Advanced DRAM and SRAM Technologies Essentials Training by Tonex
This course provides a comprehensive exploration of advanced DRAM and SRAM technologies, focusing on innovations, challenges, and applications. Participants will learn about high-bandwidth memory (HBM) in AI and HPC, emerging architectures, and strategies to overcome scaling limitations. The program blends theory with practical insights, enabling attendees to apply concepts in real-world scenarios.
Audience:
Engineers, researchers, technical managers, and professionals in semiconductor, AI, and HPC industries.
Learning Objectives:
- Understand advanced DRAM and SRAM architectures.
- Explore HBM and its role in modern computing.
- Analyze challenges in DRAM scaling.
- Learn practical applications of advanced memory technologies.
- Stay updated on trends in memory design.
- Gain skills for innovative memory solutions.
Course Modules:
Module 1: DRAM Architecture Innovations
- Evolution of DRAM designs.
- Emerging materials and technologies.
- High-speed DRAM interfaces.
- Energy-efficient DRAM solutions.
- Advanced row access techniques.
- Thermal management in DRAM systems.
Module 2: SRAM Architecture Innovations
- Low-power SRAM design techniques.
- High-speed SRAM operations.
- SRAM reliability and testing methods.
- 3D SRAM architectures.
- Memory integration in SoCs.
- Applications in AI and edge computing.
Module 3: High-Bandwidth Memory (HBM)
- HBM architecture and standards.
- HBM stacks and interconnects.
- Applications in AI and HPC.
- Power efficiency in HBM systems.
- Comparisons with other memory types.
- Integration challenges in HBM.
Module 4: Scaling Challenges in DRAM
- DRAM scaling bottlenecks.
- Process node limitations.
- Addressing cell capacitor issues.
- New approaches to data storage.
- Impact of DRAM scaling on performance.
- Future trends in scaling technologies.
Module 5: Emerging Memory Architectures
- Innovations in non-volatile memory.
- Hybrid memory solutions.
- Memory-centric computing paradigms.
- Architectures for AI workloads.
- Advances in memory bandwidth.
- System-level optimization techniques.
Module 6: Practical Applications and Case Studies
- AI and HPC memory requirements.
- Designing efficient memory subsystems.
- Case studies of HBM in real-world applications.
- DRAM and SRAM in autonomous systems.
- Optimization techniques for performance.
- Addressing thermal and power constraints.
Enroll in this course to master advanced DRAM and SRAM technologies and drive innovation in memory solutions.