Google Cloud Storage Solutions for AI and ML Workloads - Performance Optimization and Management

Watch a comprehensive technical presentation where Dave Stiver, Group Product Manager at Google Cloud, delves into cloud storage solutions optimized for AI/ML workloads. Learn about critical components of the AI data pipeline including training, checkpoints, and inference, with a focus on developer-friendly storage interfaces. Explore key features like GCS FUSE for mounting cloud storage buckets as local file systems and Anywhere Cache for enhanced data access speeds near accelerators. Discover real-world implementation through Toyota's Woven case study, which achieved 50% cost reduction and 14% faster training times by switching to GCS FUSE. Understand the architecture and benefits of Parallel Store, a fully managed parallel file system built on DAOS technology for high-throughput AI workloads. Gain insights into managing large datasets across hybrid environments while optimizing both cost and performance for diverse organizational needs in the evolving AI landscape.