Currently, China is comprehensively promoting breakthroughs in the systematization of AI computing power and accelerating the construction of an independent and controllable computing power base. Domestic computing chips generally have ultra-high integration, high power consumption, and multi-layer advanced packaging features. The operation of computing power is long faced with dual constraints of power consumption wall and bandwidth wall, which continuously subject GPU, HBM, and CPO optical modules to severe alternating cold and hot stress. Temperature Forcing Systems provides a real temperature environment and has become a core precision equipment for the research and mass production verification of domestic computing chips, optical interconnect devices, and computing server modules. It is an indispensable underlying testing tool for connecting the independent controllable computing power industry chain and ensuring the long-term stable operation of computing power networks.
Temperature Forcing Systems is different from traditional full box cold and hot shock testing equipment. It adopts directional clean cold and hot air flow fixed-point spraying technology and relies on stacked mechanical refrigeration and high-speed heating modules to achieve ultra wide temperature range coverage of -80 ℃~225 ℃. The switching of high and low temperature air flow takes 10-15 seconds, accurately simulating the real extreme temperature change conditions of computing hardware.

The four core advantages of Temperature Forcing Systems in adapting to the AI computing power industry chain
1. Local fixed-point impact, supporting on-board in-situ live testing, only applying cold and hot airflow to the tested GPU, NPU, HBM, CPO optical modules, PCB peripheral components are not affected by temperature interference, and full load live impact testing can be completed without disassembling the chip. Real time monitoring of computing power, power consumption, bandwidth, signal transmission parameters, accurately capturing instantaneous failures such as computing power attenuation, impedance drift, and transmission errors under sudden temperature changes, perfectly adapting to high-density heterogeneous computing power motherboard testing scenarios.
2. Rapid temperature cycling, efficient exposure of latent defects caused by thermal fatigue can be customized according to computing chip standards and server environment specifications, with a high and low temperature cycling program of 500-1000 times. The temperature difference stress of packaging, solder joints, and HBM stacking layers can be amplified, and process defects can be quickly screened to solve the problem of early failure of domestically advanced packaging chips and significantly shorten the research and development verification cycle of domestically produced AI chips.
3. Wide temperature range and high-precision temperature control, covering all computing power application scenarios with temperature control accuracy of ± 1 ℃ and display accuracy of ± 0.1 ℃. The high-temperature section replicates the full load high-temperature working condition at 125 ℃, and the low-temperature section matches edge computing power, outdoor base stations, and low-temperature hub environments at -40 ℃. It completes one-stop data center level, industrial level, and edge level computing power hardware reliability verification.
4. Miniaturization and low energy consumption, suitable for dual scenarios of laboratory and mass production lines. Compact models do not require liquid nitrogen assisted cooling, are quiet and low-power, and are suitable for chip design enterprise R&D laboratories; Supporting automated fixture linkage, it can connect with domestic chip pilot testing and large-scale production screening processes, helping to achieve the industrial goal of replacing imported computing chips on a large scale.
In the stage of tackling domestic AI chips, Temperature Forcing Systems runs through the entire process of chip fabrication, packaging, and performance optimization:
In the development of general-purpose GPU and AI specific ASIC chips, the long-term high-power start stop temperature difference of the chip is simulated through thermal shock to verify the accuracy of operator operations and the stability of compiler adaptation under extreme temperatures. High temperature power consumption anomalies and low-temperature startup lag problems are investigated to overcome the thermal failure hazards caused by the computing power "power wall" and support chip performance.
2. Reliability verification of HBM high bandwidth memory stacking: The HBM multi-layer stacking structure is extremely sensitive to temperature stress. Cold and hot cycling impacts can expose stacking interface delamination and micro bump cracking defects, ensuring stable output of computing chip bandwidth, breaking the bottleneck of computing power "bandwidth wall", and supporting hardware implementation of high-throughput large model training.
3. Optimization of chip software ecosystem, synchronized collection of chip operation logs at different temperatures throughout impact testing, identification of development framework and operator library adaptation bugs in low and high temperature environments, differentiation of root causes of faults, and completion of collaborative optimization of chip software and hardware ecosystem.
Temperature Forcing Systems makes up for the shortcomings of traditional temperature box testing by leveraging its unique advantages of fixed-point rapid temperature changes and synchronous testing with live load. On the one hand, by accelerating the exposure of physical failure hazards of computing core devices such as GPU/TPU and optical modules through strong thermal stress, pre screening for mass production can be achieved; On the other hand, relying on the ability to synchronously collect real-time logs, it can accurately distinguish software and hardware failures, locate deep learning frameworks and operator libraries compatible bugs in extreme temperature ranges, assist in iterative optimization of chip software ecology, and cover the verification needs of the entire computing power industry chain. It is an indispensable specialized testing equipment to ensure the long-term stable operation of AI servers and large-scale computing power clusters.

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