【导读】美股全线上涨！国际油价一度大跌超5%！英伟达重大宣布 中国基金报记者 伊万 美东时间3月16日，随着国际油价回落，以及多国释放原油储备等消息，市场对通货膨胀担忧暂时缓解，美股三大指数集体收涨。 截至收盘，道琼斯指数涨0.83%，报46946.41点；标普500指数涨1.01%，报6699.38点，与道指一起结束四连跌；纳斯达克综合指数涨1.22%，报22374.18 点。 宏观方面，据央视新闻，美国总统特朗普16日表示，希望欧洲国家以及日本、韩国等国协助保障霍尔木兹海峡航行安全。 据央视新闻，伊朗方面，当地时间16日，伊朗总统佩泽希齐扬在其个人社交媒体透露了他与法国总统马克龙的通话内容。 佩泽希齐扬表示，伊朗并未挑起这场残酷的战争。抵御侵略是伊朗的天赋权利，这正是伊朗擅长的。利用美国在该地区的军事基地来对抗伊朗，企图破坏 伊朗与邻国的关系，这种行为必须停止。若无视以色列与美国对伊朗发动的侵略，就无法实现地区的和平与稳定。伊朗绝不会向霸凌者屈服。 佩泽希齐扬说，伊朗期待国际社会谴责这一侵略行为，并说服侵略者尊重国际法。在确保伊朗领土未来不再遭受攻击之前，谈论结束战争是毫无意义的。 国际油价大跌超5% Q ...

Core Insights - The hybrid computing cluster has become an essential technology option for the industry in pursuit of optimal cost-performance by 2025, shifting from a previous stance of caution regarding mixed computing resources [1][3] - The potential re-entry of NVIDIA's H200 into the Chinese market has garnered significant attention, emphasizing the necessity for domestic computing capabilities in China [1] - The establishment of a "heterogeneous computing scheduling" technology moat is currently a hot topic in the industry [1] Group 1: Technological Trends - The consensus has shifted towards hybrid computing, with Intel combining its Gaudi 3 accelerator with NVIDIA's B200 GPU to enhance the inference limits of the NVIDIA B200 cluster by up to 70% [3] - Software-hardware collaboration is identified as a major trend in addressing computing challenges, with NVIDIA's CUDA software platform being a critical technology moat [3] - The development of intelligent computing is viewed as a comprehensive competition involving technology, ecology, and applications, with the establishment of an open, unified, and cooperative ecosystem being key to overcoming challenges [3] Group 2: Market Dynamics - The ability to solve the "mixed computing" challenge will determine who holds pricing power in the market, with a clear business model emerging from standardizing computing resources and achieving economies of scale [4] - The daily average token call volume for Wunwen AI Cloud has increased fivefold over the past five months, indicating a surge in demand for computing resources [5] - The rapid iteration of models presents new challenges for computing resources, with significant increases in token calls observed during specific high-demand periods [5] Group 3: Future Directions - The infrastructure for AI creation must evolve from focusing solely on inference efficiency to supporting long-term tasks, context management, and multi-modal resource scheduling [6] - The trend towards heterogeneous computing is expected to grow, with industry experts emphasizing the need for systematic methodologies and tools to address the technical challenges of mixed computing [6][7] - The rapid expansion of computing demands will lead to increased energy costs, with projections indicating that global GPU computing cluster electricity consumption could exceed 1000 TWh by 2030, accounting for approximately 2.5% of global electricity consumption [7]