Two-pulse switching scheme and reinforcement learning for energy efficient SOT-MRAM simulations
Autor: | R. L. de Orio, Simone Fiorentini, Johannes Ender, Viktor Sverdlov, Siegfried Selberherr, Wolfgang Goes |
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Rok vydání: | 2021 |
Předmět: |
010302 applied physics
Magnetoresistive random-access memory Computer science 02 engineering and technology 021001 nanoscience & nanotechnology Condensed Matter Physics 01 natural sciences Electronic Optical and Magnetic Materials Power (physics) Pulse (physics) Switching time Reduction (complexity) 0103 physical sciences Materials Chemistry Electronic engineering Reinforcement learning Electrical and Electronic Engineering 0210 nano-technology Electrical efficiency Efficient energy use |
Zdroj: | Solid-State Electronics. 185:108075 |
ISSN: | 0038-1101 |
DOI: | 10.1016/j.sse.2021.108075 |
Popis: | We demonstrate by means of numerical simulations the switching of a perpendicularly magnetized free layer by spin–orbit torques based on a two-pulse switching scheme with improved writing power efficiency. In this scheme, the first pulse selects the cell, while the second pulse completes the switching deterministically. It is shown that the magnitude of the second current pulse can be reduced to about 50% of the critical current and the switching remains reliable with a switching time of 300 ps. With such a significant current reduction the writing power required for switching decreases by 40%, which results in a very energy efficient scheme. In addition, we develop a reinforcement learning approach to optimize the pulse configuration with the goal of achieving the shortest switching time. With this approach a switching time of 146 ps has been obtained, a reduction of 50% in relation to the non-optimized configuration. These research findings confirm that reinforcement learning is a promising tool to simplify and automate the search for a faster, energy efficient scheme in the two-pulse switching approach. |
Databáze: | OpenAIRE |
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