CMOS devices display volatile characteristics and are not well suited for analog applications such as neuromorphic computing. Spintronic devices, on the other hand, exhibit both non-volatile and ...analog features, which are well suited to neuromorphic computing. Consequently, these novel devices are at the forefront of beyond-CMOS artificial intelligence applications. However, a large quantity of these artificial neuromorphic devices still require the use of CMOS to implement various neuromorphic functionalities, which decreases the efficiency of the system. To resolve this, we have previously proposed a number of artificial neurons and synapses that do not require CMOS for operation. Although these devices are a significant improvement over previous renditions, their ability to enable neural network learning and recognition is limited by their intrinsic activation functions. This work proposes modifications to these spintronic neurons that enable configuration of the activation functions through control of the shape of a magnetic domain wall track. Linear and sigmoidal activation functions are demonstrated in this work, which can be extended through a similar approach to enable a wide variety of activation functions.
Despite hitting major roadblocks in 2-D scaling, NAND flash continues to scale in the vertical direction and dominate the commercial nonvolatile memory market. However, several emerging nonvolatile ...technologies are under development by major commercial foundries or are already in small volume production, motivated by storage-class memory and embedded application drivers. These include spin-transfer torque magnetic random access memory (STT-MRAM), resistive random access memory (ReRAM), phase change random access memory (PCRAM), and conductive bridge random access memory (CBRAM). Emerging memories have improved resilience to radiation effects compared to flash, which is based on storing charge, and hence may offer an expanded selection from which radiation-tolerant system designers can choose from in the future. This review discusses the material and device physics, fabrication, operational principles, and commercial status of scaled 2-D flash, 3-D flash, and emerging memory technologies. Radiation effects relevant to each of these memories are described, including the physics of and errors caused by total ionizing dose, displacement damage, and single-event effects, with an eye toward the future role of emerging technologies in radiation environments.
We evaluate the resilience of CoFeB/MgO/CoFeB magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy (PMA) to displacement damage induced by heavy-ion irradiation. MTJs were exposed ...to 3-MeV Ta 2+ ions at different levels of ion beam fluence spanning five orders of magnitude. The devices remained insensitive to beam fluences up to <inline-formula> <tex-math notation="LaTeX">10^{11} </tex-math></inline-formula> ions/cm 2 , beyond which a gradual degradation in the device magnetoresistance, coercive magnetic field, and spin-transfer-torque (STT) switching voltage were observed, ending with a complete loss of magnetoresistance at very high levels of displacement damage (>0.035 displacements per atom). The loss of magnetoresistance is attributed to structural damage at the MgO interfaces, which allows electrons to scatter among the propagating modes within the tunnel barrier and reduces the net spin polarization. Ion-induced damage to the interface also reduces the PMA. This study clarifies the displacement damage thresholds that lead to significant irreversible changes in the characteristics of STT magnetic random access memory (STT-MRAM) and elucidates the physical mechanisms underlying the deterioration in device properties.
Emerging concepts for neuromorphic computing, bioelectronics, and brain-computer interfacing inspire new research avenues aimed at understanding the relationship between oxidation state and ...conductivity in unexplored materials. This report expands the materials playground for neuromorphic devices to include a mixed valence inorganic 3D coordination framework, a ruthenium Prussian blue analog (RuPBA), for flexible and biocompatible artificial synapses that reversibly switch conductance by more than four orders of magnitude based on electrochemically tunable oxidation state. The electrochemically tunable degree of mixed valency and electronic coupling between N-coordinated Ru sites controls the carrier concentration and mobility, as supported by density functional theory computations and application of electron transfer theory to in situ spectroscopy of intervalence charge transfer. Retention of programmed states is improved by nearly two orders of magnitude compared to extensively studied organic polymers, thus reducing the frequency, complexity, and energy costs associated with error correction schemes. This report demonstrates dopamine-mediated plasticity of RuPBA synapses and biocompatibility of RuPBA with neuronal cells, evoking prospective application for brain-computer interfacing.
In this article, we present a unique method of measuring single-event transient (SET) sensitivity in 12-nm FinFET technology. A test structure is presented that approximately measures the length of ...SETs using flip-flop shift registers with clock inputs driven by an inverter chain. The test structure was irradiated with ions at linear energy transfers (LETs) of 4.0, 5.6, 10.4, and 17.9 MeV-cm 2 /mg, and the cross sections of SET pulses measured down to 12.7 ps are presented. The experimental results are interpreted using a modeling methodology that combines TCAD and radiation effect simulations to capture the SET physics, and SPICE simulations to model the SETs in a circuit. The modeling shows that only ion strikes on the fin structure of the transistor would result in enough charge collected to produce SETs, while strikes in the subfin and substrate do not result in enough charge collected to produce measurable transients. Comparisons of the cumulative cross sections obtained from the experiment and from the simulations validate the modeling methodology presented.
We demonstrate SONOS (silicon-oxide-nitride-oxide-silicon) analog memory arrays that are optimized for neural network inference. The devices are fabricated in a 40nm process and operated in the ...subthreshold regime for in-memory matrix multiplication. Subthreshold operation enables low conductances to be implemented with low error, which matches the typical weight distribution of neural networks, which is heavily skewed toward near-zero values. This leads to high accuracy in the presence of programming errors and process variations. We simulate the end-to-end neural network inference accuracy, accounting for the measured programming error, read noise, and retention loss in a fabricated SONOS array. Evaluated on the ImageNet dataset using ResNet50, the accuracy using a SONOS system is within 2.16% of floating-point accuracy without any retraining. The unique error properties and high On/Off ratio of the SONOS device allow scaling to large arrays without bit slicing, and enable an inference architecture that achieves 20 TOPS/W on ResNet50, a <inline-formula> <tex-math notation="LaTeX">> 10\times </tex-math></inline-formula> gain in energy efficiency over state-of-the-art digital and analog inference accelerators.
We investigate the sensitivity of silicon-oxide-nitride-silicon-oxide (SONOS) charge trapping memory technology to heavy-ion induced single-event effects. Threshold voltage (<inline-formula> ...<tex-math notation="LaTeX">V_{T} </tex-math></inline-formula>) statistics were collected across multiple test chips that contained in total 18 Mb of 40-nm SONOS memory arrays. The arrays were irradiated with Kr and Ar ion beams, and the changes in their <inline-formula> <tex-math notation="LaTeX">V_{T} </tex-math></inline-formula> distributions were analyzed as a function of linear energy transfer (LET), beam fluence, and operating temperature. We observe that heavy ion irradiation induces a tail of disturbed devices in the "program" state distribution, which has also been seen in the response of floating-gate (FG) flash cells. However, the <inline-formula> <tex-math notation="LaTeX">V_{T} </tex-math></inline-formula> distribution of SONOS cells lacks a distinct secondary peak, which is generally attributed to direct ion strikes to the gate-stack of FG cells. This property, combined with the observed change in the <inline-formula> <tex-math notation="LaTeX">V_{T} </tex-math></inline-formula> distribution with LET, suggests that SONOS cells are not particularly sensitive to direct ion strikes but cells in the proximity of an ion's absorption can still experience a <inline-formula> <tex-math notation="LaTeX">V_{T} </tex-math></inline-formula> shift. These results shed new light on the physical mechanisms underlying the <inline-formula> <tex-math notation="LaTeX">V_{T} </tex-math></inline-formula> shift induced by a single heavy ion in scaled charge trap memory.
Integration-technology feature shrink increases computing-system susceptibility to single-event effects (SEE). While modeling SEE faults will be critical, an integrated processor's scope makes ...physically correct modeling computationally intractable. Without useful models, presilicon evaluation of fault-tolerance approaches becomes impossible. To incorporate accurate transistor-level effects at a system scope, we present a multiscale simulation framework. Charge collection at the 1) device level determines 2) circuit-level transient duration and state-upset likelihood. Circuit effects, in turn, impact 3) register-transfer-level architecture-state corruption visible at 4) the system level. Thus, the physically accurate effects of SEEs in large-scale systems, executed on a high-performance computing (HPC) simulator, could be used to drive cross-layer radiation hardening by design. We demonstrate the capabilities of this model with two case studies. First, we determine a D flip-flop's sensitivity at the transistor level on 14-nm FinFet technology, validating the model against published cross sections. Second, we track and estimate faults in a microprocessor without interlocked pipelined stages (MIPS) processor for Adams 90% worst case environment in an isotropic space environment.
The analog-to-digital converter (ADC) is not only a key component in analog in-memory computing (IMC) accelerators but also a bottleneck for the efficiency and accuracy of these systems. While the ...tradeoffs between power consumption, latency, and area in ADC design are well studied, it is relatively unknown which ADC implementations are optimal for algorithmic accuracy, particularly for neural network inference. We explore the design space of the ADC with a focus on accuracy, investigating the sensitivity of neural network outputs to component variability inside the ADC and how this sensitivity depends on the ADC architecture. The compact models of the pipeline, cyclic, successive-approximation-register (SAR) and ramp ADCs are developed, and these models are used in a system-level accuracy simulation of analog neural network inference. Our results show how the accuracy on a complex image recognition benchmark (ResNet50 on ImageNet) depends on the capacitance mismatch, comparator offset, and effective number of bits (ENOB) for each of the four ADC architectures. We find that robustness to component variations depends strongly on the ADC design and that inference accuracy is particularly sensitive to the value-dependent error characteristics of the ADC, which cannot be captured by the conventional ENOB precision metric.
We study the impact of irradiation on magnetic tunnel junction (MTJ) films with perpendicular magnetic anisotropy (PMA) and spin-orbit torque (SOT) switching using magneto-optical Kerr effect and ...transmission electron microscopy. Our results show that the thin-film stack is robust to gamma ionizing dose up to 1 Mrad(Si) and Ta 1+ ion irradiation fluences up to 10 12 ions/cm 2 , showing SOT PMA MTJs are radiation-hard. But, at very high Ta 1+ ion irradiation between 10 12 and 10 14 ions/cm 2 , reduced coercivity and eventually greatly reduced PMA are observed, corresponding with an increase in intermixing of the CoFeB-MgO layers, particularly at the lower CoFeB-MgO interface. These results agree with displacement damage modeling that predicts higher damage in the layers closer to the bottom heavy metal and substrate. Compared to spin transfer torque and in-plane anisotropy MTJs, needing a top-pinned stack, a thicker heavy metal layer, and perpendicular anisotropy that is pinned out of plane by interfaces, all could make SOT PMA MTJs more susceptible to damage at high doses.
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