Tech Insight | High-Speed Interconnect · Memory Coherency · Heterogeneous Computing

From PCIe to CXL: The Generational Leap in the AI Era

In the era of large-scale AI model training and inference, the traditional PCIe bus is encountering unprecedented performance bottlenecks. Although PCIe 5.0 has pushed per-lane data rates to 32 GT/s, its fundamental architecture—point-to-point with no cache coherency—is increasingly inadequate for efficient collaboration among GPUs, FPGAs, and CPUs.

Enter CXL (Compute Express Link)—a protocol built on the PCIe physical layer but reimagined at the stack level, introducing cache coherency and memory semantics into a standard interconnect for the first time.

1. The Limits of PCIe: Bandwidth Isn’t Everything

While PCIe offers high bandwidth, every data transfer must traverse the OS kernel, driver layers, and memory copies, resulting in microsecond-level latency. In multi-GPU training setups, this “incoherency” leads to redundant data movement, severely degrading system efficiency.

2. Three Pillars of CXL Innovation

This transforms the GPU from a mere “compute unit” into an intelligent co-processor capable of dynamic memory sharing.

3. A Paradigm Shift in AI Infrastructure

Future AI servers will adopt a “CPU + Multi-GPU + CXL Memory Pool” topology. For example:

According to Intel, by 2027, over 60% of data center accelerators will support CXL.

4. YZMU’s Forward-Looking Strategy

As a provider of high-speed interconnect solutions, YZMU (Shenzhen Yunzhou Interconnect Technology) has already initiated R&D on CXL 1.1/2.0–optimized cables:

We believe: The ultimate goal of connectivity is not to move data faster—but to make data movement unnecessary.

Contact YZMU Technical Team

Request our CXL Interconnect Architecture White Paper and custom cable solutions

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