[Aug 18 at 11am PT] Join Rambus for a live webinar as we explore the industry’s transition from traditional aggregated servers to modern scale-up, scale-out, and disaggregated architectures. We will also discuss the critical role of PCI Express® (PCIe®) as the foundational interconnect for next-generation infrastructure and explains how PCIe switches and PCIe retimers enable scalable, high-performance connectivity across increasingly disaggregated environments.
Interface IP
HBM4E Advances Bandwidth Performance for AI Training
[Live on April 8 at 11am PT] Join Rambus for a technical deep dive into HBM4E and the industry-leading HBM4E Memory Controller IP. In this webinar, Nidish Kamath from Rambus will walk through the key requirements driving HBM4E adoption and introduce Rambus’ newly announced HBM4E Memory Controller IP.
Scaling AI Infrastructure with PCIe 7 and CXL 3
Interconnect technologies are key to scaling AI workloads across data center infrastructure. Learn how PCIe 7 and CXL 3 enable high-speed, low-latency connectivity for memory expansion and composable architectures in AI systems.
Memory IP for AI Accelerators: HBM4, LPDDR5, and GDDR7
AI accelerators require high-performance memory IP to meet bandwidth, capacity and latency requirements. This session dives into Rambus IP solutions for HBM4, LPDDR5, and GDDR7, highlighting their role in powering next-gen AI silicon.
35 Years of Memory Innovation for AI
In this keynote, Dr. Steve Woo reflects on the 35-year journey of Rambus and the evolution of memory technology that has culminated in today’s AI-driven computing landscape. From early innovations to modern high-bandwidth architectures, this session highlights how memory has become a foundational enabler of artificial intelligence.
Empowering Autonomous Driving: the Impact of MIPI CSI-2 on Advanced Sensor Technologies
[Live on 11/6 at 8am PT] The pursuit of autonomous driving is accelerating the widespread adoption of sensors such as cameras, LIDAR, radar and ultrasound. As significant progress is being made toward fully autonomous vehicles, Advanced Driver Assistance Systems (ADAS) are also becoming increasingly sophisticated by leveraging these sensors. These devices capture vital information about the vehicle’s surroundings, which is then processed and interpreted to provide real-time assistance to drivers. As sensor resolution improves, the data that must be transmitted to processing or display subsystems grows, demanding reliable and performant interfaces with high bandwidth, low power consumption and low latency. This session explores how MIPI CSI-2 technology addresses these challenges, enabling efficient data transmission for ADAS applications.
