An Adiabatic Capacitive Artificial Neuron With RRAM-Based Threshold Detection for Energy-Efficient Neuromorphic Computing

In the quest for low power, bio-inspired computation both memristive and memcapacitive-based Artificial Neural Networks (ANN) have been the subjects of increasing focus for hardware implementation of neuromorphic computing. One step further, regenerative capacitive neural networks, which call for the use of adiabatic computing, offer a tantalising route towards even lower energy consumption, especially when combined with `memimpedace' elements. Here, we present an artificial neuron featuring adiabatic synapse capacitors to produce membrane potentials for the somas of neurons; the latter implemented via dynamic latched comparators augmented with Resistive Random-Access Memory (RRAM) devices. Our initial 4-bit adiabatic capacitive neuron proof-of-concept example shows 90% synaptic energy saving. At 4 synapses/soma we already witness an overall 35% energy reduction. Furthermore, the impact of process and temperature on the 4-bit adiabatic synapse shows a maximum energy variation of 30% at 100 degree Celsius across the corners without any functionality loss. Finally, the efficacy of our adiabatic approach to ANN is tested for 512 & 1024 synapse/neuron for worst and best case synapse loading conditions and variable equalising capacitance's quantifying the expected trade-off between equalisation capacitance and range of optimal power-clock frequencies vs. loading (i.e. the percentage of active synapses).Comment: This work has been accepted to the IEEE TCAS-

Mathematical Modeling of Neuronal Logic, Memory and Clocking Circuits

The differential equations used to model biological neurons and the chemical kinetics involved in synaptic excitation and inhibition have been well-established for a number of decades. For the first time, this paper presents mathematical and computational models of a neuronal binary oscillator half-adder, a neuronal Set-Reset (SR) flip-flop and a simple neuronal clocking circuit, which have all been shown to be noise resistant. In modern computers, the half-adder is the basic component to perform logic, the SR flip-flop is used to store memory and clocking circuits are used to synchronize components in parts of the computer. These novel circuits will provide the world with neuronal assays that can measure the functionality of the neurons and hence provide more information than is available with current technology. The authors are not proposing to build conventional computers with these components (they would be too slow to be practical) but the simple circuits could be used to measure the functionality of diseased circuits which are subjected to certain drugs. Neurological conditions research into Alzheimer’s disease, epilepsy and Parkinson’s disease, for example, would all benefit from this research. These assays for neuronal degradation could have major implications for the National Center for the Replacement, Refinement and Reduction of Animals in Research — otherwise known as the NC3R agenda

Direct Laser Writing of Metal and Metal Oxide Patterns for Flexible and Memristive Electronic Components

Growing interest in the fields of flexible electronics and AI are leading the development of new manufacturing techniques able to make computer hardware devices that can suite their unique needs. Research into these areas is stalled by the high cost of manufacturing putting rapid and low-cost manufacturing methods in high demand. Direct Laser Writing, as a novel manufacturing technique, has been shown to be able to produce flexible electronic devices rapidly and with the use of inexpensive raw materials. It works by treating a substrate coated in a metal ion precursor with focused laser irradiation. Where the laser interacts with the precursor organic reduction agents within the precursor are able to reduce the metal ions which then form nanoparticles that are then sintered to form interconnected nanoparticle networks. In this work direct laser writing is utilized to develop a manufacturing technique of novel flexible electronics for neuromorphic computing hardware. Direct laser writing of copper and copper patterns is used to study the relationship between applied laser energy and electrical properties of deposited patterns. Other metals are also studied. Anodic metals are not able to be fully reduced and are deposited as metal oxides. Cathodic metals are easily reduced and deposited as metals. Metals with intermediate reduction potentials can selectively be deposited as either metals or metal oxides. Deposition of metal alloys with homogenous composition is also demonstrated through the deposition of copper-nickel alloys. Memristor devices fabricated from Cu/Cu2O/Cu patterns are produced using direct laser writing. Planar patterns are fabricated and shown to have a high sensitivity to changing laser settings used to print the oxide region. Bipolar resistive switching is observed with setting and resetting occurring near +/- 0.7V, and ratios between the high and low resistance states being as high as 102 are achieved. Fabricated devices are shown to flexible and stable over long periods of time. Memristor based logic structures Including Boolean “And” and “Or” gates are fabricated in planar patterns from memristor pairs. Logic gates show signal processing in times as short as 300ns. Moderate signal degradation from the logic gates are noted at 9% and 21% in the “Or” gate and “And” gate respectively. Memristor crossbar arrays are also fabricated from Cu/Cu2O/Cu and Ag/Cu2O/Cu patterns. Their multiple resistance states are programmed and performances are compared. In summary Direct laser writing is demonstrated as a process that has promise as a method for producing flexible novel computer hardware. Further work is recommended to focus on identifying combinations of materials and laser settings that can further improve the consistency and performance of the direct laser writing fabricated memristor devices

Design and practical implementation of memristor-based threshold logic gates

Current advances in emerging memory technologies enable novel and unconventional computing architectures for high-performance and low-power electronic systems carrying out massively parallel operations at the edge. One emerging technology, ReRAM, also known as memristor, is gathering attention due to its attractive features for logic and memory computing systems. These include nanoscale dimensions, low-power operation and multi-state programming. The introduction of memristors has enabled the development of a new era of computing through hybridization of circuit and system design. At the same time, standalone CMOS circuit design seems to have reached its physical and functional limitations. Thus, further research towards novel logic families, such as Threshold Logic Gates (TLGs) is needed. TLGs constitute a logic family known for its high-speed and low power consumption. Although many implementation concepts of TLG circuit are assuming the use of memristors, few of them are based on physical ReRAM devices.& more ..

Dataset for "Practical Implementation of Memristor-Based Threshold Logic Gates"

This dataset supports the publication: Georgios Papandroulidakis, Alexander Serb, Ali Khiat, Geoff V. Merrett, Themis Prodromakis Practical Implementation of Memristor-Based Threshold Logic Gates Transactions on Circuits and Systems I: Regular Papers DOI: 10.1109/TCSI.2019.2902475 For more information see the readme file.</span