Video Player is loading.
Current Time 0:00
Duration 0:00
Loaded: 0%
Stream Type LIVE
Remaining Time 0:00
 
1x
    • Chapters
    • descriptions off, selected
    • subtitles off, selected
      • Quality

      Getting the Storage Right for AI Applications

      , Distinguished Engineer, NVIDIA
      , Field Chief Technology Officer and Head of of Strategy, VAST Data
      , Chief Storage Architect, Dell
      , CTO, DDN
      , Vice President of Engineering, NetApp
      , VP Storage Technology, NVIDIA
      Today’s evolving landscape of generative AI poses challenges for storage. Storage platforms need to have high capacity, high performance, high bandwidth, and low latency to support the data ingestion, preparation, training, and inference stages of generative AI. Because generative AI models can work with different kinds of data such as text, images, audio, video, or combinations thereof, the storage platform has to handle different file systems, protocols, and networks to access data efficiently and securely. We'll explore several key topic areas, such as hybrid, multi-cloud, data migration, security, the impact of storage on underlying functions like check-pointing and replication, and scaling storage capacity up or down. We've assembled a panel of experts from across the NVIDIA storage partner ecosystem to provide insight on how to avoid potential issues to get the most out of your storage for different AI applications.
      活动: GTC 24
      日期: March 2024
      NVIDIA 技术: BlueField DPU,DOCA,Ethernet Networking,Infiniband Networking,Magnum IO
      级别: 通用
      行业: HPC / 科学计算
      话题: Storage Networking & Security
      语言: 英语
      所在地: