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闲云没有野鹤
11-13
真搞笑
亮剑英伟达，寒武纪引领中国AI软件新生态
闲云没有野鹤
10-29
所以当时我几乎是all in 英伟达，可惜资金太少了
去老虎APP查看更多动态
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href=http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20251113201241976717cf&s=b><strong>21世纪经济报道</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>21世纪经济报道记者 雷晨“得生态者得天下”，在AI芯片领域，这已成为不容置疑的竞争法则。多年来，英伟达凭借其CUDA软件生态系统，构筑了几乎垄断的市场地位。今年5月17日，清华大学计算机系教授、中国工程院院士郑纬民在一场公开论坛上表示，当前大模型训练主要依赖两类系统：一是英伟达GPU，其硬件性能与生态成熟度领先，但面临禁售、价格高涨和一卡难求的困境；二是国产芯片，全国已有3万余家企业投入研发，...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20251113201241976717cf&s=b\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"LU0265550359.USD":"BGF SYSTEMATIC GLOBAL ENHANCED EQUITY YIELD \"A2\" (USD) ACC","LU1989764664.SGD":"CPR Invest - Global Disruptive Opportunities A2 Acc SGD-H","LU1815336760.USD":"THREADNEEDLE (LUX) GLOBAL TECHNOLOGY \"AUP\" (USD) INC","LU1934455277.USD":"AB SICAV I LOW VOLATILITY TOTAL RETURN EQUITY PORT \"AD\" (USD) INC","LU2023250504.SGD":"Allianz Thematica Cl AMg DIS 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NeuWare已经日趋成熟，全面兼容社区最新PyTorch版本和Triton算子开发语言，支持用户模型和自定义算子快速迁移。在业内人士看来，寒武纪正在构建一个能够与行业巨头英伟达CUDA生态相抗衡的软硬件一体化体系。然而，但要真正与英伟达CUDA生态竞争，仍面临诸多挑战。“CUDA的巨大生态优势在于其深厚的开发者社区积累。多年来，CUDA已成为AI领域事实上的标准，大量算法和研究都基于CUDA实现。”有业内人士指出，这形成了强大的网络效应和迁移成本，使得即使有其他选择，开发者也难以脱离CUDA生态。寒武纪显然意识到了这一点，并采取了全面兼容主流开源框架的策略。Cambricon NeuWare全面兼容主流开源框架，不仅跟进PyTorch社区的进展，支持PyTorch 2.1到PyTorch 2.8的全部社区版本，还建立了快速跟进社区版本的长效机制，可在社区版本发布后两周内实现MLU适配版本的发布。在开发工具层面，Cambricon NeuWare提供了完整的软件栈：CNPerf-GUI适配多平台，支持超大日志文件的快速加载及流畅操作；新增程序正确性分析工具CNSantizer，可自动完成多核间竞争访问检测。BANG C语言则是寒武纪BANG异构并行编程模型的编程语言，在C/C++语言基础上针对MLU架构特点进行扩展，可以高效编写在MLU上运行的并行程序，充分利用MLU大规模并行架构来加速计算任务。寒武纪还提供GPU Migration一键迁移工具，帮助用户近乎零成本将模型从GPU迁移到MLU。这种降低迁移成本的策略对于生态建设至关重要。“芯模”加速协同，软件生态破壁值得注意的是，任何技术平台的成功，不仅在于技术先进，更在于能否经得起大规模实践的检验。据21世纪经济报道记者了解，寒武纪在大模型与“搜广推”的训练推理上，已完成大规模的技术和产品验证，验证结果表明：解决方案可支撑多场景下的流式训练任务，可持续超数月稳定运行，精度与稳定性均满足要求。在大模型训练方向，寒武纪重点支持众多主流模型，包括DeepSeek V3/V3.1、Qwen2.5/Qwen3/Qwen3-next等MoE类模型训练，同时扩展了GLM4.5、Flux、Wan2.1/2.2等模型的训练支持。基于原生FP8的计算能力，寒武纪新增了Qwen/DeepSeek等系列网络FP8的训练支持，精度符合预期。在大模型推理方向，寒武纪研究并实践W4A4以及MX-FP8/MX-FP4等新型数据类型，探索并支持多种高效注意力机制，包括Sparse Attention与Linear Attention。通过深度的生态合作，针对DeepSeek V3.2-Exp模型，寒武纪实现发布即适配的支持，并与合作伙伴同步开源适配代码。而在自研NeuWare的同时，寒武纪也积极参与共建统一开放生态，破解AI领域长期存在的“芯片架构碎片化”难题。11月12日，寒武纪宣布拥抱众智FlagOS生态，这是构建国产AI软件生态的重要一步。FlagOS由北京智源人工智能研究院牵头研发，是面向多种AI芯片的开源系统软件栈，支持超20种国内外主流AI芯片型号。寒武纪和智源研究院从2024年初起就开始进行FlagGems的联合开发工作，后续进一步拓展到FlagTree（统一多后端的增强版Triton编译器）、FlagCX（统一通信库）、FlagScale（并行训推一体框架）等组件。FlagOS 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20:09","market":"us","language":"zh","title":"亮剑英伟达，寒武纪引领中国AI软件新生态","url":"https://stock-news.laohu8.com/highlight/detail?id=2583003562","media":"21世纪经济报道","summary":"多年来，英伟达凭借其CUDA软件生态系统，构筑了几乎垄断的市场地位。亮剑英伟达，打造国产“CUDA”近期，寒武纪公开表示，经过多年投入与积累，其基础软件平台Cambricon NeuWare已经日趋成熟，全面兼容社区最新PyTorch版本和Triton算子开发语言，支持用户模型和自定义算子快速迁移。11月12日，寒武纪宣布拥抱众智FlagOS生态，这是构建国产AI软件生态的重要一步。双重推力加持，中国AI的自主未来在受访业内人士看来，国产AI软件生态的崛起，恰逢天时地利。","content":"<div>\n<p>21世纪经济报道记者 雷晨“得生态者得天下”，在AI芯片领域，这已成为不容置疑的竞争法则。多年来，英伟达凭借其CUDA软件生态系统，构筑了几乎垄断的市场地位。今年5月17日，清华大学计算机系教授、中国工程院院士郑纬民在一场公开论坛上表示，当前大模型训练主要依赖两类系统：一是英伟达GPU，其硬件性能与生态成熟度领先，但面临禁售、价格高涨和一卡难求的困境；二是国产芯片，全国已有3万余家企业投入研发，...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20251113201241976717cf&s=b\">Web Link</a>\n\n</div>\n","source":"tencent","collect":0,"html":"<!DOCTYPE html>\n<html>\n<head>\n<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n<meta name=\"viewport\" 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href=http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20251113201241976717cf&s=b><strong>21世纪经济报道</strong></a>\n\n\n</h4>\n\n</header>\n<article>\n<div>\n<p>21世纪经济报道记者 雷晨“得生态者得天下”，在AI芯片领域，这已成为不容置疑的竞争法则。多年来，英伟达凭借其CUDA软件生态系统，构筑了几乎垄断的市场地位。今年5月17日，清华大学计算机系教授、中国工程院院士郑纬民在一场公开论坛上表示，当前大模型训练主要依赖两类系统：一是英伟达GPU，其硬件性能与生态成熟度领先，但面临禁售、价格高涨和一卡难求的困境；二是国产芯片，全国已有3万余家企业投入研发，...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20251113201241976717cf&s=b\">Web Link</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","type":0,"thumbnail":"","relate_stocks":{"LU0265550359.USD":"BGF SYSTEMATIC GLOBAL ENHANCED EQUITY YIELD \"A2\" (USD) ACC","LU1989764664.SGD":"CPR Invest - Global Disruptive Opportunities A2 Acc SGD-H","LU1815336760.USD":"THREADNEEDLE (LUX) GLOBAL TECHNOLOGY \"AUP\" (USD) INC","LU1934455277.USD":"AB SICAV I LOW VOLATILITY TOTAL RETURN EQUITY PORT \"AD\" (USD) INC","LU2023250504.SGD":"Allianz Thematica Cl AMg DIS 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NeuWare已经日趋成熟，全面兼容社区最新PyTorch版本和Triton算子开发语言，支持用户模型和自定义算子快速迁移。在业内人士看来，寒武纪正在构建一个能够与行业巨头英伟达CUDA生态相抗衡的软硬件一体化体系。然而，但要真正与英伟达CUDA生态竞争，仍面临诸多挑战。“CUDA的巨大生态优势在于其深厚的开发者社区积累。多年来，CUDA已成为AI领域事实上的标准，大量算法和研究都基于CUDA实现。”有业内人士指出，这形成了强大的网络效应和迁移成本，使得即使有其他选择，开发者也难以脱离CUDA生态。寒武纪显然意识到了这一点，并采取了全面兼容主流开源框架的策略。Cambricon NeuWare全面兼容主流开源框架，不仅跟进PyTorch社区的进展，支持PyTorch 2.1到PyTorch 2.8的全部社区版本，还建立了快速跟进社区版本的长效机制，可在社区版本发布后两周内实现MLU适配版本的发布。在开发工具层面，Cambricon NeuWare提供了完整的软件栈：CNPerf-GUI适配多平台，支持超大日志文件的快速加载及流畅操作；新增程序正确性分析工具CNSantizer，可自动完成多核间竞争访问检测。BANG C语言则是寒武纪BANG异构并行编程模型的编程语言，在C/C++语言基础上针对MLU架构特点进行扩展，可以高效编写在MLU上运行的并行程序，充分利用MLU大规模并行架构来加速计算任务。寒武纪还提供GPU Migration一键迁移工具，帮助用户近乎零成本将模型从GPU迁移到MLU。这种降低迁移成本的策略对于生态建设至关重要。“芯模”加速协同，软件生态破壁值得注意的是，任何技术平台的成功，不仅在于技术先进，更在于能否经得起大规模实践的检验。据21世纪经济报道记者了解，寒武纪在大模型与“搜广推”的训练推理上，已完成大规模的技术和产品验证，验证结果表明：解决方案可支撑多场景下的流式训练任务，可持续超数月稳定运行，精度与稳定性均满足要求。在大模型训练方向，寒武纪重点支持众多主流模型，包括DeepSeek V3/V3.1、Qwen2.5/Qwen3/Qwen3-next等MoE类模型训练，同时扩展了GLM4.5、Flux、Wan2.1/2.2等模型的训练支持。基于原生FP8的计算能力，寒武纪新增了Qwen/DeepSeek等系列网络FP8的训练支持，精度符合预期。在大模型推理方向，寒武纪研究并实践W4A4以及MX-FP8/MX-FP4等新型数据类型，探索并支持多种高效注意力机制，包括Sparse Attention与Linear Attention。通过深度的生态合作，针对DeepSeek V3.2-Exp模型，寒武纪实现发布即适配的支持，并与合作伙伴同步开源适配代码。而在自研NeuWare的同时，寒武纪也积极参与共建统一开放生态，破解AI领域长期存在的“芯片架构碎片化”难题。11月12日，寒武纪宣布拥抱众智FlagOS生态，这是构建国产AI软件生态的重要一步。FlagOS由北京智源人工智能研究院牵头研发，是面向多种AI芯片的开源系统软件栈，支持超20种国内外主流AI芯片型号。寒武纪和智源研究院从2024年初起就开始进行FlagGems的联合开发工作，后续进一步拓展到FlagTree（统一多后端的增强版Triton编译器）、FlagCX（统一通信库）、FlagScale（并行训推一体框架）等组件。FlagOS 1.5版本已经发展成为“4+3”模式，即四大核心开源技术库+三大开源工具平台。通过开源技术库和开源工具平台的相互支撑，提供了更广泛的硬件支持、和更完善的组件协同。双重推力加持，中国AI的自主未来在受访业内人士看来，国产AI软件生态的崛起，恰逢天时地利。外部环境的压力和内部政策的推力，共同构成了发展的双重驱动力。一方面，供应链不确定性催化国产替代。全球GPU市场长期被英伟达主导。然而，2022年美国禁售A100芯片后，2025年H20芯片也停止对中国市场供应，这让国内AI企业纷纷将目光转向本土芯片。以寒武纪为例，今年前三季度，在行业高景气度的推动下，公司实现营收46.07亿元，同比增长2386.38%；净利润16.04亿元，同比增长320.19%；扣非后归母净利润14.19亿元，同比增长264.52%。另一方面，我国是全球最大的集成电路消费国家，日益增长的市场需求为集成电路行业带来了广阔的市场空间。国家层面发布的《关于深入实施“人工智能+”行动的意见》等政策，正全方位推动人工智能的规模化落地。这意味着，国产AI芯片及其软件生态将在智慧城市、智能工业等海量场景中获得宝贵的“试验田”和“练兵场”，这是任何封闭生态都无法比拟的优势。在国内外政策和产业催化下，国产云端芯片渗透率提升已成大势所趋。根据TrendForce数据，2025年国内AI 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