The rapid growth of energy consumption in the computing industry and the transformation demands of the new power system have made computing and electric power coordination a critical trend. Based on an analysis of the characteristics and needs of both the computing and electric power industries, this paper proposes the definition of computing and electric power coordination. Then, it analyzes the challenges, explores key measures for computing and electric power coordination. It is hoped that this study will provide references for related research and practical applications.
Artificial Intelligence Native Networks (AINNs) mark a transformative phase in the evolution of communication networks, characterized by a core integration of artificial intelligence within network architectures. This integration unveils unprecedented technological features and substantial potential for diverse applications. The study begins by examining the interplay between the development of Large Language Models (LLMs) and network infrastructure, thereby elucidating the concept, advancement, and standardization of AINNs along with their potential application scenarios. Subsequently, an analysis of the anticipated trends, challenges, and opportunities facing AINNs is presented. The paper concludes by proposing future research directions and recommendations for the continued evolution of AINNs.
By focusing on the needs of computing power development in the era of artificial intelligence (AI), this paper analyzes the current situation and technical challenges of computing power development in three dimensions: computing devices, computing units, and infrastructure. To address the challenges of performance, efficiency, and energy consumption brought about by the development of AI, the concept of high-quality computing power is proposed, and the technological directions for the development of high-quality computing power are prospected.
This article focuses on the advantageous conditions of the China’s computing industry and provides an in-depth analysis of opportunities and challenges faced by China in expanding emerging markets. It proposes comprehensive and detailed countermeasures and suggestions in six key dimensions. These are intended to provide an action guide for China’s computing power enterprises to grasp the opportunities in emerging markets, enhance international competitiveness, and jointly promote the prosperity and development of the global digital economy.
The computing power center includes large-scale hardware facilities such as servers and storage devices, providing a unified computing platform for processing complex computing tasks. How to design and implement a computing power center cloud architecture compatible with universal computing power, super computing power and intelligent computing power is a hot research direction. This paper focuses on analyzing the development and evolution trend of the research paradigm driven by education cloud, as well as the demand for computing power of different representative disciplines. And this paper gives the research progress of the industry in computing power network, supercomputing center, smart computing platform and data governance. On this basis, this paper proposes an overall network architecture of computing power center cloud, describes the basic structure, security protection and open service design of this architecture, and gives a typical docking scheme of computing power connected to the grid in cross-domain scenarios. The architecture can meet the needs of scientific computing in heterogeneous computing force management, data model concurrent training, distributed reasoning, high-performance computer simulation, and scientific research application services. Based on the flat network design of Spine-Leaf two-tier devices, integrating the platform capabilities of general computing power, super computing power, intelligent computing power and other platform capabilities, it will be able to form a new cloud service network architecture with heterogeneous integration, high-performance computing and storage, and open capabilities.
The rapid development of information technology has made the demand for efficient heat dissipation in data centers more and more urgent, and liquid cooling technology has gradually become a solution to the problem. And the cold plate liquid cooling technology has become the mainstream liquid cooling method due to its advantages of high reliability, easy maintenance and low transformation cost. Blind-mate quick disconnect is an important component in cold plate liquid cooling system, which has significant advantages in operation efficiency, reliability and safety. It is one of the core components to ensure the efficient operation of liquid cooling system. This paper analyzes the importance and key features of the blind-mate quick disconnect in cold plate liquid cooling, points out the current decoupling dilemma of the blind-mate quick disconnect.Further, this paper puts forward the development paths and suggestions of the blind-mate quick disconnect in cold plate liquid cooling system.
Computing power is a new form of productivity in the digital economy era, continuously injecting new momentum into the digital transformation of various industries. This paper aims to explore the innovation in teaching models driven by computing power and its value assessment framework. It provides a detailed analysis of how computing power assists in building personalized learning ecosystems, enhancing the teaching experience in smart classrooms, and opening up new frontiers in immersive learning. By constructing a value assessment framework for the intelligent transformation of education, this paper offers guidance strategies and recommendations from multiple dimensions, including value orientation, cost-benefit analysis, and sustainability considerations, for both theoretical research and practical applications in the field of education.
The concept of “asset” often carries three layers of meaning in practical use, with each layer adding specific conditions. The concept of “data asset” originated from an emphasis on the potential value of data and has gradually evolved into a specialized term in China, becoming a key part of promoting the market-oriented allocation reform of data factor. The process of data assetization can be correspondingly divided into three stages, each with varying degrees of implementation difficulty, and it is not necessary to pursue a one-time complete data assetization. At present, most entities in China have not yet met the conditions required for the first and second stages of data assetization, and there is still a need to consolidate foundations, stabilize expectations, and continue to deepen the exploration of data assetization.
With the rapid development of new technologies, the deep integration and penetration with various fields have driven our smart city construction to a new stage of digital transformation. Based on a comprehensive review of the construction of smart cities in China, this article compares the differences between the new guidance for 2024 and the old guidance for 2014, summarizes and sorts out the new requirements for deepening the development of local smart cities in the new stage, and proposes suggestions for implementation.
Facilitating the robust and systematic advancement of the data security industry can significantly bolster the construction of data security capabilities in critical sectors. This can give full play to the intrinsic value of data assets and expedite the progression of the digital economy. Analyzing the motivation of the development of the data security industry can better clarify the development context of the data security industry, and provide reference for grasping the development orientation of the data security industry and predicting the future development trend of the industry. From the perspectives of external factors and internal factors, this study analyzes the impacts of external factors such as releasing the value of data elements, implementing the top-level design of data security, coping with the new situation of data security, developing industrial digitization and enhancing the international influence of data security, as well as internal factors such as technical products, capital empowerment and high-quality and skilled labor on the development of data security industry. It finally puts forward suggestions for the further development of data security industry.
With the extensive deployment of new services in the electric power industry, high requirements have been put forward for the key performance of electric power communication networks, such as delay and security isolation. This paper firstly describes the SPN layering model and the fine granularity multiplexing process. Then, it illustrates the new SPN technologies for electric power applications, including GE interface fine granularity, constant bit rate, and intelligent operation and maintenance. Finally, it introduces the application of the new technologies in practice.
The amount of industrial data has grown exponentially with the development of the digital economy, and general search has been unable to meet the requirements of searching massive multi-source heterogeneous data in the industrial field. Identification resource search for industrial internet of things can connect to identification resolution nodes, and use identification to obtain object or user information efficiently. It can get much more valuable industrial data, and carry out more in-depth and professional information mining for industrial scenarios. It is an efficient way to transform industrial data to productive forces. First, this paper analyzes the necessity of developing identification resource search for industrial internet of things in detail. Then, it introduces key technologies such as data collection, knowledge construction, data search as well as identification resolution preprocessing. Finally, it gives suggestions on the application scenarios and development trends.
This paper analyzes the current construction situation and standard research of quantum network management systems, and provides two deployment architectures for quantum network management systems based on the situation of quantum networks. It proposes the functions and interface construction points of quantum network management systems, and points out the main differences between quantum network management and classical network management, in order to guide related standardization work and application in engineering practice.
Firstly, the extraction and ambiguity handling method of standard text keywords based on multi-algorithm fusion combines TF-IDF and TextRank, while considering word position, part of speech, word length, and word frequency to complete the keywords extraction of standard text. Then, it uses Hanlp to process the same text and complete the contrastive ambiguity processing. Through the analysis of experimental results, this method has a significant effect on improving the efficiency and processing quality of keywords extraction and ambiguity handling in standard texts. It also provides an innovative approach for large models to conduct standard knowledge mining by combining knowledge bases with intelligent agents.