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| मुख्य लेखकों: | , , , , , , , , |
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| स्वरूप: | Preprint |
| प्रकाशित: |
2022
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| विषय: | |
| ऑनलाइन पहुंच: | https://arxiv.org/abs/2202.10228 |
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| _version_ | 1866910762559078400 |
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| author | Wang, Wei Danial, Loai Herbelin, Eric Hoffer, Barak Oved, Batel Greenberg-Toledo, Tzofnat Pikhay, Evgeny Roizin, Yakov Kvatinsky, Shahar |
| author_facet | Wang, Wei Danial, Loai Herbelin, Eric Hoffer, Barak Oved, Batel Greenberg-Toledo, Tzofnat Pikhay, Evgeny Roizin, Yakov Kvatinsky, Shahar |
| contents | Y-Flash memristors utilize the mature technology of single polysilicon floating gate non-volatile memories (NVM). It can be operated in a two-terminal configuration similar to the other emerging memristive devices, i.e., resistive random-access memory (RRAM), phase-change memory (PCM), etc. Fabricated in production complementary metal-oxide-semiconductor (CMOS) technology, Y-Flash memristors allow excellent repro-ducibility reflected in high neuromorphic products yields. Working in the subthreshold region, the device can be programmed to a large number of fine-tuned intermediate states in an analog fashion and allows low readout currents (1 nA ~ 5 $μ$ A). However, currently, there are no accurate models to describe the dynamic switching in this type of memristive device and account for multiple operational configurations. In this paper, we provide a physical-based compact model that describes Y-Flash memristor performance both in DC and AC regimes, and consistently describes the dynamic program and erase operations. The model is integrated into the commercial circuit design tools and is ready to be used in applications related to neuromorphic computation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2202_10228 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Physical based compact model of Y-Flash memristor for neuromorphic computation Wang, Wei Danial, Loai Herbelin, Eric Hoffer, Barak Oved, Batel Greenberg-Toledo, Tzofnat Pikhay, Evgeny Roizin, Yakov Kvatinsky, Shahar Emerging Technologies Applied Physics Y-Flash memristors utilize the mature technology of single polysilicon floating gate non-volatile memories (NVM). It can be operated in a two-terminal configuration similar to the other emerging memristive devices, i.e., resistive random-access memory (RRAM), phase-change memory (PCM), etc. Fabricated in production complementary metal-oxide-semiconductor (CMOS) technology, Y-Flash memristors allow excellent repro-ducibility reflected in high neuromorphic products yields. Working in the subthreshold region, the device can be programmed to a large number of fine-tuned intermediate states in an analog fashion and allows low readout currents (1 nA ~ 5 $μ$ A). However, currently, there are no accurate models to describe the dynamic switching in this type of memristive device and account for multiple operational configurations. In this paper, we provide a physical-based compact model that describes Y-Flash memristor performance both in DC and AC regimes, and consistently describes the dynamic program and erase operations. The model is integrated into the commercial circuit design tools and is ready to be used in applications related to neuromorphic computation. |
| title | Physical based compact model of Y-Flash memristor for neuromorphic computation |
| topic | Emerging Technologies Applied Physics |
| url | https://arxiv.org/abs/2202.10228 |