Abstract
AbstractWith the ubiquitous diffusion of mobile computing and Internet of Things (IoT), the amount of data exchanged and processed over the internet is increasing every day, demanding secure data communication/storage and new computing primitives. Although computing systems based on microelectronics steadily improved over the past 50 years thanks to the aggressive technological scaling, their improvement is now hindered by excessive power consumption and inherent performance limitation associated to the conventional computer architecture (von Neumann bottleneck). In this scenario, emerging memory technologies are gaining interest thanks to their non-volatility and low power/fast operation. In this chapter, experimental characterization and modeling of spin-transfer torque magnetic memory (STT-MRAM) are presented, with particular focus on cycling endurance and switching variability, which both present a challenge towards STT-based memory applications. Then, the switching variability in STT-MRAM is exploited for hardware security and computing primitives, such as true-random number generator (TRNG) and stochastic spiking neuron for neuromorphic and stochastic computing.
Highlights
The ubiquitous widespread of mobile devices marked the beginning of the Internet of Things (IoT) era, where the information is acquired, elaborated and transmitted by billions of interconnected smart devices
spin-transfer torque (STT) magnetic memory has at its core the magnetic tunnel junction (MTJ), which consists of a metal-insulator-metal tri-layered structure comprising a thin MgO tunnel barrier separating two CoFeB ferromagnetic electrodes (FMs)
Stochastic switching variability is harmful to the operation of STT-based magnetic memory, it is considered beneficial for emerging concept such as truerandom number generator (TRNG) [16], stochastic computing [28] and braininspired computing [29]
Summary
The ubiquitous widespread of mobile devices marked the beginning of the Internet of Things (IoT) era, where the information is acquired, elaborated and transmitted by billions of interconnected smart devices. Emerging applications such as active health monitoring, drone/robot navigation and autonomous car driving, require online elaboration of massive data In this scenario, there is an ever increasing need for faster computing and larger/faster storage available on the IoT devices themselves. During the last 50 years information technology achieved tremendous advancements in terms of computing power This trend was made possible by the continuous miniaturization of the metal-oxide-semiconductor field-effect transistor (MOSFET). The great majority of computer systems are based on the von Neumann architecture, which is characterized by a rigid separation of logic and memory circuits requiring a continuous movement of data between them. They generally depend on material-based storage, which relies on the physics of the constituent active materials. The stochastic switching phenomenon is exploited towards the design of true-random number generator (T-RNG) and spiking neuron for stochastic/neuromorphic computing
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