1-112Gbps Medium Reach (MR) and Very Short Reach (VSR) SerDes
Enflame Technology Selects Rambus HBM2 Memory Subsystem Solution For Next-Generation AI Training Chip
SUNNYVALE, Calif. – Dec. 11, 2019 – Rambus Inc. (NASDAQ: RMBS) a premier silicon IP and chip provider making data faster and safer, today announced that Enflame (Suiyuan) Technology has selected Rambus HBM2 PHY and Memory Controller IP for its next-generation AI training chip. Rambus memory interface IP enables the development of high-performance, next-generation hardware for leading-edge AI applications.
“Artificial intelligence training requires far greater memory bandwidth than standard compute applications. Rambus’ proven HBM2 memory subsystem IP delivers the ultra-high bandwidth performance our AI chips need,” said Arthur Zhang, COO of Enflame Technology. “Using Rambus interface IP cores, we are revolutionizing what’s possible in AI technology.”
Optimized for low-latency and high-bandwidth memory applications, the Rambus HBM2 interface solution delivers maximum performance and flexibility in minimal form factor and power envelope. The comprehensive HBM2 subsystem solution of PHY and memory controller provides 2Tb/s of bandwidth, making it the perfect fit for Enflame Technology’s cloud AI training needs. Complementing this interface IP, Rambus provides silicon interposer and package reference designs, and supports signal and power integrity (SI/PI) analysis.
“Enflame Technology’s repeat choice of Rambus showcases our HBM2 PHY and memory controller IP as the ideal solution for complex neural network-based AI and machine learning chips,” said Hemant Dhulla, vice president and general manager of IP Cores at Rambus. “Our HBM portfolio of solutions already in volume production deliver the memory performance needed at the frontier of AI computing.”
For more information on Rambus HBM2 PHY offerings, please visit https://www.rambus.com/interface-ip/ddrn-phys/hbm/. Find out more details on Rambus Memory Controllers at https://www.rambus.com/interface-ip/controllers/memory-controllers/.
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