大摩深度透视ASIC产业链：谁是大赢家？

华尔街见闻12-17 09:48

随着生成式AI应用的迅猛发展，AI ASIC能否成为英伟达GPU可⾏的替代品⼀直是全球热议话题。摩根士丹利15日发布研报《AI ASIC 2.0：潜在赢家》，认为ASIC凭借针对性优化和成本优势，有望逐步从英伟达GPU手中争取更多市场份额。大摩预计，AI ASIC市场规模将从2024年的120亿美元增长至2027年的300亿美元，年复合增长率达到34%。在此情况下，英伟达凭借其在大型语言模型训练...

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ASIC能否成为英伟达GPU可⾏的替代品⼀直是全球热议话题。摩根士丹利15日发布研报《AI ASIC 2.0：潜在赢家》，认为ASIC凭借针对性优化和成本优势，有望逐步从英伟达GPU手中争取更多市场份额。大摩预计，AI ASIC市场规模将从2024年的120亿美元增长至2027年的300亿美元，年复合增长率达到34%。在此情况下，英伟达凭借其在大型语言模型训练...</p>\n\n<a href=\"https://wallstreetcn.com/articles/3737040\">网页链接</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","isBrief":false,"type":0,"news_type":1,"symbol":"IE00BD6J9T35.USD","symbol_name":"NEUBERGER BERMAN NEXT GENERATION MOBILITY \"A\" (USD) 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ASIC市场规模将从2024年的120亿美元增长至2027年的300亿美元，年复合增长率达到34%。在此情况下，英伟达凭借其在大型语言模型训练方面的优势，将继续占据主导地位。博通、世芯电子（Alchip）和Socionext被看好。Cadence、台积电及其供应链伙伴（ASE、KYEC等）将从ASIC设计与制造的快速增长中获益。大摩表示，ASIC的崛起并不意味着GPU的衰退。相反，这两种技术将长期共存，为不同需求场景提供最佳解决方案。ASIC会成为英伟达的有力竞争者吗？随着生成式AI应用的迅猛发展，全球AI计算需求呈现爆炸式增长。报告预计，基本情境下，到2027年，云端AI半导体市场规模将达到2380亿美元，而在乐观情境下甚至可能达到4050亿美元。在这一领域，ASIC凭借针对性优化和成本优势，有望逐步从英伟达 GPU手中争取更多市场份额。摩根士丹利预计，AI ASIC市场规模将从2024年的120亿美元增长至2027年的300亿美元，年复合增长率达到34%。尽管英伟达的AI GPU性能卓越，但摩根士丹利认为，云服务提供商如谷歌、亚马逊和微软，仍在积极推动ASIC设计。这背后的驱动力主要有两个。首先，是优化内部工作负载。通过开发自定义芯片，CSP可以更高效地满足其内部AI推理和训练需求。其次，是更好的性价比。报告指出，虽然英伟达的GPU具备强大的计算性能，但其硬件价格高昂，特别是在AI训练过程中。相比之下，ASIC的单位成本更低，尤其是在大规模使用后。例如，亚马逊的Trainium芯片在推理任务中比英伟达的H100 GPU便宜约30%至40%。谷歌也在不断优化其TPU系列，最新的TPU v6在能效上比上一代提升67%。摩根士丹利强调，尽管英伟达的GPU仍是大多数CSP的首选，但未来几年内，随着ASIC设计的日益成熟，这些云巨头可能通过自研ASIC在采购谈判中获得更大话语权。赢家与输家：谁将主导未来市场？摩根士丹利在报告中梳理了全球ASIC供应链，并明确了六大可能的赢家：AI GPU：英伟达将继续主导市场，尤其是在大规模语言模型训练方面，其解决方案仍是最优选择。ASIC供应商：博通、Alchip（世芯电子）和Socionext被视为ASIC市场的潜力股。其中，Alchip由于与AWS的深度合作，预计将在2026年显著提升市场份额。电子设计自动化工具：Cadence（楷登电子）有望实现结构性增长。代工厂：台积电及其供应链伙伴（如ASE、KYEC等）将从ASIC设计与制造的快速增长中受益。测试服务：Advantest是AI芯片测试领域的领先者，其在AI设备测试方面的专注将为其带来显著增长。HBM：三星电子是非英伟达HBM市场份额领先者，将从ASIC需求增长中获益。相比之下，一些传统芯片公司和代工厂可能面临挑战。例如，AMD由于在AI GPU领域未能与英伟达拉近差距，或将失去更多市场份额。而UMC等缺乏先进工艺节点支持的代工厂也可能难以在高端AI芯片市场中分得一杯羹。TCO分析：ASIC真的划算吗？摩根士丹利通过TCO模型对比了ASIC和GPU在AI训练和推理任务中的成本效益。结果显示，尽管英伟达的GPU在性能上占据明显优势，但ASIC的初始成本较低，尤其适合预算有限的云服务提供商。例如，在同等预算下，AWS的Trainium 2可以比英伟达的H100 GPU更快速完成推理任务，且性价比提高了30-40%。Trainium3计划于2025年下半年推出，计算性能提高2 倍，能效提高40%。不过，报告也指出，英伟达凭借其更成熟的系统集成能力和更强大的软件生态，仍在TCO计算中保持竞争力，特别是在需要灵活应对不同AI任务的场景中。研报中提到，量子计算的潜在崛起可能会对AI半导体需求产生冲击，但目前来看，量子计算在AI推理领域的适用性较低，短期内难以取代ASIC和GPU。此外，退役GPU也可能成为ASIC市场的威胁。一些云服务商可能选择通过使用退役GPU降低成本，而不是投资昂贵的ASIC。摩根士丹利总结道，ASIC的崛起并不意味着GPU的衰退。相反，这两种技术将长期共存，为不同需求场景提供最佳解决方案。在未来的AI市场中，ASIC将凭借成本和能效优势争取更多份额，而英伟达则将继续依靠其技术领先性巩固市场地位。风险提示及免责条款 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