Watch a technical presentation exploring Compute Express Link (CXL) technology, delivered by MemVerge CEO Charles Fan at Tech Field Day 27. Learn about the evolution from CXL 1.1 through 3.0, examining how this new memory bus technology addresses modern data-centric application challenges and memory limitations. Discover practical applications through detailed use cases, including dynamic elastic memory management, thin provisioning, memory auto-healing, distributed database caching, and AI workload optimization. Gain insights into memory pooling, switch fabric architecture, and memory sharing capabilities while understanding the market potential and impact on big memory solutions. Explore how CXL technology helps reduce stranded memory, enables transparent migration, and facilitates zero-copy data sharing in modern computing environments.
Introduction to CXL Technology and Memory Management Use Cases
Overview
Syllabus
Intro
The Rise of Modern Data-Centric Applications
The Memory Wall
CXL: A New Memory Bus!
A Generational Opportunity
Usage Models & Device Types
CXL v1.1 - Memory Expansion
CXL 2.0 Memory Pooling
CXL 3.0 Switch Fabric & Memory Sharing
Gartner Early Estimate of CXL DRAM TAM
Use Case: Dynamic Elastic Memory Reduces Stranded Memory
Use Case: Thin Provisioning Dynamic Allocation on Demand
Use Case: Memory Auto-healing With Transparent Migration
Use Case: Distributed Database Caching
Use Case: Distributed Application Data Shuffling
Use Case: Avoid Al Worker Node Memory Spill
Use Case: Zero-copy Data Sharing With CXL Memory Sharing
Big Memory
Taught by
Tech Field Day
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Memory Disaggregation and Pooling with CXL - Architecture and Services
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CXL 3.0 - Expanded Capabilities for Memory Pooling and Resource Optimization
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Server Fabrics and the Evolution to CXL 3.0 - Memory and Resource Management in Heterogeneous Computing
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Computing with CXL Memory Devices - Memory Expansion and Computational Offloading
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CXL 2.0 Switch Technology - Enabling Next-Era Big Memory Computing
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CXL Technology for AI and ML Workloads - Memory Expansion and Performance Optimization
