OAM switch module PCB fabrication

OAM switch module PCB fabrication for AI and HPC systems

OAM switch module board PCB fabrication is a core technology in the fields of high-performance computing (HPC) and artificial intelligence (AI) servers. OAM is an open standard AI accelerator card package promoted by the Open Compute Project (OCP), and is widely used in large-scale data centers for AI training, inference, and other scenarios.

Description

OAM Switch Module Board PCB Fabrication

OAM switch module board PCB fabrication provides these systems with a foundation for high-bandwidth, low-latency data interconnection, making it a vital component for implementing modern AI infrastructure.

Key Features of OAM Switch Module Board PCB Fabrication

  • High-speed interconnection and data exchange: Integrates high-speed switch chips such as PCIe Switch and NVSwitch, enabling high-speed interconnection between multiple OAM accelerator cards and between the cards and the host CPU.
  • Modularity and scalability: Supports parallel deployment of various OAM accelerator cards, making it easier to scale system computing power as needed.
  • Multi-protocol compatibility: Compatible with multiple high-speed interconnect protocols such as PCIe, NVLink, and CXL, meeting the requirements of different AI acceleration scenarios.
  • Unified management and power supply: Provides unified power distribution, monitoring, and management interfaces for OAM accelerator cards, ensuring long-term stable operation of the system.
  • High-precision manufacturing process: PCB designs typically have around 18 layers, with drilling diameter of 0.2mm, using advanced techniques such as back drilling, resin plugging, and POFV. There are stringent coplanarity requirements at BGA positions to ensure the quality of chip package soldering.
  • Application of high-performance materials: Uses Very Low Loss grade and above high-speed materials, high-speed ink, and Low Profile brown oxide processes. Some products use inner copper foil thickness of 3OZ or more to ensure signal integrity and high current-carrying capacity.

Main Applications

  • Large AI servers (such as NVIDIA HGX platforms), AI accelerator chassis, supercomputing centers, and other high-density AI cluster systems.
  • AI large model training, inference, scientific computing, and cloud computing platforms.
  • Various high-performance AI application scenarios such as image recognition, natural language processing, and machine learning.