Jay Gite | Sr. Thermal Product Design Engineer
NVIDIA
Jay Gite is a Thermal Engineer at NVIDIA, where he specializes in architecting, designing, and executing air cooled and liquid cooled solutions for HPC data center products. He also has prior experience working on battery thermal management at Tesla and working on consumer electronic products at Crestron Electronics. Jay obtained his MS in mechanical engineering from SUNY – Stony Brook University with a thesis on developing a novel thermal energy storage system. Throughout his academic and professional career, he has focused on developing an expertise for implementing the fundamentals of heat transfer and fluid dynamics for practical applications.
Appearances:
Future of Memory and Storage - Day 2 @ 15:35
Thermal Evolution for Next-Generation SSDs: From Air to Liquid Cooling and Enabling AI Inference at Scale
As data center workloads diversify across storage, compute, and AI platforms, thermal management strategies must evolve to meet distinct operational demands. Traditional air cooling remains viable for conventional storage with moderate power envelopes, while compute-intensive and AI environments increasingly demand direct liquid cooling and immersion solutions for targeted heat extraction at extreme power densities.
This presentation quantifies thermal dissipation budgets across cooling technologies—comparing air, direct liquid, and immersion cooling capabilities for current and next-generation SSDs operating at PCIe Gen6 and Gen7 power levels. We examine how each cooling approach aligns with specific platform requirements and power roadmaps. For newer applications like network attached storage used for inference, high-density SSDs are not only nice to have, but requirements. With interface speeds, even at network attached storage, moving from Gen5 to Gen6 and 7, thermal management becomes a priority, especially when massive scale of storage deployment is needed to feed data to AI compute. The session will also cover impact to SSD thermal architecture due to fan-less AI servers.
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