Storage for AI Applications

Presented by

Craig Tierney, NVIDIA; Brien Porter, Intel; Young Paik, Samsung; Tom Friend, Illuminosi

About this talk

Everyone enjoys having storage that is fast, reliable, scalable, and affordable. But it turns out different applications have different storage needs in terms of I/O requirements, capacity, data sharing, and security. Some need local storage, some need a centralized storage array, and others need distributed storage—which itself could be local or networked. One application might excel with block storage while another with file or object storage. With limited resources, it’s important to understand the storage intent of the applications in order to choose the right storage and storage networking strategy, rather than discovering the hard way that you’ve chosen the wrong solution for your application. Artificial intelligence (AI) is a technology which itself encompasses a broad range of use cases, largely divided into training and inference. In this webcast, we’ll look at what types of storage are typically needed for different aspects of AI, including different types of access (local vs. networked, block vs. file vs. object) and different performance requirements. And we will discuss how different AI implementations balance the use of on-premises vs. cloud storage. Tune in to this SNIA Networking Storage Forum (NSF) webcast to boost your natural (not artificial) intelligence about application-specific storage. After you watch the webcast, check out the Q&A blog at
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SNIA is a not-for-profit global organization made up of corporations, universities, startups, and individuals. The members collaborate to develop and promote vendor-neutral architectures, standards, and education for management, movement, and security for technologies related to handling and optimizing data. SNIA focuses on the transport, storage, acceleration, format, protection, and optimization of infrastructure for data.