AI Requires Tailored DRAM Solutions: Part 3
Frank Ferro, Senior Director Product Management at Rambus, and Shane Rau, Senior Research Executive at IDC, recently hosted a webinar that explores the role of tailored DRAM solutions in advancing artificial intelligence. Part two of this four-part series touched on multiple topics including how AI enables useful data processing, various types of AI silicon, and the evolving role of DRAM. This blog post (part three) takes a closer look at the impact of AI on specific hardware systems, training versus inference, and selecting the most appropriate memory for AI/ML applications.
To read the full article, click here
Related Semiconductor IP
Related Blogs
- AI Requires Tailored DRAM Solutions: Part 1
- AI Requires Tailored DRAM Solutions: Part 2
- AI Requires Tailored DRAM Solutions: Part 4
- Redefining XPU Memory for AI Data Centers Through Custom HBM4 – Part 3
Latest Blogs
- The Silent Guardian of AI Compute - PUFrt Unifies Hardware Security and Memory Repair to Build the Trust Foundation for AI Factories
- Heterogeneous NPU Data Movement Tax: Intel's Own Slides Tell the Story
- PQMicroLib-Core now supports PSA Certified Crypto API
- Imagination Demonstrates DirectX Gaming on D-Series GPUs
- Embedded Security explained: Post-Quantum Cryptography (PQC) for embedded Systems