Non-Boolean associative architectures based on nano-oscillators

Levitan, Steven P.; Fang, Yan; Dash, Denver; Shibata, Tadashi; Nikonov, Dmitri E.; Bourianoff, George I.

doi:10.1109/cnna.2012.6331473

Cited by 50 publications

(30 citation statements)

References 6 publications

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“…They also have the potential to open new paths towards neuromorphic computing with spin-torque nanooscillators, where inputs are microwave stimuli, and outputs are the different synchronization states of coupled oscillators arrays [34][35][36][37][38] …”

Section: Injection Lockingmentioning

confidence: 99%

Enhancing the injection locking range of spin torque oscillators through mutual coupling

Romera

Talatchian

Lebrun

et al. 2016

Applied Physics Letters

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We investigate how the ability of the vortex oscillation mode of a spin-torque nanooscillator to lock to an external microwave signal is modified when it is coupled to another oscillator. We show experimentally that mutual electrical coupling can lead to locking range enhancements of a factor 1. 64. Furthermore, we analyze the evolution of the locking range as a function of the coupling strength through experiments and numerical simulations. By uncovering the mechanisms at stake in the locking range enhancement, our results will be useful for designing spin-torque nano-oscillators arrays with high sensitivities to external microwave stimuli.Spin-torque nano-oscillators (STNOs) are promising candidates for the next generation of multifunctional spintronic nano-devices [1] such as efficient integrated microwave generators [2] and detectors [3,4]. One of their characteristic features compared to other auto-oscillators is their high non-linearity [5]. On one hand, this high nonlinearity translates into one of their most attractive properties: their ability to easily adapt their frequencies to external stimuli. On the other hand, by increasing their sensitivity to noise, it has the undesirable effect of broadening the spectral linewidth. In the last few years, many efforts have been made to improve the spectral purity of spintorque oscillators, a crucial step towards most applications. From these studies, a promising approach consists in the synchronization of the oscillators to an external microwave source [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] (injection locking), or to other oscillators [21][22][23][24][25][26][27] (mutual synchronization). In both cases, a crucial parameter to optimize for applications is the locking range, which should be as large as possible. A first way to increase the locking range is to work in regimes where the oscillator's nonlinearity is the largest. However, as mentioned earlier, this comes at the detriment of spectral purity. In the case of injection locking, another possibility is to increase the power of the external signal, but this is limited by the breakdown voltage of the tunnel barrier of the device and results in an increase of power consumption. Therefore, finding alternative paths to enhance the locking range is an important step towards designing next generation's magnetic microwave devices.In this manuscript we combine experimental results with numerical simulations to show that the injection locking range of a spin-torque oscillator can be enhanced by coupling it to another spintorque oscillator. Furthermore, it is shown that the locking range can be tuned by changing the mutual coupling strength between oscillators. (7) is the free layer and numbers represent thickness in nanometers. Samples were grown by sputterdeposition and patterned down to the bottom electrode into circular nanopillars with a diameter of 200 nm. The nano-pillars exhibit a TMR of 64% and a resistance-area product of RA~1 Ω.μm 2 . With this combination of materials and geometry, th...

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Section: Injection Lockingmentioning

confidence: 99%

Enhancing the injection locking range of spin torque oscillators through mutual coupling

Romera

Talatchian

Lebrun

et al. 2016

Applied Physics Letters

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“…To address the fundamental capacity problem that stems from the need for direct comparisons between the input and the data set, we introduce the N-Tree model [25]. In this model, we perform indirect comparisons between the input and representative patterns for subsets of the data.…”

Section: N-tree Modelmentioning

confidence: 99%

Alternative Architectures for NonBoolean Information Processing Systems

Fang¹,

Levitan²,

Chiarulli³

et al. 2014

Emerging Nanoelectronic Devices

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In this chapter we explore algorithms and develop an architecture based on emerging nanodevice technologies for cognitive computing tasks such as recognition, classification, and vision. Though the performance of computing systems has been continuously improving for decades, for cognitive tasks that humans are adept at, our machines are usually ineffective despite the rapid increases in computing speed and memory size. Moreover, given the fact that CMOS technology is approaching the limits of scaling, computing systems based on traditional Boolean logic may not be the best choice for these special computing tasks due to their massive parallelism and complex nonlinearities. On the other hand, recent research progress in nanotechnology provides us opportunities to access alternative devices with special nonlinear response characteristics that fit cognitive tasks better than general purpose computation. Building circuits, architectures, and algorithms around these emerging devices may lead us to a more efficient solution to cognitive computing tasks or even artificial intelligence. This chapter presents several nonBoolean architecture models and algorithms based on nano-oscillators to address image pattern recognition problems.The idea of special hardware architectures for cognitive tasks is not new. Equivalent circuits for a neuron model go back at least to 1907, where the model was just simply composed of a resistor and a capacitor [1]. Since then, various models have been implemented based on different technologies. In the late 1980s, Carver Mead proposed the term neuromorphic system in reference to all the electronic implementations of neural systems [2]. Meanwhile, with the development of digital computing systems, theoretical and computational models for neural

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“…Associative processing algorithms implemented in the Boolean computing framework which processes information in a binary (1 or 0) format are computationally expensive; an oscillator based non-Boolean approach that harnesses their non-linear phase and frequency synchronization dynamics can provide an energy efficient hardware platform [34] for such applications. Further, low-power MIT based oscillators with tunable coupling can be potential candidates in associative memories [9]. …”

Section: Conclusion and Future Perspectivementioning

confidence: 99%

Modeling and Simulation of Vanadium Dioxide Relaxation Oscillators

Maffezzoni

Daniel

Shukla

et al. 2015

IEEE Trans. Circuits Syst. I

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Abstract-This paper deals with modeling and simulation of a new family of two-terminal devices fabricated with vanadium dioxide material. Such devices allow realization of very compact relaxation nano-oscillators that can be connected electronically to form arrays of coupled oscillators. Challenging applications of oscillator arrays include the realization of multi-phase signal generators and massively parallel brain-inspired neurocomputing. In the paper, a circuit-level model of the vanadium dioxide device is provided which enables extensive electrical simulations of oscillator systems built on the device. The proposed model is exploited to explain the dynamics of vanadium dioxide relaxation oscillators as well as to accomplish a robust parameter design. Applications to the realization of voltage-controlled oscillators and of multi-phase oscillator arrays are illustrated.

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Non-Boolean associative architectures based on nano-oscillators

Cited by 50 publications

References 6 publications

Enhancing the injection locking range of spin torque oscillators through mutual coupling

Enhancing the injection locking range of spin torque oscillators through mutual coupling

Alternative Architectures for NonBoolean Information Processing Systems

Modeling and Simulation of Vanadium Dioxide Relaxation Oscillators

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