High-Performance AI/ML Inference with 24G GDDR6 Memory

A rapid rise in the size and sophistication of AI/ML inference models requires increasingly powerful hardware deployed at the network edge and in endpoint devices. This webinar will explore how GDDR6, operating at data rates up to 24 Gigabits per second (Gb/s) supports the memory and performance requirements of AI/ML inference workloads through an excellent combination of high bandwidth and low latency performance. Frank Ferro and Vinitha Seevaratnam will also discuss the design and implementation considerations of GDDR6 memory subsystems with a particular emphasis on signal integrity challenges at ultra-high data rates.

Featured Speakers

Frank Ferro

Senior Director, Product Marketing, Rambus

Frank Ferro is the senior director of product management at Rambus Inc. responsible for memory interface IP products. Having spent more than 20 years at AT&T, Lucent and Agere Systems, he has extensive experience in wireless communications, networking and consumer electronics fields. Mr. Ferro holds an executive MBA from the Fuqua School of Business at Duke University, an M.S. in computer science and a B.S.E.T. in electronic engineering technology from the New Jersey Institute of Technology.

Vinitha Seevaratnam

Senior Product Marketing Manager, Rambus

Vinitha Seevaratnam is the Sr. Product Marketing Manager at Rambus, an IP Core provider specializing in Memory, PCI Express and MIPI controller cores. Vinitha’s primary focus during her 20+ year career has been in semiconductor and communication/storage product segments. Her 14+ years has been with Rambus (formerly Northwest Logic). Prior to Rambus, Vinitha worked at Northwest Logic, Thomson Grass Valley, Tektronix, Inc., and Mentor Graphics. She has a B.S. from University of Washington in Electrical Engineering.