"2025第二届高算力芯片开发者论坛暨芯片热管理技术交流会" 将于 5月22-23日 在 北 京 举办。本次论坛由 车乾信息&热设计网 主办，论坛重点探讨：国产AI芯片进程、AI芯 片安全、芯片封装Chiplet技术、先进封装材料与封装基板、AI 芯片热力设计、芯片直冷 技术、3DVC均温技术等。届时将安排 20+ 演讲，预计将超过 300+ 行业专家参会！ 1.参会学习，包含服务：参会学习+会后资料+会议专属社群，费用：2500元/人 芯片热管理难题,车乾信息&热设计网继首届成功举办后,再度携手举办 "2025第二届高算力芯片开发者论坛暨芯片热管理技术交流会"。本次论坛 将于5月22-23日在北京举办,汇聚AI芯片领域的开发者、研究人员、企业 代表和专家学者,共同探讨前沿动态、创新应用和未来发展趋势。 会议概览 第一天上午 Al 芯片关键技术及发展趋势 第一天下午 AI芯片封装技术 AI芯片高效散热技术 第二天上午 企业参观 演讲信息 | 确认及确认中演讲单位 | 演讲话题 | | --- | --- | | 清华大学 | 电子系统的跨尺度热管理 | | 中兴通讯有限公司 | 浅谈高功率芯片散热 | | 芯 ...

在供应链和厂商层面，像华硕、微星、技嘉等面向全球市场的厂商，更能从当前的高价环境中受益。而 像七彩虹这样主要深耕中国大陆市场、目前只能生产和销售5090D的厂商，其获利空间相对受到限制。 国内大型科技公司如阿里巴巴和腾讯，获取算力的途径主要有两种：一是通过正规渠道直接向英伟达采 购，二是也在外部市场收购消费级显卡（如90系列），但主流需求仍依赖正规途径。 关于英伟达的市场策略，5090芯片在所有显卡芯片中的占比和投放数量都相对有限。这部分是由于全球 范围内的年供应量有限，与市场需求之间存在显著差距。另一方面，英伟达也有意控制5090芯片的投 放，因为它不希望该型号被大规模用于数据中心，从而影响其利润率更高的专业AI计算卡（如A100、 H100等）的销售策略和市场份额。由于5090芯片的毛利率相对较低，英伟达会将其供应控制在一定范 围内，以维持整体产品线的利润结构。 总的来看，RTX 5090系列正处于高需求、高价格、供应受限的状态，并且在中国市场面临特殊的监管 挑战和产品调整。 最近一直在推RTX 5090的卡，我们这边找到了一些价格很有优势的渠道。也为此专门做了一些针对 5090的市场调研，跟大家分享一下 ...

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Industry Trends Overview - The synergy between AI and cloud computing has created a tight feedback loop driven by technological iteration, application expansion, and computing power demand [3] - The rapid enhancement of AI large model capabilities is pushing AI from being an auxiliary tool to a core productivity driver, heavily relying on cloud service providers for continuous upgrades in computing power, storage, and operations [3] - For instance, Alibaba Cloud's ninth-generation ECS instance has seen a 20% increase in computing power while prices have decreased by 5%, lowering the AI development threshold for enterprises [3] Cloud Service Providers' Technological Upgrades and Competitive Landscape - Cloud service providers are engaged in intense competition centered around AI computing power demands, with leading firms building competitive advantages through differentiated technological paths [5] - Alibaba Cloud focuses on end-to-end optimization, achieving a 20% improvement in AI preprocessing efficiency and a 92% reduction in response time for its PAI platform [5][6] - Huawei Cloud emphasizes architectural innovation, with its CloudMatrix 384 super node achieving three times the GPU density of traditional servers, addressing enterprise needs for customized AI solutions [6] AI Model Progress and Multimodal Breakthroughs - The current phase of AI model iteration is driven by "multimodal + deep thinking," with significant breakthroughs transitioning from laboratories to commercial applications [7] - Upcoming releases like Qwen3 and Llama4 are expected to enhance logical reasoning and voice interaction capabilities, while Alibaba's Qwen2.5-Omni demonstrates end-to-end processing across four modalities [7][8] - The competition among AI models is intensifying, with Google’s Gemini 2.5 Pro showcasing its potential in complex reasoning tasks, while GPT-4o aims to improve image generation precision for enterprise needs [7] Computing Power Demand Surge and Price Transmission in the Industry Chain - The explosive growth of AI technology is leading to a significant surge in computing power demand, creating a structural shortage on the supply side [9] - For example, the price of H100 calls has jumped 22% within two weeks, reflecting the scarcity of computing resources [11] - In North America, IDC rents have increased by over 60% due to high demand and limited supply, while in China, the upgrade of AI-specific data centers has raised unit cabinet costs [15][16] Rise of Computing Power Leasing Models - The emergence of computing power leasing models is becoming a new variable to balance supply and demand contradictions, with companies like CoreWeave reducing marginal costs [17] - However, the sustainability of this business model depends on the downstream application side's ability to pay, as some startups face losses due to high inference costs [17] - Overall, the price transmission in the computing power industry chain is shifting from short-term spikes to long-term structural inflation, reinforcing the barriers for leading firms while posing risks for smaller players [17]