM AUTHOR]

An ac small signal model for lateral spin valves (LSVs) is developed, and is applied to two different types of devices: spin transmitters and magnetic field sensors. The small signal models explicitly decouple the charge- and spin-dependent components, which describe the intrinsic RC delay and the ac spin accumulation dynamics, separately. The analysis is applied to graphene LSVs as an example to illustrate the optimization strategies for LSV devices. By using the charge-spin circuit model, the scattering parameters and the reflection coefficients at the output terminals are quantitatively calculated as a function of frequency. This model can be used as a guide for future LSV design and to benchmark performance across different material systems. [ABSTRACT FROM AUTHOR]