AI servers are high-performance computers specially designed to run artificial intelligence algorithms and process large-scale data. They usually have high processing power, large memory and high-speed storage, multi-core processors, high-speed network interfaces, etc., and can handle complex calculation tasks and large data processing tasks.
AI server drives PCB performance and price to rise
The increase in the value of PCB in AI servers is mainly reflected in the following modules: GPU accelerator card (OAM), which is mainly composed of GPU chips, memory chips, power modules, radiators and other components. It connects and transmits signals through PCB boards. GPU accelerator cards can be divided into two types: SXM version and PCIE version.
The SXM version refers to the accelerator card that uses the SXM interface developed by NVIDIA to connect the GPU chip and the motherboard; the PCIE version refers to the accelerator card that uses the standard PCIE interface to connect the GPU chip and the motherboard. The SXM version has higher bandwidth and lower latency than the PCIE version, but also requires a higher-level PCB board and cooling system. Advanced GPU accelerator cards require the use of 5-level 20-layer or above HDI boards. HDI boards are short for high-density interconnect boards. It is a PCB board that uses laser drilling or micro-machining technology to form tiny holes or line widths on ordinary PCB boards to achieve higher-level, denser wiring and connections.
HDI boards can improve signal integrity, reduce electromagnetic interference, reduce size and weight, and enhance reliability. HDI boards can be divided into different orders and layers. The order indicates how many times there are laser drilling or micromachining on each layer, and the layer number indicates how many layers are stacked together. Generally speaking, the higher the order and the more layers, the higher the density and complexity of the HDI board. Both GPU chips and memory chips have many pins or pads, and HDI boards are required to achieve high-efficiency, low-latency, low-power consumption, and low-noise signal transmission.
GPU accelerator cards need to use high-level, high-density, high-reliability HDI boards to connect various components. There are several main reasons: GPU chips and memory chips have many pins or pads, and HDI boards are needed to achieve high Efficient, low-latency, low-power consumption, and low-noise signal transmission. GPU accelerator cards have high power consumption and generate a large amount of heat. If they cannot be dissipated in time, their stability and lifespan will be affected.
Therefore, it is necessary to use HDI board materials with good thermal conductivity. The size of the GPU accelerator card is small, and an HDI board is required to reduce the area and thickness of the PCB board and improve space utilization and heat dissipation. The performance of the GPU accelerator card is higher, and an HDI board is required to support higher frequencies and bandwidth, and improve data transmission speed and quality.
Level 5 HDI boards with more than 20 layers are currently one of the high-end and expensive products in the PCB industry. Their manufacturing process requirements are very high and require the use of advanced equipment, materials and processes. At present, there are very few manufacturers in the world that can produce this kind of HDI boards, mainly concentrated in Japan, South Korea, Taiwan, China and other places.
GPU accelerator card requirements for CCL
High-frequency and high-speed performance: Since the AI server needs to process a large amount of data and signals, the GPU accelerator card needs to use CCL with high-frequency and high-speed performance, that is, it can maintain low loss, low latency, low crosstalk, low noise, etc. at high frequencies. This requires CCL to have a lower dielectric constant (Dk), dielectric loss (Df), surface roughness (Rz) and other parameters.
Thermal conductivity: Due to the high power consumption of the GPU accelerator card, a large amount of heat will be generated. If it cannot be dissipated in time, its stability and life will be affected. Therefore, GPU accelerator cards need to use CCL with good thermal conductivity, that is, CCL that can effectively conduct heat from the chip to the heat sink or the external environment. This requires CCL to have parameters such as higher thermal conductivity (K) and lower coefficient of thermal expansion (CTE).
Reliability: Since the GPU accelerator card needs to operate stably for a long time in a complex environment, the GPU accelerator card needs to use CCL with high reliability, that is, it can resist the influence of various stresses and environmental factors and maintain its structure and function unchanged. This requires CCL to have parameters such as higher glass transition temperature (Tg), lower moisture absorption rate (MOT), stronger mechanical strength and chemical corrosion resistance.
GPU module board requirements for CCL
Number of layers: Since the GPU module board needs to connect multiple GPU accelerator cards and implement a multi-level power distribution network (PDN), a higher-layer copper-clad board needs to be used. Currently, the copper-clad laminate used in GPU module boards generally has more than 16 layers;
Electrical performance: Since the GPU module board needs to support high-speed data transmission and high-frequency signal processing, it is necessary to use a copper-clad board with a lower dielectric constant (Dk) and dielectric loss factor (Df) to reduce signal attenuation and distortion. To improve signal integrity and reliability, the copper-clad laminate currently used in GPU module boards generally uses high-performance resin materials such as PPO;
Thermal performance: Since the GPU module board needs to withstand high power consumption and heat generation, it is necessary to use a copper-clad board with high thermal conductivity and thermal stability to effectively conduct heat from the components to the heat dissipation module, preventing Overheating causes performance degradation or damage.
CPU motherboard requirements for CCL
Dielectric constant and dielectric loss: These two parameters affect the signal transmission speed and energy loss. For high-frequency, high-speed CPU motherboards, it is necessary to choose a CCL with low dielectric constant and low dielectric loss to ensure the integrity and quality of the signal.
Thermal expansion coefficient: This parameter affects the dimensional stability of CCL when temperature changes. For high-temperature, high-power CPU motherboards, it is necessary to choose CCL with a thermal expansion coefficient similar to that of copper foil to avoid defects such as interlayer separation or via cracking caused by thermal stress.
Thermal conductivity: This parameter affects the performance of CCL in heat dissipation. For high-temperature, high-power CPU motherboards, you need to choose a CCL with higher thermal conductivity to effectively conduct heat from the CPU and other components to the radiator or external environment.
Flame retardant grade: This parameter affects the safety performance of CCL in the event of fire. For all electronic products, it is necessary to choose CCL with a higher flame retardant grade to prevent casualties or property losses caused by fire. Generally speaking, the flame retardant rating should reach UL94 V-0 or above.