Two-pulse switching scheme and reinforcement learning for energy efficient SOT-MRAM simulations. (November 2021)
- Record Type:
- Journal Article
- Title:
- Two-pulse switching scheme and reinforcement learning for energy efficient SOT-MRAM simulations. (November 2021)
- Main Title:
- Two-pulse switching scheme and reinforcement learning for energy efficient SOT-MRAM simulations
- Authors:
- de Orio, R.L.
Ender, J.
Fiorentini, S.
Goes, W.
Selberherr, S.
Sverdlov, V. - Abstract:
- Highlights: Improved writing power efficiency of a two-current pulse switching scheme. Second current pulse reduced by 50% maintaining a switching time of 300 ps. Switching power of the scheme reduced by 40%. Development of reinforcement learning approach to optimize the switching. Optimized switching time of 146 ps: 50% decrease of the non-optimized configuration. Abstract: 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 switchingHighlights: Improved writing power efficiency of a two-current pulse switching scheme. Second current pulse reduced by 50% maintaining a switching time of 300 ps. Switching power of the scheme reduced by 40%. Development of reinforcement learning approach to optimize the switching. Optimized switching time of 146 ps: 50% decrease of the non-optimized configuration. Abstract: 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. … (more)
- Is Part Of:
- Solid-state electronics. Volume 185(2021)
- Journal:
- Solid-state electronics
- Issue:
- Volume 185(2021)
- Issue Display:
- Volume 185, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 185
- Issue:
- 2021
- Issue Sort Value:
- 2021-0185-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-11
- Subjects:
- Spin–orbit torque MRAM -- Magnetic field-free switching -- Two-pulse switching scheme -- Reinforcement learning -- Machine learning
Semiconductors -- Periodicals
Semiconducteurs -- Périodiques
621.38152 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00381101 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.sse.2021.108075 ↗
- Languages:
- English
- ISSNs:
- 0038-1101
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8327.385000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19356.xml