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谢伏瞻
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李培林
    男,汉族,出生于1955年5月,山东济南人,博士,研究员,全国人民代表大会社会建设委员会副主任委员,中国社会科学... 详情>>

    先进高效的算力体系实践情况

    摘要

    2022年《政府工作报告》提出要促进数字经济发展,促进产业数字化转型。算力是数字经济发展的动力引擎,是产业顺利实现数字化转型、数据要素价值得以充分释放、行业应用创新繁荣的基石。发展数字经济,算力建设先行,高质量数字经济发展需要先进高效的算力体系支撑。本报告重点阐述以数据中心为载体的算力系统和靠近数据产生端的边缘计算两类经典算力系统,并探讨量子技术在计算领域的价值和应用场景。此外,本报告还介绍了数据中心算力系统中典型技术的发展实践现状,包括云计算、CPU+GPU异构计算、液冷解决方案以及跨地域资源高效管理等实践对金融业务系统处理能力、智能化、节约能源和空间、资源利用等方面的效果和价值;介绍了边缘计算的意义及其在提升云-边算力体系效率、胜任特定金融业务场景方面取得的效果;介绍了运用量子技术突破上述经典算力约束、算法瓶颈,提升金融算力系统处理能力和运算效率的价值,以及可落地金融应用场景、实践探索。

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    Abstract

    In the 2022 “Government Work Report”,it is proposed to promote the development of digital economy and the digital transformation of industries. Computing power is the driving force for the development of the digital economy,and the cornerstone for the smooth digital transformation of the industry,the full release and utilization of data elements,and the innovation and prosperity of industrial applications. To develop the digital economy,we should give priority to the construction of computing power. The development of high-quality digital economy needs the support of advanced and efficient computing power system. This paper expounds two kinds of classical computing power systems:computing power system with data center as the carrier and edge computing near the data generation end,and discusses the value and scenarios of quantum technology in the field of computing. It introduces the development and practice of typical technologies in the computing power system of data center,including cloud computing,heterogeneous computing,liquid cooling solution,and their effects and values on the processing capacity,intelligence,energy and space conservation,resource utilization and other aspects of the financial service system. Besides,it presents the significance of edge computing and its effect on improving the efficiency of cloud-edge computing system and serving specific financial service scenarios. The paper also introduces the value of quantum technology on breaking through the above classical computing power constraints and algorithm bottlenecks,improving the processing capacity and computing efficiency of financial computing power system,as well as exploring the applicable financial scenarios and practices.

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    作者简介
    李志华:
    李华龙:
    官极:
    徐雯昕:
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