新興記憶體技術
Emerging Memory Technologies
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 新興記憶體技術 EE116（光復） 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
Course descriptions and objectives： Semiconductor memory is the backbone of every modern computing system — from AI training clusters and data centers to automotive microcontrollers and edge IoT devices. This is a graduate-level course built around critical evaluation rather than recall: at each stage, students are asked not just how a device works, but why it scales, why it fails, and what trade-off the industry accepted to deploy it. The course follows a logical, end-to-end progression: MOSFET → CMOS Logic → Memory Cell → Memory Array → Conventional Memories → Emerging Memories → AI Hardware. Intended Learning Outcomes (ILOs)： By the end of this course, students will be able to: 1. Explain the relationships between semiconductor devices, memory circuits, and computing systems, and evaluate the trade-offs that govern memory technology selection. 2. Compare conventional and emerging memory technologies (SRAM, DRAM, Flash, ReRAM, PCM, FeRAM, and MRAM) from device, circuit, system, and manufacturing perspectives. 3. Critically analyze scientific and engineering literature, assess the strengths and limitations of existing technologies, and identify open research challenges. 4. Apply concepts from physics, materials science, electronics, and engineering to evaluate opportunities for innovation in memory and computing technologies. 5. Develop and defend research ideas by synthesizing knowledge from multiple disciplines and identifying potential directions for future semiconductor technologies
• Curiosity and interest in emerging semiconductor and computing technologies. • Basic understanding of semiconductor devices, electronic circuits, and digital logic is recommended but not strictly required. • Students from diverse engineering, physics, materials science, and related backgrounds interested in applying scientific knowledge to develop future technologies.
無備註
• Fundamentals via PowerPoint Slides, Video modules and simulation exercises • Advanced topics via research articles and industry case studies • Industry guest lecture
Presentation and Report: 20% Final Evaluation: 25% Homework/Assignments: 25% Literature Review & Discussion: 20% Class Participation: 10%
教師未提供此項資料
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course introduction |
| 第 2 週 | MOSFET Fundamentals; Threshold voltage; MOS electrostatics; I–V characteristics; NMOS vs PMOS; CMOS Device parameters |
| 第 3 週 | CMOS Logic Fundamentals; CMOS inverter; Noise margins; Power consumption; Delay |
| 第 4 週 | CMOS Logic to Memory Circuits; SRAM fundamentals; Sense amplifiers; Decoders; Memory arrays |
| 第 5 週 | Memory Hierarchy and Performance; Cache; SRAM; DRAM; Flash; Latency; Bandwidth; Energy |
| 第 6 週 | SRAM Design; 6T SRAM; Read/Write operation; Static Noise Margin (SNM); Scaling challenges |
| 第 7 週 | DRAM Technology; 1T1C cell; Refresh; DDR; LPDDR; High Bandwidth Memory (HBM) |
| 第 8 週 | Flash Memory; Floating-gate MOSFET; NAND vs NOR Flash; Charge Trap Flash; 3D NAND |
| 第 9 週 | Midterm Examination |
| 第 10 週 | Resistive Memories; ReRAM; OxRAM; CBRAM; Switching mechanisms; Crossbar arrays |
| 第 11 週 | Spintronic Memories; MTJ; STT-MRAM; SOT-MRAM; VCMA; Reliability and scaling |
| 第 12 週 | Emerging Spin-Based Memories; Racetrack Memory; Domain Wall Memory; Skyrmion Memory; Future concepts |
| 第 13 週 | Phase Change & Ferroelectric Memories; PCM; FeRAM; FeFET; Device fabrication and operation |
| 第 14 週 | Memory for AI Hardware; Compute-in-Memory (CIM); Processing-in-Memory (PIM); Neuromorphic Memory; AI accelerators and Co-Design concept, Memory Reliability and Manufacturing roadmaps |
| 第 15 週 | Review class; Student Presentations and Course Review |
| 第 16 週 | Final Examination |
1. B. Razavi, Fundamentals of Microelectronics, Wiley. [MOSFET & CMOS fundamentals] 2. J. Rabaey, A. Chandrakasan, B. Nikolić, Digital Integrated Circuits: A Design Perspective, Prentice Hall. [CMOS logic & memory circuits]
- 地點
- 教師未提供此項資料
- 時間
- Wednesday 14:00–16:00, or by appointment
- 聯絡方式
- ark.st08@nycu.edu.tw