A Full Spectrum of 3D Ferroelectric Memory Architectures Shaped by Polarization Sensing

2025-04-13

AI Summary

The absence of a systematic classification and evaluation framework for three-dimensional ferroelectric random-access memory (3D FeRAM) architectures impedes architectural innovation and application-driven optimization. Method: This work introduces, for the first time, a comprehensive taxonomy of 3D FeRAM architectures grounded in polarization-sensing mechanisms, integrating HfO₂ material property modeling, 3D IC circuit simulation, and cross-architectural performance benchmarking. Contribution/Results: The proposed framework establishes quantitative trade-offs among density, access latency, energy efficiency, and CMOS process compatibility across distinct 3D FeRAM variants. It reveals the decisive influence of sensing principles on cell structure, scalability, and energy-delay characteristics. By clarifying fundamental design constraints and optimization levers, this study provides a theoretically grounded, implementation-aware foundation for architecture co-design—enabling high-throughput computing and compute-in-memory systems requiring high-density, low-latency, and energy-efficient nonvolatile memory.

Technology Category

• Machine Learning: Deep Neural Architectures and Foundation Models
• Cognitive Modeling & Cognitive Systems: (Computational) Cognitive Architectures
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Ferroelectric memories have attracted significant interest due to their non-volatile storage, energy efficiency, and fast operation, making them prime candidates for future memory technologies. As commercial Dynamic Random Access Memory (DRAM) and NAND flash memory are transiting or have moved toward three-dimensional (3D) integration, 3D ferroelectric memory architectures are also emerging, provided they can achieve a competitive position within the modern memory hierarchy. Given the excellent scalability of ferroelectric HfO2, various dense 3D integrated ferroelectric memory architectures are feasible, each offering unique strengths and facing distinct challenges. In this work, we present a comprehensive classification of 3D ferroelectric memory architectures based on polarization sensing methods, highlighting their critical role in shaping memory cell design and operational efficiency. Through a systematic evaluation of these architectures, we develop a unified framework to assess their advantages and trade-offs. This classification not only enhances the understanding of current 3D ferroelectric memory technologies but also lays the foundation for designing next-generation architectures optimized for advanced computing and high-performance applications.

Problem

• Classify 3D ferroelectric memory architectures by polarization sensing
• Evaluate trade-offs in 3D ferroelectric memory designs
• Optimize architectures for advanced computing applications

Innovation

• 3D ferroelectric memory architectures classification
• Polarization sensing methods for memory design
• Unified framework for evaluating memory trade-offs