Remote Direct Memory Access Over Converged Ethernet (RoCE) Market for AI Workloads Expected to Reach $6.89 Bn by 2030

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TBRC's RoCE For Artificial Intelligence (AI) Workloads Market Report 2026 – Market Size, Trends, And Global Forecast 2026-2035

LONDON, GREATER LONDON, UNITED KINGDOM, February 26, 2026 /EINPresswire.com/ -- "The world of artificial intelligence (AI) is driving rapid advancements in networking technologies, especially those that enhance data transfer speeds and efficiency. One such technology gaining attention is Remote Direct Memory Access over Converged Ethernet (RoCE), which plays a pivotal role in accelerating AI workloads. Let's explore the current market size, growth factors, regional leadership, and key trends shaping the RoCE market for AI applications.

Market Expansion Outlook for RoCE in AI Workloads
The market for Remote Direct Memory Access over Converged Ethernet (RoCE) tailored to AI workloads has witnessed remarkable growth recently. It is projected to increase from $2.63 billion in 2025 to $3.19 billion in 2026, reflecting a strong compound annual growth rate (CAGR) of 21.0%. This surge during the historical period can be linked to the rapid expansion of data centers, rising demands for big data processing, widespread adoption of high-performance computing clusters, early-stage implementation of Ethernet-based networking, and the growth of enterprise cloud infrastructures.

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Future Growth Trajectory for RoCE in AI Applications
Looking ahead, the RoCE market for AI workloads is expected to experience exponential expansion, reaching an estimated size of $6.89 billion by 2030 with an anticipated CAGR of 21.3%. This forecasted growth stems from increasing AI model complexity, the proliferation of hyperscale AI data centers, heightened demand for distributed training frameworks, ongoing investments in GPU and accelerator technologies, and rising needs for real-time analytics and inference processing. Key upcoming trends include broader deployment of high-bandwidth Ethernet interconnects, wider adoption of low-latency distributed AI training architectures, advancements in GPU cluster networking optimization, integration of traffic management and congestion control software, and improvements in scalable data center networking infrastructure.

Understanding RoCE Technology in AI Workloads
Remote Direct Memory Access over Converged Ethernet (RoCE) enables high-speed, low-latency data transfers directly between memory components across servers and storage systems within AI computing environments. Its main function is to speed up AI training and inference by reducing CPU load, decreasing data transfer delays, and optimizing bandwidth for handling large datasets efficiently.

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Primary Factors Fueling RoCE Market Growth
One of the main drivers for the RoCE market in AI workloads is the increasing adoption of Ethernet-based alternatives to InfiniBand. Technologies like RDMA over Converged Ethernet allow remote direct memory access over standard Ethernet networks, which are widely deployed in AI data centers. This shift is largely propelled by hyperscale cloud providers and other major players seeking scalable, cost-effective networking solutions compatible with existing Ethernet infrastructure. RoCE facilitates low-latency, high-throughput GPU-to-GPU communication and supports efficient distributed training across Ethernet fabrics. For example, in June 2025, Vitex LLC, a US-based fiber optic solutions provider, reported that major hyperscale cloud companies are making unprecedented capital investments in AI infrastructure. Microsoft allocated around $80 billion, Amazon committed $86 billion as part of a broader $100 billion plan, Google invested $75 billion, and Meta spent $65 billion in 2025, combining to over $450 billion in total investment. These massive investments underscore the growing reliance on Ethernet-based alternatives like RoCE, accelerating market growth.

Regional Market Leadership and Growth Prospects for RoCE
In 2025, North America held the largest share of the RoCE market for AI workloads. Moving forward, the Asia-Pacific region is set to emerge as the fastest-growing market during the forecast period. The analysis covers key regions including Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa, providing a comprehensive view of the market’s global landscape.

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