SNIA Developer Conference September 15-17, 2025 | Santa Clara, CA
Optimizing HDD Interface in the Generative AI Era
Abstract
Citigroup Inc. analysts quote, "Enterprise data is expected to continue to grow at over 40% CAGR as AI becomes an incremental driver for data creation, storage, and data management."
Today's AI ecosystem require fundamental shifts in the requirements of every datacenter infrastructure component. The predominant AI infrastructure strategy tends to currently focus on the most drastically impactful infrastructure components, as in GPUs, CPUs and Memory.
Unfortunately, this leaves a major gap in the detailed understanding of the various AI Storage Infrastructure usage models with regards to the various TCO optimized storage tiers and their requirements from a Capacity, Workloads and Performance.
Our presentation's focus is to inform and empower the audience of this session with key information and strategies that pertain specifically to the AI ecosystem impact on Mass Storage HDD Workloads, Performance, Capacity, Interface-Type and key advanced features that could potentially reshape the future of HDDs and their datacenter TCO optimization enablement.
Learning Objectives
Describe today's overall AI ecosystem strategy.
Define the current major AI infrastructure components and the role they play in the ecosystem.
Discuss the various types of AI usage models and their impact on the various storage tiers.
Understand the AI impact on HDD Mass Storage tier and how it must change and adapt.
Learn about the upcoming AI workload optimizations impacting HDD storage
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Optimizing HDD Interface in the Generative AI Era
Citigroup Inc. analysts quote, "Enterprise data is expected to continue to grow at over 40% CAGR as AI becomes an incremental driver for data creation, storage, and data management."
Today's AI ecosystem require fundamental shifts in the requirements of every datacenter infrastructure component. The predominant AI infrastructure strategy tends to currently focus on the most drastically impactful infrastructure components, as in GPUs, CPUs and Memory.
Unfortunately, this leaves a major gap in the detailed understanding of the various AI Storage Infrastructure usage models with regards to the various TCO optimized storage tiers and their requirements from a Capacity, Workloads and Performance.
Our presentation's focus is to inform and empower the audience of this session with key information and strategies that pertain specifically to the AI ecosystem impact on Mass Storage HDD Workloads, Performance, Capacity, Interface-Type and key advanced features that could potentially reshape the future of HDDs and their datacenter TCO optimization enablement.
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