Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers
This article proposes a new mathematical model that accurately predicts statistical margin characteristics of bit-line sense amplifiers (BLSAs) with offset calibration (OC) and pre-sensing (PS), while providing techniques to improve sensing margins. In particular, threshold voltage mismatch caused b...
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| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10843701/ |
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| author | Dongyeong Kim Geon Kim Suyeon Kim Jewon Park Sinwook Kim Hyeona Seo Chaehyuk Lim Sowon Kim Juwon Lee Jeonghyeon Yun Hyerin Lee Jinseok Park Yongbok Lee Seungchan Lee Myoungjin Lee |
| author_facet | Dongyeong Kim Geon Kim Suyeon Kim Jewon Park Sinwook Kim Hyeona Seo Chaehyuk Lim Sowon Kim Juwon Lee Jeonghyeon Yun Hyerin Lee Jinseok Park Yongbok Lee Seungchan Lee Myoungjin Lee |
| author_sort | Dongyeong Kim |
| collection | DOAJ |
| description | This article proposes a new mathematical model that accurately predicts statistical margin characteristics of bit-line sense amplifiers (BLSAs) with offset calibration (OC) and pre-sensing (PS), while providing techniques to improve sensing margins. In particular, threshold voltage mismatch caused by reduced transistor sizes introduces sensing offsets, further degrading the already limited sensing margins under low-voltage conditions. While various BLSAs incorporating OC and PS techniques have been proposed to address these challenges, and studies have been conducted on models predicting statistical offset, previous research has not adequately considered OC timing (<inline-formula> <tex-math notation="LaTeX">$t_{OC}$ </tex-math></inline-formula>) and transistor size effects. We independently model the OC, charge sharing (CS), and PS operations of DRAM BLSAs to accurately predict both deterministic and stochastic offsets resulting from various operation combinations. Notably, our model incorporates <inline-formula> <tex-math notation="LaTeX">$t_{OC}$ </tex-math></inline-formula> dependency, which was not considered in previous models, and accurately analyzes transistor size effects through integration with Pelgrom’s equation. The primary advantage of the proposed model lies in its design optimization efficiency. While HSPICE simulations combining Monte Carlo (MC) and binary search methods require numerous iterations for single design point verification, our model significantly reduces design time by effectively narrowing the region of interest through pre-optimization using statistical characteristics. Furthermore, the model’s general form demonstrates high practicality through easy application to various BLSA types based on OC scheme types and PS operation presence. In conclusion, this article presents optimal design guidelines by accurately predicting deterministic and stochastic offset characteristics according to <inline-formula> <tex-math notation="LaTeX">$t_{OC}$ </tex-math></inline-formula> and transistor size ratios, showing high correlation with HSPICE MC simulation results. |
| format | Article |
| id | doaj-art-6682ff6fe2e64af1b9605c1348329531 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-6682ff6fe2e64af1b9605c13483295312025-01-25T00:01:05ZengIEEEIEEE Access2169-35362025-01-0113141651417610.1109/ACCESS.2025.353041210843701Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense AmplifiersDongyeong Kim0https://orcid.org/0000-0002-5942-329XGeon Kim1Suyeon Kim2https://orcid.org/0000-0002-4837-9916Jewon Park3https://orcid.org/0000-0002-7366-8840Sinwook Kim4https://orcid.org/0009-0004-3052-1293Hyeona Seo5Chaehyuk Lim6Sowon Kim7Juwon Lee8Jeonghyeon Yun9Hyerin Lee10Jinseok Park11https://orcid.org/0000-0001-7743-4112Yongbok Lee12Seungchan Lee13https://orcid.org/0000-0002-9959-9660Myoungjin Lee14https://orcid.org/0000-0002-9489-3801Department of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaDepartment of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, South KoreaThis article proposes a new mathematical model that accurately predicts statistical margin characteristics of bit-line sense amplifiers (BLSAs) with offset calibration (OC) and pre-sensing (PS), while providing techniques to improve sensing margins. In particular, threshold voltage mismatch caused by reduced transistor sizes introduces sensing offsets, further degrading the already limited sensing margins under low-voltage conditions. While various BLSAs incorporating OC and PS techniques have been proposed to address these challenges, and studies have been conducted on models predicting statistical offset, previous research has not adequately considered OC timing (<inline-formula> <tex-math notation="LaTeX">$t_{OC}$ </tex-math></inline-formula>) and transistor size effects. We independently model the OC, charge sharing (CS), and PS operations of DRAM BLSAs to accurately predict both deterministic and stochastic offsets resulting from various operation combinations. Notably, our model incorporates <inline-formula> <tex-math notation="LaTeX">$t_{OC}$ </tex-math></inline-formula> dependency, which was not considered in previous models, and accurately analyzes transistor size effects through integration with Pelgrom’s equation. The primary advantage of the proposed model lies in its design optimization efficiency. While HSPICE simulations combining Monte Carlo (MC) and binary search methods require numerous iterations for single design point verification, our model significantly reduces design time by effectively narrowing the region of interest through pre-optimization using statistical characteristics. Furthermore, the model’s general form demonstrates high practicality through easy application to various BLSA types based on OC scheme types and PS operation presence. In conclusion, this article presents optimal design guidelines by accurately predicting deterministic and stochastic offset characteristics according to <inline-formula> <tex-math notation="LaTeX">$t_{OC}$ </tex-math></inline-formula> and transistor size ratios, showing high correlation with HSPICE MC simulation results.https://ieeexplore.ieee.org/document/10843701/DRAMsense amplifierlow voltagemismatchsensing offset |
| spellingShingle | Dongyeong Kim Geon Kim Suyeon Kim Jewon Park Sinwook Kim Hyeona Seo Chaehyuk Lim Sowon Kim Juwon Lee Jeonghyeon Yun Hyerin Lee Jinseok Park Yongbok Lee Seungchan Lee Myoungjin Lee Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers IEEE Access DRAM sense amplifier low voltage mismatch sensing offset |
| title | Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers |
| title_full | Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers |
| title_fullStr | Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers |
| title_full_unstemmed | Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers |
| title_short | Model-Based Variation-Aware Optimization for Offset Calibration and Pre-Sensing in DRAM Sense Amplifiers |
| title_sort | model based variation aware optimization for offset calibration and pre sensing in dram sense amplifiers |
| topic | DRAM sense amplifier low voltage mismatch sensing offset |
| url | https://ieeexplore.ieee.org/document/10843701/ |
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