Source URL: https://www.tomshardware.com/tech-industry/artificial-intelligence/deepseek-research-suggests-huaweis-ascend-910c-delivers-60-percent-nvidia-h100-inference-performance
Source: Hacker News
Title: Huawei’s Ascend 910C delivers 60% of Nvidia H100 inference performance
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Summary: The text discusses Huawei’s HiSilicon Ascend 910C processor, highlighting its potential in AI inference despite performance limitations in training compared to Nvidia’s offerings. It touches on the implications of U.S. sanctions, ongoing improvements in China’s AI hardware, and potential shifts in the dependency on Nvidia’s ecosystem.
Detailed Description: The provided text outlines several key points related to AI hardware and the competitive landscape in the AI processor market:
– **Huawei’s Ascend 910C**: This processor, a variant of the Ascend 910 released in 2019, is designed for AI applications, particularly training large models. However, its performance is becoming less competitive relative to other leading processors, particularly those from Nvidia.
– **Inference Performance**: The Ascend 910C matches approximately 60% of the performance of Nvidia’s H100 during inference tasks, positioning it as a viable option albeit not the most powerful.
– **Dependency on Nvidia**: Despite advancements, the text emphasizes that Nvidia still leads the market, especially in AI training due to its mature hardware-software ecosystem developed over the last two decades. This raises concerns about the long-term reliability of training on Huawei’s hardware.
– **Technical Advancements**: The Ascend 910C features an advanced chiplet packaging design with around 53 billion transistors. Its production involves an alternative chip fabrication process by SMIC, diverging from Nvidia’s manufacturing resources.
– **Future Considerations**: Predictions suggest a potential shift in dependency from Nvidia as AI models evolve. The importance of software ecosystems may diminish if alternative hardware becomes optimized for AI usage, particularly through companies like DeepSeek that offer native support for using Huawei’s processors.
– **Challenges Ahead**: To compete globally, China must enhance its AI training reliability and continue to improve its hardware and software offerings. The ongoing geopolitical context, including U.S. sanctions, adds complexity to the acquisition of leading technologies.
Overall, this analysis highlights not just the technical evolution of AI processors but also the strategic implications for companies involved in AI development, especially in light of compliance with global regulations and the shifting dynamics of technology ownership and innovation.