Sun research project submitted to the department of electrical engineering and computer sciences, university of california at berkeley, in partial satisfaction of the requirements for the degree of master of science, plan ii. Novel designs of spiking neuron circuit and stdp learning. The memristor has a high resistance at first, but current flow causes the resistance to decrease over time until it hits a minimum value. Hopkins university, brainscales in the european unions neuromorphic chip program, brain simulator c2 introduced by ibm, and modular neural exploring traveling agent moneta. Simulation platform for memristor based neuromorphic computing system article pdf available in ieee transactions on computeraided design of integrated circuits and systems pp99. Apr, 2020 fourlayer 3d vertical rram integrated with finfet as a versatile computing unit for braininspired cognitive information processing. This is because a brain is far more energysaving than a. Oct 17, 20 realistic modeling is a new advanced methodology for investigating brain functions. Memristors mimic brains for massive machine learning july 8, 2015 timothy prickett morgan ai, compute, hpc 1 if you think that hewlettpackard is disappointed about the delays in getting the memristor to market, so is a tenacious inventor who has been working at the confluence of electronics and machine learning.
Chua in 1971, but it has been aroused recently by researchers at hp labs. The hp labs boss also said that, by 2018, we could pop 100tb memristor drives into storeserv arrays. In this study, a novel spiking neuron circuit and stdp learning circuit based on memristors are designed. A model of the neural connectome of the target organism is also required. Stanley williams, whose team discovered the memristor the fourth fundamental circuit element gives us a quick whiteboard talk about how the device works. Researchers at hp labs have built the first working prototypes of an important new electronic component that may lead to instanton pcs as well as analog computers that process information the way. Realistic modeling is a new advanced methodology for investigating brain functions. Cmos and memristor technologies for neuromorphic computing applications by jeff k. Brain simulation is the concept of creating a functioning computer model of a brain or part of a brain.
The proposed spiking neuron circuit, which is based on conventional leaky integrateandfire neuron and utilizes the nonlinear variation of memristance, is served to generate spikes. The current flowing through the memristor depends linearly on the input voltage according to the ohms law. It was described and named in 1971 by leon chua, completing a theoretical quartet of fundamental electrical components which comprises also the resistor, capacitor and inductor. A simulation platform for memristorbased neuromorphic. From medical to automotive application, from preventive maintenance to global climate forecasting and prevention, from the management of emergencies to the prevention of terrorist attacks, deeplearningbased ai is continuously penetrating our daily lives. However, the challenge is a complex one, as the human brain contains 86 billion brain cells known as neurons.
Design and simulation of memristorbased artificial neural. A memristorbased neuromorphic computing application. We just created an artificial synapse that can learn. Stanley williams, how we found the missing memristor, ieee spectrum, december. Moneta which is the part of the darpas synapse program, is a software.
Apr 30, 2008 hp is not going to reproduce all the functions of a brain in memristor, but the company is trying to build a relatively simple computing machine that operates on a different principle from todays. A simulation platform for memristorbased neuromorphic computing system lixue xia 1, boxun li1, tianqi tang, peng gu12, xiling yin1, wenqin huangfu1, paiyu chen3, shimeng yu 3, yu cao, yu wang1, yuan xie2 and huazhong yang1 1 dept. Keywords tao memristor modeling, numerical techniques, circuit implementation 1. Multisim circuit simulation software shows that this memristive module has the characteristic of the hysteresis loop as well, and circuit output curves are approximately in agreement with those of matlab numerical calculation results within the range of the permitted errors. Memristors are a new class of electrical circuitsand they could end the silicon era and change electronics forever.
Memristor is a robotics team focused on research and development. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. Using memristor hp spice model presented in, the simulation of the proposed circuits was carried out using cadence software with 65 nm cmos technology. The new memristor usedcalled a diffusive memristor because atoms in the resistive material move even without an applied voltage when the device is in the high resistance statewas a dielectic. This fact implies that the memristor stores no energy, not even briefly.
Construction of fluxcontrolled memristor and circuit. Brain circuits mimic processes of human brain decade emulate, not simulate simulate a mouse brain using transistors. Hp is not going to reproduce all the functions of a brain in memristor, but the company is trying to build a relatively simple computing machine that operates on a different principle from todays. If you really wanted to replicate a mammalian brain, software and hardware would need to be inextricable. Sun research project submitted to the department of electrical engineering and computer sciences, university of california at berkeley, in partial satisfaction of the requirements for.
Here, we will investigate memristorbased neural networks with a focus on systems that are inspired by biological processes. This study is an extension of the previous work advancing toward the circuit implementation where the. It used 147,456 cpus and 144tb of memory to create a simulation that was 83 times slower than that of a real cats brain. Introduction the memristor and its applications represent one of the most interesting. Memristor emulator circuit design and applications. A memristor, proposed in 1971 4 and experimentally established in 2008, 5 is a resistive device as an optimized future neuromorphic device to this kind of non. The architecture of the braininspired microprocessor under development at hp labs can be thought of as a kind of memristorbased multicore chip see illustration, moneta. New research, led by the university of southampton, has demonstrated that a nanoscale device, called a memristor, could be used to power artificial systems that can mimic the human brain. We just created an artificial synapse that can learn autonomously. Sputteringdeposited amorphous srvo x based memristor for. Proceedings of the european computing conference isbn. What is memristor know all about memristor technology. A memristorbased neuromorphic computing application date of final oral examination.
To build a brain, you need to throw away the conceit of separate hardware and software because the brain doesnt work that way. Memristor and memristorbased computing structure a memristor cell is a passive twoport element with variable resistance states. Design and layout were done in nm ibm process for cmos, and the hspice model files for the process were used to simulate the cmos part of the mmost design. The pure circuit implementation of stdp is a worthwhile work. This spice model makes it possible to design and simulate memristor circuits. Its a characteristic of the memristor that whenever the voltage is zero, so is the current, and vice versa. If you set the input voltage to a negative value, then the resistance will gradually increase until it hits a maximum value. Once again, this is because they tried to emulate this system in software, he said. A graph of the memristor s voltage, current, and resistance is shown below the circuit. Memristor modeling using finite element and spice based. Scientists have long been dreaming about building a computer that would work like a brain.
The current flowing through the memristor is shown in figure 5a. Memristor emulator circuit design and applications intechopen. Multiple memristor cells can be used to build the crossbar structure. This work lays a foundation for the construction of future advanced neuromorphic computing systems. It brings together students from many engineering fields and teaches them how to build fully autonomous robots together with other team members. In addition, the computing environment used for simulation offers the possibility of studying disease processes electronically. Design and simulation of memristorbased artificial neural network for bidirectional adaptive neural interface sergey shchanikov1, anton zuev1, ilya bordanov1, sergey danilin1, dmitry korolev2, alexey belov2, yana pigareva3, alexey pimashkin3, alexey mikhaylov2, victor kazantsev3 1department of information technologies, vladimir state university, vladimir, russia. A voltage mode memristor bridge synaptic circuit with. Once again, this is because they tried to emulate this system in software.
Memristors are important because they are nonvolatile, meaning that they retain memory without power. To evaluate the associative memory of the asvo memristor for neuromorphic system applications, a hopfield neural network hnn simulation 59, which has been commonly used to investigate. Since hp first developed a working prototype with a titanium dioxide film in. The simulation of memristive behaviour in electric circuits is also possible 2428. Aug 20, 2009 memory resistor or memristor is a nonlinear, fourth basic, passive element beside on conventional elements, r, l and c. As spice is too slow on simulating largescale memristor crossbar arrays, specific tools have been developed to investigate memristorbased neural network nn implementations 15 16. But, the recent memristor spice model can be used for a circuit level simulation. Modeling framework and comparison of memristive devices. Memristor is a novel device which acts as forth fundamental circuit element envisioned by the researchers in 1971. Making a new generation of memristors for digital memory.
Making a new generation of memristors for digital memory and. Several challenges need to be addressed when developing a behaviorlevel simulation platform for the memristorbased neuromorphic accelerator. Cmos and memristor technologies for neuromorphic computing. Memristor circuit design using ltspice spice electronic circuit simulation software. There are multiple kinds of devices which can be used as memristor cells, such as resistive random access memory rram, phase change memory pcm, etc. A novel memristive multilayer feedforward smallworld. Threedimensional memristor circuits as complex neural. Center pulse width modulation implementation based on. In this model, we simulate two circuits a lowpass filter in which a memristor is in series with an inductor, and a resistor with an operational amplifier. It mimics the way that the connections between neurons strengthen or weaken when signals pass through them. Specifically, the memristors curve is a pinched hysteresis loop, because the two branches cross at the origin. However, a behaviorlevel memristor based neuromorphic computing simulator, which can model the performance and realize an earlystage design space exploration, is still missing. Memristor can change its resistance according to the interior state and the exterior stimulation, such as voltage pulse. In this paper, we propose a simulation platform for the memristor based neuromorphic system, called mnsim.
As a proofofconcept demonstration, we programmed parallelly operated kernels into the 3d array, implemented a convolutional neural network and achieved softwarecomparable accuracy in. However, one of the most promising applications for memristors is the emulation of synaptic behaviour. The experiment was made using a sinusoidal voltage with a magnitude of 0. Fourlayer 3d vertical rram integrated with finfet as a versatile computing unit for braininspired cognitive information processing. Modelling a brain or brain subsystem involves both modelling neurons electrical and bulk chemical properties e. Memristor research highlights neuromorphic device future. Figure 5c illustrates that the memristance is a nonlinear function of the flow of charge as discussed previously. Memory resistor or memristor is a nonlinear, fourth basic, passive element beside on conventional elements, r, l and c. Center pulse width modulation implementation based on memristor. Memristor modeling in the first week of the internship, i was tasked with creating a veriloga model of memristors i could.
It is expected to make a huge change not only in literatures but also in nanoelectronic industry. It has a role to educate members and ensure development environment to enhance their skills. It brings together students from many engineering fields and teaches them how to build fully autonomous robots together with. He also pointed to ibms bluegenep supercomputer at argonne national lab that was used to simulate a cats brain.
Simulation platform for memristorbased neuromorphic computing system article pdf available in ieee transactions on computeraided design of integrated circuits and systems pp99. A memristor bridge neural circuit which is able to perform signed synaptic weighting was proposed in our previous study, where the synaptic operation was verified via software simulation of the mathematical model of the hp memristor. In this paper, we propose a simulation platform for the memristorbased neuromorphic system, called mnsim. The memristors capacity for learning is based on this adjustable resistance. Pspice computer simulation abdala and pickett 2009. Simulation also aims to replicate work on animal models, such as the mouse. A new electronic device can developed at the university of michigan can directly model the behaviors of a synapse, which is a connection between two neurons.
A memristor is an electrical component that limits or regulates the flow of electrical current in a circuit and remembers the amount of charge that has previously flowed through it. Dear colleagues, machine learning is impacting our society in every corner. The typical hysteresis loop in figure 5b shows its switching characteristic. However, a behaviorlevel memristorbased neuromorphic computing simulator, which can model the performance and realize an earlystage design space exploration, is still missing. This chapter introduces a design guide of memristor emulator circuits, from conceptual idea until experimental tests. In 2016 ieee symposium on vlsi technology 12 ieee, 2016. Memristor neuromorphic brain is not boolean emerging memristor devices, such as rram devices, provide a promising solution to realize better implementation of brain inspired circuits and systems 5 1 oj ik k j, k j k kj vr v g g m.
But the changes in conductance typically come from changes in the shape of the. Memristor devices have great interest in research ranging from memory and logic. Artificial neural networks anns exhibit learning abilities and can perform tasks which are difficult for conventional computing systems, such as pattern. The behavioural model of each topology is derived and programmed at simulink under the matlab environment.
The time diagrams of the memristor voltage and current for the picketts memristor model are presented in fig. Memristors mimic brains for massive machine learning. Simulation platform for memristorbased neuromorphic. Three topologies of memristor emulator circuits in their incremental and decremental versions are analysed and designed at low and high frequency. Brain circuits mimic processes of human brain decade emulate, not simulate. Memristor crossbar the estimation model of area and latency is the same with memoryoriented design the energy consumption of computation is larger than read a single cell in memory as an behaviorlevel simulator, mnsim uses the average case to estimate the energy consumption of each cell 19 all working various resistance states. A graph of the memristors voltage, current, and resistance is shown below the circuit. Index termsanalog circuits design, memristor, bessel. As spice is too slow on simulating largescale memristor crossbar arrays, specific tools have been developed to investigate memristor based neural network nn implementations 15 16.