ntvНаучно-технический вестник информационных технологий, механики и оптикиScientific and Technical Journal of Information Technologies, Mechanics and Optics2226-14942500-0373Университет ИТМО10.17586/2226-1494-2024-24-6-1059-1065ntv-413Research ArticleМАТЕМАТИЧЕСКОЕ И КОМПЬЮТЕРНОЕ МОДЕЛИРОВАНИЕMODELING AND SIMULATIONИсследование стабильности гибридной МОП-мемристорной памяти с использованием модифицированного метода оптимизации роя частицStability study of hybrid MOS memristor memory using modified particle swarm optimization methodhttps://orcid.org/0000-0002-2933-9599БондаревА. В.BondarevA. V.

Бондарев Андрей Владимирович - кандидат технических наук, доцент, заведующий кафедрой,

Уфа, 450076

Andrei V. Bondarev - PhD, Associate Professor, Head of Department,

Ufa, 450076

bondarevav@kfosu.edu.ruhttps://orcid.org/0000-0002-5917-2910ЕфановВ. Н.EfanovV. N.

Ефанов Владимир Николаевич - доктор технических наук, профессор, профессор,

Уфа, 450076

Vladimir N. Efanov – D.Sc., Full Professor,

Ufa, 450076

efanov@mail.ruУфимский университет науки и технологийРоссияUfa University of Science and TechnologyRussian Federation20242912202424610591065Copyright © Бондарев А.В., Ефанов В.Н., 20242024Бондарев А.В., Ефанов В.Н.Bondarev A.V., Efanov V.N.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://ntv.elpub.ru/jour/article/view/413Введение

Введение. Рассматривается проблема оценки стабильности наноэлектронных структур, включающих гибридную транзисторно-мемристорную энергонезависимую память. Результаты исследования процессов в наноэлектронных структурах с использованием мемристоров показали, что дополнительно к обычному дрейфу параметров, свойственному полупроводниковым приборам, в данных структурах возникают новые уникальные эффекты. Такие эффекты приводят к неопределенности в оценке состояния ячеек мемристорной памяти. Исследование подобных эффектов находится в начальном состоянии, в том числе из-за отсутствия моделей, позволяющих в полном объеме исследовать изменчивость параметров и дрейф состояний мемристоров. В связи с этим предлагается использовать метаэвристический метод роя частиц, позволяющий оценивать устойчивость гибридной транзисторно-мемристорной памяти.

Методы

Методы. В работе используются методы топологического и параметрического анализов наноэлектронных структур с мемристорами, метод интервального анализа подобных структур, метод оптимизации роя частиц для решения интервальных алгебраических и дифференциальных уравнений.

Основные результаты

Основные результаты. Предложена структурно-параметрическая модель гибридного устройства памяти на основе мемристоров с учетом конечных приращений их параметров, вызванных воздействием внешних и внутренних факторов. Разработан алгоритм оценки параметров гибридного запоминающего устройства с мемристорами на основе модифицированного метода оптимизации роя частиц.

Обсуждение

Обсуждение. Интервальные математические модели служат основой для разработки новых принципов организации сверхплотной энергонезависимой памяти и создают предпосылки для новых подходов к организации вычислений в памяти. Вычислительный алгоритм, основанный на методе оптимизации роя частиц, позволяет оценить работоспособность гибридных металл-оксид-полупроводниковых структур (МОП-структур) с мемристорами в реальных условиях эксплуатации. В результате выполненной оценки появляется возможность расширить область применения устройств, использующих квантовые эффекты, в различных технических приложениях.

The problem of stability assessment of nanoelectronic structures including hybrid transistor-memristor non-volatile memory is considered. The results of the study of processes in nanoelectronic structures using memristors indicate that in addition to the usual parameter drift inherent in semiconductor devices, new unique effects arise in them, in particular, such effects that lead to uncertainty in the evaluation of the state of memristor memory cells. The study of such effects is in its infancy, in part due to the lack of models that allow full investigation of parameter variability and state drift of memristors. In this regard, we propose to use the metaheuristic particle swarm method which allows us to evaluate the stability of hybrid transistor-memristor memory. The methods of topological and parametric analysis of nanoelectronic structures with memristors, the method of interval analysis of similar structures, the method of particle swarm optimization for solving interval algebraic and differential equations are used in this work. A structuralparametric model of a hybrid memristor-based memory device is proposed, taking into account finite increments of their parameters caused by the influence of external and internal factors. An algorithm for estimating the parameters of a hybrid memristor-based memory device using a modified particle swarm optimization method is developed. Interval mathematical models serve as a basis for the development of new principles of organization of ultra-dense nonvolatile memory and create prerequisites for new approaches to the organization of computations in memory. The computational algorithm based on the method of particle swarm optimization allows us to evaluate the performance of hybrid metaloxide-semiconductor structures (MOS structures) with memristors under real operating conditions, resulting in the possibility to expand the scope of application of devices using quantum effects in various technical application.

мемристорМОП-транзисторпамятьстабильностьоптимизациярой частицmemristorMOSFETmemorystabilityoptimizationswarm of particlesReferencesZiegler T., Brackmann L., Hennen T., Bengel C., Menzel S., Wouters D.J. Eliminating capacitive sneak paths in associative capacitive networks based on complementary resistive switches for in-memory computing // Proc. of the 2023 IEEE International Memory Workshop (IMW). 2023. P. 1–4. https://doi.org/10.1109/IMW56887.2023.10145947Ziegler T., Brackmann L., Hennen T., Bengel C., Menzel S., Wouters D.J. Eliminating capacitive sneak paths in associative capacitive networks based on complementary resistive switches for in-memory computing. Proc. of the 2023 IEEE International Memory Workshop (IMW), 2023, pp. 1–4. https://doi.org/10.1109/IMW56887.2023.10145947Mannocci P., Baroni A., Melacarne E., Zambelli C., Olivo P., Perez E., Wenger C., Ielmini D. In-memory principal component analysis by crosspoint array of resistive switching memory: A new hardware approach for energy-efficient data analysis in edge computing // IEEE Nanotechnology Magazine. 2022. V. 16. N 2. P. 4–13. https://doi.org/10.1109/MNANO.2022.3141515Mannocci P., Baroni A., Melacarne E., Zambelli C., Olivo P., Perez E., Wenger C., Ielmini D. In-memory principal component analysis by crosspoint array of resistive switching memory: A new hardware approach for energy-efficient data analysis in edge computing. IEEE Nanotechnology Magazine, 2022, vol. 16, no. 2, pp. 4–13. https://doi.org/10.1109/MNANO.2022.3141515Shalini, Singh K. Power and area efficient hybrid memristor-CMOS based 2’s complement fsm for high-performance computing system // Proc. of the 2023 International Conference on Artificial Intelligence and Smart Communication (AISC). 2023. P. 170–174. https://doi.org/10.1109/AISC56616.2023.10085331Shalini, Singh K. Power and area efficient hybrid memristor-CMOS based 2’s complement fsm for high-performance computing system. Proc. of the 2023 International Conference on Artificial Intelligence and Smart Communication (AISC), 2023, pp. 170–174. https://doi.org/10.1109/AISC56616.2023.10085331Nawaria M., Kumar S., Gautam M.K., Dhakad N.S., Singh R., Singhal S., Kumar P., Vishvakarma S.K., Mukherjee S. Memristorinspired digital logic circuits and comparison with 90-/180-nm CMOS technologies // IEEE Transactions on Electron Devices. 2024. V. 71. N 1. P. 301–307. https://doi.org/10.1109/TED.2023.3278625Nawaria M., Kumar S., Gautam M.K., Dhakad N.S., Singh R., Singhal S., Kumar P., Vishvakarma S.K., Mukherjee S. Memristorinspired digital logic circuits and comparison with 90-/180-nm CMOS technologies. IEEE Transactions on Electron Devices, 2024, vol. 71, no. 1, pp. 301–307. https://doi.org/10.1109/TED.2023.3278625Masoumi M. Novel hybrid CMOS/memristor implementation of the AES algorithm robust against differential power analysis attack // IEEE Transactions on Circuits and Systems II: Express Briefs. 2020. V. 67. N 7. P. 1314–1318. https://doi.org/10.1109/TCSII.2019.2932337Masoumi M. Novel hybrid CMOS/memristor implementation of the AES algorithm robust against differential power analysis attack. IEEE Transactions on Circuits and Systems II: Express Briefs, 2020, vol. 67, no. 7, pp. 1314–1318. https://doi.org/10.1109/TCSII.2019.2932337Radhakrishnan A., Babu S., James A. Python based memristor model library for variability analysis // Proc. of the 2023 IEEE International Symposium on Circuits and Systems (ISCAS). 2023. P. 1–5. https://doi.org/10.1109/ISCAS46773.2023.10181939Radhakrishnan A., Babu S., James A. Python based memristor model library for variability analysis. Proc. of the 2023 IEEE International Symposium on Circuits and Systems (ISCAS), 2023, pp. 1–5. https://doi.org/10.1109/ISCAS46773.2023.10181939Kumar R., Chordia A., Aswani A., James A., Tripathi J.N. Uncertainty quantification of memristor crossbar array for vector matrix multiplication // Proc. of the 2021 IEEE 25th Workshop on Signal and Power Integrity (SPI). 2021. P. 1–4. https://doi.org/10.1109/SPI52361.2021.9505193Kumar R., Chordia A., Aswani A., James A., Tripathi J.N. Uncertainty quantification of memristor crossbar array for vector matrix multiplication. Proc. of the 2021 IEEE 25th Workshop on Signal and Power Integrity (SPI), 2021, pp. 1–4. https://doi.org/10.1109/SPI52361.2021.9505193Khan R.A., Yang S., Fahad S., Khan S.U., Kalimullah. A modified particle swarm optimization with a smart particle for inverse problems in electromagnetic devices // IEEE Access. 2021. V. 9. P. 99932– 99943. https://doi.org/10.1109/ACCESS.2021.3095403Khan R.A., Yang S., Fahad S., Khan S.U., Kalimullah. A modified particle swarm optimization with a smart particle for inverse problems in electromagnetic devices. IEEE Access, 2021, vol. 9, pp. 99932– 99943. https://doi.org/10.1109/ACCESS.2021.3095403Swari M.H.P., Handika P.S., Satwika K.S., Wahani H.E. Optimization of single exponential smoothing using particle swarm optimization and modified particle swarm optimization in sales forecast // Proc. of the 2022 IEEE 8th Information Technology International Seminar (ITIS). 2022. P. 292–296. https://doi.org/10.1109/ITIS57155.2022.10010034Swari M.H.P., Handika P.S., Satwika K.S., Wahani H.E. Optimization of single exponential smoothing using particle swarm optimization and modified particle swarm optimization in sales forecast. Proc. of the 2022 IEEE 8th Information Technology International Seminar (ITIS), 2022, pp. 292–296. https://doi.org/10.1109/ITIS57155.2022.10010034Zhao Q., Li C. Two-stage multi-swarm particle swarm optimizer for unconstrained and constrained global optimization // IEEE Access. 2020. V. 8. P. 124905–124927. https://doi.org/10.1109/ACCESS.2020.3007743Zhao Q., Li C. Two-stage multi-swarm particle swarm optimizer for unconstrained and constrained global optimization. IEEE Access, 2020, vol. 8, pp. 124905–124927. https://doi.org/10.1109/ACCESS.2020.3007743Cui Y., Long Z. Load balancing scheduling algorithm based on improved particle swarm optimization // Proc. of the 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). 2021. P. 1044–1047. https://doi.org/10.1109/ICAICA52286.2021.9498058Cui Y., Long Z. Load balancing scheduling algorithm based on improved particle swarm optimization. Proc. of the 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA), 2021, pp. 1044–1047. https://doi.org/10.1109/ICAICA52286.2021.9498058Zhuo L., Cheng Z., Wang Y., Liu L. Design of vehicle trajectory optimization based on multiple-shooting method and modified particle swarm optimization // Proc. of the 2018 37th Chinese Control Conference (CCC). 2018. P. 4649–4654. https://doi.org/10.23919/ChiCC.2018.8483741Zhuo L., Cheng Z., Wang Y., Liu L. Design of vehicle trajectory optimization based on multiple-shooting method and modified particle swarm optimization. Proc. of the 2018 37th Chinese Control Conference (CCC), 2018, pp. 4649–4654. https://doi.org/10.23919/ChiCC.2018.8483741Mladenov V. Analysis and simulations of hybrid memory scheme based on memristors // Electronics. 2018. V. 7. N 11. P. 289. https://doi.org/10.3390/electronics7110289Mladenov V. Analysis and simulations of hybrid memory scheme based on memristors. Electronics, 2018, vol. 7, no. 11, pp. 289. https://doi.org/10.3390/electronics7110289Bondarev A.V., Efanov V.N. Features of the development of a mathematical model of an electric multipole with memresistive branches for nanoelectronic components of quantum computing systems // IOP Conference Series: Materials Science and Engineering. 2020. V. 976. N 1. P. 012010. https://doi.org/10.1088/1757-899X/976/1/012010Bondarev A.V., Efanov V.N. Features of the development of a mathematical model of an electric multipole with memresistive branches for nanoelectronic components of quantum computing systems. IOP Conference Series: Materials Science and Engineering, 2020, vol. 976, no. 1, pp. 012010. https://doi.org/10.1088/1757-899X/976/1/012010Bondarev A.V., Efanov V.N. Investigation of the robustness of nanoelectronic structures based on resonant tunneling elements // Russian Microelectronics. 2022. V. 51. N 7. P. 552–561. https://doi. org/https://doi.org/10.1134/S1063739722070022Bondarev A.V., Efanov V.N. Investigation of the robustness of nanoelectronic structures based on resonant tunneling elements. Russian Microelectronics, 2022, vol. 51, no. 7, pp. 552–561. https://doi.org/https://doi.org/10.1134/S1063739722070022Moore R.E. A survey of interval methods for differential equations // Proc. of the 23rd IEEE Conference on Decision and Control. 1984. P. 1529–1535. https://doi.org/10.1109/CDC.1984.272338Moore R.E. A survey of interval methods for differential equations. Proc. of the 23rd IEEE Conference on Decision and Control, 1984, pp. 1529–1535. https://doi.org/10.1109/CDC.1984.272338

The authors declare that there are no conflicts of interest present.