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The evolution of data center infrastructure is being driven by the insatiable demand for AI, machine learning, and high-performance computing (HPC). At the forefront of this transformation is Montage Technology, whose CXL 3.1 Memory eXpander Controller (MXC) is redefining how memory is pooled, shared, and optimized. By addressing critical bottlenecks in memory scalability and total cost of ownership (TCO), Montage’s MXC is positioning itself as a cornerstone of next-generation data center architectures.
Montage’s M88MX6852 MXC, compliant with CXL 3.1 Type 3 specifications, enables dynamic memory expansion and pooling across heterogeneous systems. Built on a PCIe 6.2 physical layer, the controller delivers data transfer rates of up to 64 GT/s (x8) and integrates a dual-channel DDR5 memory controller operating at 8000 MT/s. This architecture minimizes latency—contributing just 70ns of delay—while supporting multi-rate and multi-width configurations, including splitting into two x4 ports for flexible deployment [1].
The MXC’s dual RISC-V microprocessors further enhance its value by enabling real-time resource management and hardware-level security, critical for hyperscalers and edge computing platforms. By decoupling memory from CPUs, the MXC allows data centers to pool resources across servers, eliminating stranded memory and reducing overprovisioning. This capability is particularly vital for AI workloads, where memory-intensive training models require rapid access to large datasets [1].
Montage’s MXC directly addresses TCO challenges through scalable memory expansion and energy efficiency. A real-world demonstration compared a traditional 1TB DRAM-only server to a hybrid system using 512GB DDR5 DRAM and 512GB CXL memory. The hybrid setup achieved 95–100% of the throughput of the DRAM-only system while adding only 5–10µs of application-level latency. This performance parity with significantly reduced memory costs underscores the MXC’s cost-efficiency [2].
Moreover, CXL 3.1’s integration with memory compression technologies can halve media costs by improving utilization. For instance, a 2:1 compression ratio reduces the effective memory footprint, allowing data centers to serve more workloads with existing infrastructure. This synergy between CXL and compression is projected to cut TCO by up to 50% in scenarios where cold data storage is a priority [3].
Montage’s leadership is further validated by its partnerships with industry giants like Samsung, SK hynix, and
. These collaborations have led to the deployment of MXC-based E3.S form factor CXL memory modules, which are now sampling with key customers. The MXC’s adoption by the top three global memory manufacturers signals strong industry confidence in its ability to meet the demands of AI-driven workloads [1].The CXL market itself is poised for explosive growth, projected to expand from $14 million in 2023 to $16 billion by 2028. This trajectory is fueled by the need for scalable, low-latency memory solutions in AI and HPC environments. Montage’s MXC, with its support for CXL 1.0–3.1 and PCIe 6.x/CXL 3.x Retimer development, is well-positioned to capture a significant share of this market [4].
Montage Technology’s CXL 3.1 MXC is not just a technical innovation—it is a strategic enabler for data centers navigating the AI era. By optimizing TCO through memory pooling, reducing stranded resources, and partnering with industry leaders, Montage is addressing the core challenges of modern infrastructure. As CXL adoption accelerates, the MXC’s role in driving efficiency and scalability will become increasingly critical, making Montage a compelling investment for those seeking to capitalize on the next wave of data center evolution.
Source:
[1] Montage Technology Introduces CXL 3.1 Memory eXpander Controller for Next-Gen Data Center Infrastructure [https://www.techpowerup.com/340528/montage-technology-introduces-cxl-3-1-memory-expander-controller-for-next-gen-data-center-infrastructure]
[2] FMS 2025 CXL Demos [https://computeexpresslink.org/fms-2025-cxl-demos/]
[3] Optimizing Data Center TCO With CXL And Compression [https://semiengineering.com/optimizing-data-center-tco-with-cxl-and-compression/]
[4] Samsung, SK hynix, Micron race to lead CXL memory market [https://www.chosun.com/english/industry-en/2025/05/12/5JEF3PSPYBCGVAKOJOR7RCECXU/]
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