CXL 메모리 풀링 및 분산형 인프라 시장 : 시장 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the CXL memory pooling and Disaggregated Infrastructure Market size is projected to be USD 0.96 billion in 2025, USD 1.39 billion in 2026, and reach USD 5.42 billion by 2031, growing at a CAGR of 31.28% from 2026 to 2031.

This report is Segmented by Component (CXL Memory Modules, CXL Controllers, CXL Switches, and Software and Orchestration), Deployment Architecture (Memory Expansion, and More), Application (Artificial Intelligence and Machine Learning, High-Performance Computing and Scientific Computing, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global CXL Memory Pooling and Disaggregated Infrastructure Market Trends and Insights

AI Cluster Memory Wall Pressure

The gap between accelerator throughput and on-server DRAM capacity is the strongest immediate force behind adoption in the CXL memory pooling and disaggregated infrastructure market. DDR5 server memory costs stood at USD 30-40 per GB in 2026, while AI workloads are doubling memory needs every 18 months, which made simple DIMM-based scaling expensive for hyperscalers and enterprise AI operators alike. Shared CXL pools let KV cache demand extend beyond local DRAM at near-DRAM latency, helping avoid GPU underuse and reducing inference cost per token. This pressure is especially visible in inference systems, where token economics depend heavily on memory efficiency rather than on raw training throughput alone. Penguin Solutions launched the first production-ready CXL-based KV cache server in March 2026, with up to 11 TB of CXL-based memory and 10x faster speeds than NVMe-based approaches, demonstrating that commercial deployments had moved beyond the pilot stage.

Hyperscale Shift to Composable Infrastructure

Hyperscalers are restructuring data center procurement around composable pools where memory, compute, and accelerators can be provisioned independently and moved as workloads change. That shift is tied to GPU utilization economics and rack-density limits, pushing the CXL memory pooling and disaggregated infrastructure market toward rack-scale designs rather than server-bound memory expansion alone. This change raises demand for switching fabrics that can make shared memory a standard rack component rather than a niche attachment. Astera Labs said its Scorpio X-Series 320-lane Smart Fabric Switch entered the production ramp in H2 2026 and cuts AllReduce latency by at least 50%, providing operators with a practical path toward larger pooled deployments. As these fabrics become more common in AI racks, the marginal cost of adding disaggregated memory tiers falls, making the software case for dynamic memory allocation easier to justify.

Interoperability Gaps Across CXL Generations and Vendor Stacks

Interoperability remains a real brake on procurement even as standardization improves. Research showed that the CXL cache-coherence protocol still lacks mechanisms to guarantee safe interoperability across heterogeneous host architectures with different memory consistency models, forcing platform-device qualification on a pair-by-pair basis. That raises engineering cost for buyers who want multi-vendor pools and do not have the internal validation capacity of hyperscalers. The issue is sharper at the fabric layer, where switch implementations are still maturing and where production-ready topologies are not yet fully uniform across vendors. As a result, the CXL memory pooling and disaggregated infrastructure market is progressing fastest, where buyers can control hardware combinations closely and absorb longer qualification cycles.

Other drivers and restraints analyzed in the detailed report include:

1. Standardization of CXL 3.x and 4.0 Fabric Features
2. Energy Efficiency and Rack Utilization Gains from Memory Pooling
3. Limited Volume Availability of Production-Qualified CXL Type 3 and Switch Ecosystems

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

CXL Switches are the fastest-growing component in the CXL memory pooling and disaggregated infrastructure markett, with a 32.57% CAGR through 2031, as architecture moves from single-server expansion toward rack-level shared memory fabrics. Marvell announced the Structera S 30260, a 260-lane CXL 3.0 switch developed through the XConn Technologies acquisition, and said sampling would begin in Q3 2026, making it the first switch purpose-built for AI rack-scale memory pooling. The switch ramp is closely tied to CPU platform readiness because multi-host fabric features require newer processor generations, which are arriving through 2026 and 2027. That keeps near-term switch volumes modest even as the CXL memory industry positions this category for stronger revenue concentration later in the forecast period.

CXL Memory Modules commanded 44.17% share of the CXL memory pooling and disaggregated infrastructure market size in 2025, supported by Type 3 memory expander adoption on CXL 2.0-capable server platforms. Samsung's July 2026 evaluation showed that CXL memory maintained 92% of DRAM performance in 8-GPU configurations while delivering much larger capacity, which is influencing hyperscaler qualification work for AI servers. SK hynix completed customer validation of its 96 GB CMM-DDR5 module in April 2025, delivering a 50% capacity increase and a 30% bandwidth improvement to 36 GB/s over DDR5, while a 128 GB version remained under validation. Controllers are drawing more competition as Montage Technology's CXL 3.1 Memory eXpander Controller gained support from AMD and Intel, while orchestration software remains smaller today but is likely to become a recurring revenue layer as pay-per-use memory pools mature.

Complete Report Scope:

• By Component
  • CXL Memory Modules
  • CXL Controllers
  • CXL Switches
  • Software and Orchestration
• By Deployment Architecture
  • Memory Expansion
  • Memory Pooling
  • Other Deployment Architectures
• By Application
  • Artificial Intelligence and Machine Learning
  • In-Memory Databases and Real-Time Analytics
  • High-Performance Computing and Scientific Computing
  • Cloud Infrastructure and Virtualization
  • Other Applications
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • Taiwan
    • India
    • Rest of Asia-Pacific
  • South America
  • Middle East and Africa

Geography Analysis

North America held a 38.69% share in 2025, making it the largest regional market for CXL memory pooling and disaggregated infrastructure industry. That lead reflected capital spending by AWS, Microsoft Azure, Google Cloud, and Meta, all of which were early backers of the CXL ecosystem and are already moving into production deployment. Astera Labs said its Leo CXL Smart Memory Controllers were validated on Microsoft Azure M-Series virtual machines in 2025, marking a clear step from pilot work toward production-ready public cloud infrastructure. Meta's Vistara project showed that older DDR4 DIMMs from retired servers can be repurposed alongside DDR5 production systems via CXL, reducing memory costs and supporting a lower carbon footprint in hyperscale environments. Demand in the region is also supported by regulated sectors seeking on-premises AI inference capacity for data sovereignty and compliance purposes.

Asia-Pacific is projected to expand at a 34.12% CAGR through 2031, which makes it the fastest-growing geography in the CXL memory pooling and disaggregated infrastructure market. The region benefits from the supply-side concentration of memory manufacturers and ODM capacity in South Korea and Taiwan, while large data center investments are also expanding across China, Japan, South Korea, India, and Australia. Samsung said in July 2026 that it was treating CXL as its next major memory priority, with AMD EPYC Venice-based sample validation planned after September 2026 and commercial production targeted for Q1 2027. SK hynix also demonstrated CMM-DDR5 at CFMS 2026 and is developing its own controllers for CXL 3.0 and 3.1 devices, which supports a stronger regional supply chain position. India's public support for data center growth and Japan's national AI computing efforts suggest that regional demand is building alongside manufacturing strength rather than trailing it.

Europe maintained a meaningful share in 2025, as sovereign AI goals and data residency rules favored on-premises disaggregated memory deployment in enterprise and public sector environments. The EU-backed CAPE project is integrating PCIe Gen 5 and Gen 6 fabric with CXL support for dynamic memory pooling in edge micro data centers, which shows how sovereign compute programs are creating non-hyperscale adoption paths. South America and the Middle East and Africa remain smaller today, but government-backed sovereign AI programs and colocation expansion are creating a future demand path that fits rack-scale and edge-oriented CXL deployment models. This means the CXL memory pooling and disaggregated infrastructure market is likely to develop a broader edge layer outside the hyperscale footprint over the latter part of the forecast period.

1. Marvell Technology, Inc.
2. Astera Labs, Inc.
3. Samsung Electronics Co., Ltd.
4. Micron Technology, Inc.
5. SK Hynix Inc.
6. Liqid Inc.
7. MemVerge Inc.
8. Intel Corporation
9. Advanced Micro Devices, Inc.
10. Montage Technology Co., Ltd.
11. Dell Technologies Inc.
12. Hewlett Packard Enterprise Company
13. Super Micro Computer, Inc.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 AI Cluster Memory Wall Pressure
  • 4.2.2 Hyperscale Shift to Composable Infrastructure
  • 4.2.3 Standardization of CXL 3.x and 4.0 Fabric Features
  • 4.2.4 Energy Efficiency and Rack Utilization Gains from Memory Pooling
  • 4.2.5 Fabric-Level Telemetry and NUMA-Aware Software Orchestration
  • 4.2.6 Procurement Preference for Shared Memory in Sovereign AI and Edge Micro Data Centers
• 4.3 Market Restraints
  • 4.3.1 Interoperability Gaps Across CXL Generations and Vendor Stacks
  • 4.3.2 Limited Volume Availability of Production-Qualified CXL Type 3 and Switch Ecosystems
  • 4.3.3 Software Licensing Friction in Pay-Per-Use Disaggregated Models
  • 4.3.4 Memory Latency Sensitivity in Production AI and HPC Workloads
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Buyers
  • 4.7.2 Bargaining Power of Suppliers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry
• 4.8 Impact of Macroeconomic Factors on the Market

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Component
  • 5.1.1 CXL Memory Modules
  • 5.1.2 CXL Controllers
  • 5.1.3 CXL Switches
  • 5.1.4 Software and Orchestration
• 5.2 By Deployment Architecture
  • 5.2.1 Memory Expansion
  • 5.2.2 Memory Pooling
  • 5.2.3 Other Deployment Architectures
• 5.3 By Application
  • 5.3.1 Artificial Intelligence and Machine Learning
  • 5.3.2 In-Memory Databases and Real-Time Analytics
  • 5.3.3 High-Performance Computing and Scientific Computing
  • 5.3.4 Cloud Infrastructure and Virtualization
  • 5.3.5 Other Applications
• 5.4 By Geography
  • 5.4.1 North America
    • 5.4.1.1 United States
    • 5.4.1.2 Canada
    • 5.4.1.3 Mexico
  • 5.4.2 Europe
    • 5.4.2.1 Germany
    • 5.4.2.2 United Kingdom
    • 5.4.2.3 France
    • 5.4.2.4 Italy
    • 5.4.2.5 Rest of Europe
  • 5.4.3 Asia-Pacific
    • 5.4.3.1 China
    • 5.4.3.2 Japan
    • 5.4.3.3 South Korea
    • 5.4.3.4 Taiwan
    • 5.4.3.5 India
    • 5.4.3.6 Rest of Asia-Pacific
  • 5.4.4 South America
  • 5.4.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 Marvell Technology, Inc.
  • 6.4.2 Astera Labs, Inc.
  • 6.4.3 Samsung Electronics Co., Ltd.
  • 6.4.4 Micron Technology, Inc.
  • 6.4.5 SK Hynix Inc.
  • 6.4.6 Liqid Inc.
  • 6.4.7 MemVerge Inc.
  • 6.4.8 Intel Corporation
  • 6.4.9 Advanced Micro Devices, Inc.
  • 6.4.10 Montage Technology Co., Ltd.
  • 6.4.11 Dell Technologies Inc.
  • 6.4.12 Hewlett Packard Enterprise Company
  • 6.4.13 Super Micro Computer, Inc.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White Space and Unmet Need Assessment