Interface IP
Memory Controllers
Silicon-proven, high-performance memory controller cores are optimized for use in SoCs, ASICs and FPGAs. These market leading solutions for memory interfaces address AI, automotive, data center, network edge, IoT and mobile applications.
Contact| Product | Product Brief | Protocol | Application |
|---|---|---|---|
| GDDR6 Controller |  |
GDDR6 | AI, Automotive, Graphics |
| HBM3 Controller | |
HBM3 | AI, HPC, Data Center, Graphics |
| HBM2E Controller | |
HBM2, HBM2E | AI, HPC, Data Center, Graphics |
| LPDDR5 Controller | |
LPDDR5 | Mobile, IoT, Automotive |
| LPDDR4 Controller | |
LPDDR4 | Mobile, IoT, Automotive |
| DDR4 Controller | |
DDR4 | Data Center, Edge |
| DDR3 Controller | |
DDR3 | IoT, Edge |
Standards Compatible
Faster time-to-market
Fully verified
Flexible Design
Full programmability
Customization options
Reduced Power
Power optimized
Minimum gate count
Improved Performance
Industry-leading data rates
High memory throughput
HBM2E and GDDR6: Memory Solutions for AI
Artificial Intelligence/Machine Learning (AI/ML) growth proceeds at a lightning pace. In the past eight years, AI training capabilities have jumped by a factor of 300,000 driving rapid improvements in every aspect of computing hardware and software. Meanwhile, AI inference is being deployed across the network edge and in a broad spectrum of IoT devices including in automotive/ADAS. Training and inference have unique feature requirements that can be served by tailored memory solutions. Learn how HBM2E and GDDR6 provide the high performance demanded by the next wave of AI applications.
2.5D/3D Packaging Solutions for AI and HPC
For AI and HPC applications, HBM2E memory can deliver excellent bandwidth, capacity and latency in a very compact footprint thanks to its 2.5D/3D structure. The flipside is that this same structure leads to greater design complexity and raises a new set of implementation considerations.