Benefits of FC-NVMe for Containerized Machine Learning Models
Fibre Channel Industry Association - FCIA via YouTube
Overview
Learn how FC-NVMe technology enhances containerized machine learning models in this 51-minute webcast from industry experts. Explore Docker container fundamentals, machine learning principles, and storage access requirements for ML/DL workloads. Discover the architectural advantages of NVMe over Fibre Channel for machine learning applications, including improved performance and resource utilization. Master the implementation of containerized ML models using FC-NVMe through detailed technical discussions covering workflow optimization, shared storage solutions, and real-world use cases. Gain insights from HPE and Marvell specialists as they demonstrate how FC-NVMe addresses the resource-intensive demands of training data processing and model development while maintaining optimal performance levels.
Syllabus
Introduction
What is Docker
Machine Learning Fundamentals
Storage for Machine Learning
Machine Learning Workflow
Storage
Shared Storage
FCNVMe Architecture
Potential Use Cases
Proposed Solution
Performance Evolution
Summary
Questions
Taught by
Fibre Channel Industry Association - FCIA