Rakesh Cheerla | Vice President of Products
Netpreme Corporation

Future of Memory and Storage - Day 2 @ 10:20

The Rise of Disaggregated Tiered Memory/Storage Fabrics

AI data centers are shifting from GPU-centric compute scaling to memory-centric system design. The rise of long-context models, persistent agents, and reinforcement-learning workflows is reshaping infrastructure requirements. Inference is no longer a stateless, token-by-token task—it is a distributed, multi-tier memory problem spanning HBM, host DRAM, NVMe, and network fabrics. Innovations such as disaggregated prefill/decode, KV cache offload, LMCache, and NVIDIA’s Dynamo/SCADA architecture signal a broader shift toward GPU-initiated storage and hierarchical memory orchestration. This session explores how product leaders and architects must rethink memory, storage, and network co-design to support agentic, persistent, and diverse AI communication workloads at scale.

Rakesh Cheerla, Vice President of Products, Netpreme Corporation

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Rakesh Cheerla / The Rise of Disaggregated Tiered Memory/Storage Fabrics

Rakesh Cheerla, Vice President of Products,
Netpreme Corporation

With over a decade of experience in top tech companies like Sun Microsystems and Dell, James leads the technology roadmap and analytics for AI and High-Performance Computing (HPC) solutions at DDN. Holding a PhD in Theoretical Physics, he brings deep scientific insight into advancing full-solution...

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