Optimizing High Density Storage for AI and ML Applications

Learn how to optimize high-density storage systems for AI and ML applications in this 15-minute technical talk from Solidigm's Product Marketing Engineer. Explore the critical role of solid-state storage as an efficient alternative to hard drives in managing growing AI datasets and models. Gain insights into maximizing GPU utilization, reducing energy consumption, and scaling storage solutions for increasing data volumes. Dive deep into the AI data pipeline, examining key stages including data ingestion, preparation, model development, checkpointing, deployment, and archiving. Understand the workload characteristics and storage requirements at each pipeline stage, with special emphasis on addressing the demanding storage needs of generative AI development. Master the fundamentals of storage subsystem optimization to support the expanding computational and power demands of modern AI applications.