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High-Performance Computing 2019-20


HPC Yearbook 19/20


News highlights


MIPT physicists imitate biological memory


Researchers from the Moscow Institute of Physics and Technology (MIPT) have created a device that acts like a synapse in the living brain, storing information and gradually forgetting it when not accessed for a long time, it was announced in August. Tis technology could pave the way for further developments in neurocomputing and find applications in AI – particularly for exploring the way the brain and memory works in humans. Known as a second-order memristor,


the new device is based on hafnium oxide and offers prospects for designing analogue neurocomputers imitating the way a biological brain learns. Te findings were reported in ACS Applied Materials & Interfaces. Neurocomputers, which enable AI,


emulate the way the brain works. It stores data in the form of synapses, a network of connections between the nerve cells, or neurons. Most neurocomputers have a conventional digital architecture and use mathematical models to invoke virtual neurons and synapses. Alternatively, an actual on-chip electronic component could stand for each neuron and synapse in the network. Tis so-called analogue approach has the potential to drastically speed up computations and reduce energy costs. But there is a catch: in an actual brain,


the active synapses tend to strengthen over time, while the opposite is true for inactive ones. Tis phenomenon, known as synaptic plasticity, is one of the foundations of natural


learning and memory. It explains the biology of cramming for an exam and why our seldom accessed memories fade. ‘Te problem with this solution is that the device tends to change its behaviour over time, and breaks down aſter prolonged operation,’ said the study’s lead author Anastasia Chouprik, from MIPT’s neurocomputing systems lab. ‘Te mechanism we used to implement synaptic plasticity is more robust. In fact, aſter switching the state of the system 100 billion times, it was still operating normally, so my colleagues stopped the endurance test.’ Te core component of a hypothetical


analogue neurocomputer is the memristor. Te word is a portmanteau of ‘memory’ and ‘resistor’, which pretty much sums up what it is: a memory cell acting as a resistor. Loosely speaking, a high resistance encodes a zero, and a low resistance encodes a one. Tis is analogous to how a synapse conducts a signal between two neurons (one), while the absence of a synapse results in no signal, a zero. Proposed in 2015, the second-order memristor is an attempt to reproduce natural memory, complete with synaptic plasticity. Te first mechanism for implementing this involves forming nanosized conductive bridges across the memristor. While initially decreasing resistance, they naturally decay with time, emulating forgetfulness. Instead of nanobridges, the MIPT team


relied on hafnium oxide to imitate natural memory. Tis material is ferroelectric: its internal bound charge distribution – electric polarisation – changes in response to an external electric field. If the field is removed, the material retains its acquired polarisation, the way a ferromagnet remains magnetised.


Te physicists implemented their second-


order memristor as a ferroelectric tunnel junction – two electrodes interlaid with a thin hafnium oxide film. Te device can be switched between its low and high resistance states by means of electric pulses, which change the ferroelectric film’s polarisation and thus its resistance. ‘Te main challenge that we faced was


figuring out the right ferroelectric layer thickness,’ Chouprik said. ‘Four nanometers proved to be ideal. Make it just one-nanometer thinner, and the ferroelectric properties are gone, while a thicker film is too wide a barrier for the electrons to tunnel through. And it is only the tunnelling current that we can modulate by switching polarisation.’ What gives hafnium oxide an edge over


other ferroelectric materials, such as barium titanate, is that it is already used by current silicon technology. For example, Intel has been manufacturing microchips based on a hafnium compound since 2007. Tis makes introducing hafnium-based devices, like the memristor, far easier and cheaper than using a new material. In a feat of ingenuity, the researchers


implemented ‘forgetfulness’ by leveraging the defects at the interface between silicon and hafnium oxide. Tose very imperfections used to be seen as a detriment to hafnium- based microprocessors, and engineers had to find a way around them by incorporating other elements to the compound. Instead, the MIPT team exploited the defects, which make memristor conductivity die down with time, just like natural memories. Vitalii Mikheev, the first author of the


paper, shared the team’s plans: ‘We are going to look into the interplay between the various mechanisms switching the resistance in our memristor. It turns out that the ferroelectric effect may not be the only one involved. To further improve the devices, we will need to distinguish between the mechanisms and learn to combine them.’ According to the physicists, they will


progress with the research on the properties of hafnium oxide to make the nonvolatile random access memory cells more reliable. Te team is also investigating the possibility of transferring their devices onto a flexible substrate, for use in flexible electronics. Last year, the researchers offered a detailed


description of how applying an electric field to hafnium oxide films affects their polarisation. It is this very process that enables reducing ferroelectric memristor resistance, which emulates synapse strengthening in a biological brain. Te team also works on neuromorphic computing systems with a digital architecture.


www.scientific-computing.com/hpc2019-20 27


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