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Starts 10 July 2025 09:54

Ends 10 July 2025

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CXL Technology for AI and ML Workloads - Memory Expansion and Performance Optimization

Event Overview: Delve into the innovative world of CXL technology and understand its pivotal role in advancing AI and ML workloads. This course offers a deep dive into memory expansion, pooling, and sharing strategies tailored to enhance your understanding and mastery over performance optimization techniques essential for large language models..
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Overview

Event Overview:


Delve into the innovative world of CXL technology and understand its pivotal role in advancing AI and ML workloads. This course offers a deep dive into memory expansion, pooling, and sharing strategies tailored to enhance your understanding and mastery over performance optimization techniques essential for large language models.

What You'll Learn:

  • The fundamental principles of CXL technology and its applicability in AI/ML.
  • Advanced memory management techniques through CXL for enhanced productivity.
  • Practical approaches to optimizing performance in AI considerations.
  • Impact of memory expansion on the deployment of large language models.

Platform:

YouTube

Categories:

Artificial Intelligence Courses, Business Courses

Join this comprehensive course to equip yourself with state-of-the-art skills needed for optimizing AI and ML workloads using CXL technology.

Perfect for anyone looking to elevate their understanding of AI systems and apply learned strategies directly to business applications.

Syllabus

  • Introduction to CXL Technology
  • Overview of Compute Express Link (CXL)
    The role of CXL in modern computing
    Comparative analysis with other interconnect technologies
  • Memory Expansion with CXL
  • Fundamentals of memory expansion
    Benefits of increased memory bandwidth
    Use cases in AI/ML workloads
  • Memory Pooling and Sharing
  • Concepts of memory pooling
    Strategies for efficient memory sharing
    Managing memory with CXL in distributed environments
  • Performance Optimization for AI/ML
  • Key performance metrics for AI/ML workloads
    Techniques for optimizing memory usage
    Parallelism and concurrency improvements
  • CXL in Large Language Models
  • Memory demands of large language models
    Optimizing LLM performance with CXL
    Case studies and practical examples
  • Implementation Strategies
  • Steps for integrating CXL in existing systems
    Best practices for deployment
    Troubleshooting common issues
  • Case Studies and Industry Applications
  • Real-world applications of CXL in AI/ML
    Analysis of performance gains in various sectors
    Future trends and developments in CXL technology
  • Summary and Future Outlook
  • Recap of key concepts
    Emerging research and innovations
    Preparing for future advancements in CXL and AI/ML technologies

Subjects

Business