Uploaded November 2025 | Updated September 2026, 2 weeks ago
This presentation examines the transformative role of Compute Express Link (CXL) technology in addressing the critical challenges of memory scaling within modern computing architectures. As data-intensive applications in graph analytics, machine learning, and recommendation engines continue to demand exponentially increasing memory resources, traditional memory architectures face significant limitations in scalability and efficiency. The presentation provides a comprehensive analysis of current memory architecture challenges, including CPU memory channel limitations and resource utilization inefficiencies, before exploring how CXL's innovative protocol stack offers solutions through its three key components: CXL.IO, CXL.cache, and CXL.mem.
We present some real data points from our experiment using distributed in-memory database as workload running on a clustered platform with CXL used as memory expander, well complemented by Samsung Cognos. The experiment shows 5x capacity increase and meeting the targeted performance/SLA.
These findings suggest that CXL represents a fundamental shift in memory architecture design, offering a viable pathway for meeting the escalating memory demands of next-generation computing applications while maintaining efficiency and cost-effectiveness.
Presented by Pramod Peethambaran, Samsung
Learn More:
• SDC Website: snia.org/sniadeveloper
• SNIA Website: snia.org
• SNIA Educational Library: snia.org/library
• X: twitter.com/SNIA
• LinkedIn: linkedin.com/company/snia
This presentation examines the transformative role of Compute Express Link (CXL) technology in addressing the critical challenges of memory scaling within modern computing architectures. As data-intensive applications in graph analytics, machine learning, and recommendation engines continue to demand exponentially increasing memory resources, traditional memory architectures face significant limitations in scalability and efficiency. The presentation provides a comprehensive analysis of current memory architecture challenges, including CPU memory channel limitations and resource utilization inefficiencies, before exploring how CXL's innovative protocol stack offers solutions through its three key components: CXL.IO, CXL.cache, and CXL.mem.
We present some real data points from our experiment using distributed in-memory database as workload running on a clustered platform with CXL used as memory expander, well complemented by Samsung Cognos. The experiment shows 5x capacity increase and meeting the targeted performance/SLA.
These findings suggest that CXL represents a fundamental shift in memory architecture design, offering a viable pathway for meeting the escalating memory demands of next-generation computing applications while maintaining efficiency and cost-effectiveness.
Presented by Pramod Peethambaran, Samsung
Learn More:
• SDC Website: snia.org/sniadeveloper
• SNIA Website: snia.org
• SNIA Educational Library: snia.org/library
• X: twitter.com/SNIA
• LinkedIn: linkedin.com/company/snia
