Accelerate AI Workloads with Rambus HBM4E Memory Controller
March 05, 2026
News
Rambus Inc. announced its HBM4E Memory Controller IP capable of facilitating innovative HBM memory deployments for next-generation AI accelerators, graphics, and HPC applications. It operates at up to 16 Gigabits per second (Gbps) per pin delivering a throughput of 4.1 Terabytes per second (TB/s) to each memory device. For an AI accelerator with eight attached HBM4E devices, this translates to over 32 TB/s of memory bandwidth for demanding AI workloads.
The solution is compatible with third-party standard or TSV PHY solutions to integrate a complete HBM4E memory subsystem into a 2.5D or 3D package for AI SoC or custom die solutions.
“Given the insatiable bandwidth demands of AI, it’s imperative for the memory ecosystem to continue aggressively advancing memory performance,” said Simon Blake-Wilson, SVP and general manager of Silicon IP, at Rambus. “As a leading silicon IP provider for AI applications, we are bringing the industry’s leading HBM4E Controller IP solution to the market as a key enabler for breakthrough performance in next-generation AI processors and accelerators.”
Per the press release, the HBM4E Controller is available for licensing, and early access design customers can engage today.
For more information, visit rambus.com/interface-ip/hbm/.
Chad Cox is the Production Editor at Embedded Computing Design. His responsibilities are centered around content creation, writing and editing, and article research and development. Chad covers industry news and events and is known to interact with various industrial leaders via on-premise visits and online interviews. He is responsible for the digital footprint and dissemination of news via social media posts, advertising creation and the production of newsletters including the Embedded Computing Design’s Daily.
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Chad graduated from the University of Cincinnati with a B.A. in Cultural and Analytical Literature and holds a master’s in education.
