{"id":18052,"date":"2025-02-18T16:32:32","date_gmt":"2025-02-18T09:32:32","guid":{"rendered":"https:\/\/thaipropertynews.com\/feeds\/?p=18052"},"modified":"2025-02-18T16:32:32","modified_gmt":"2025-02-18T09:32:32","slug":"chinas-technology-from-national-level-products-to-breakthroughs-in-specialized-fields","status":"publish","type":"post","link":"https:\/\/thaipropertynews.com\/feeds\/?p=18052","title":{"rendered":"China’s Technology: From National-Level Products to Breakthroughs in Specialized Fields"},"content":{"rendered":"

BEIJING<\/span><\/span>, Feb. 18, 2025<\/span><\/span> \/PRNewswire\/ — A news report from sinolub:<\/p>\n

In the era of rapid digitalization and intelligent development, China’s<\/span> technology is rising on the global stage at an unprecedented speed. From artificial intelligence to high-performance computing, and from basic research to practical applications, China<\/span> has not only launched national-level products like Deepseek but also achieved remarkable accomplishments in numerous specialized fields. Recently, a paper titled “High-performance CPU-GPU Heterogeneous Computing Method for 9-Component Ambient Noise Cross-correlation” once again highlighted China’s<\/span> strength in the application of high-performance computing and artificial intelligence.<\/p>\n

A Breakthrough in Seismic Data Processing<\/b><\/p>\n

The paper, published in Earthquake Research Advances, introduces a novel approach to seismic data processing using\u00a0CUDA-accelerated computing. This method leverages the power of NVIDIA GPUs to significantly enhance the efficiency of calculating nine-component noise cross-correlation functions (NCFs) from ambient seismic noise data. By integrating advanced stacking techniques such as time-frequency domain phase-weighted stacking (tf-PWS), the research not only accelerates the computational process but also improves the signal-to-noise ratio (SNR) of the data.<\/p>\n

This breakthrough is particularly significant given the critical role of seismic data in understanding and mitigating natural disasters. The ability to process large-scale seismic datasets quickly and accurately can lead to more precise imaging of the Earth’s subsurface, enhancing our understanding of geological structures and potentially saving lives through better disaster preparedness.<\/p>\n

The Journey of Innovation<\/b><\/p>\n

The development of this high-performance computing framework is a testament to the collaborative efforts of Chinese researchers. Initially commissioned by Dr. Wang Weitao from the Institute of Geophysics, China Earthquake Administration, the project was spearheaded by a team from the University of Science and Technology of China<\/span> (USTC), led by Professors Sun Guangzhong and Wu Chao<\/span>. Their work laid the foundation for the single-component version of the code, which was later expanded and optimized by doctoral candidate Wang Jingxi.<\/p>\n

Wang’s contributions include the implementation of advanced preprocessing methods, batch processing, multi-GPU adaptation, and the extension to nine-component data. These enhancements have not only improved the computational efficiency but also broadened the applicability of the framework to various seismic data processing tasks.<\/p>\n

Open Source and Global Collaboration<\/b><\/p>\n

In a move that underscores China’s<\/span> commitment to global scientific collaboration, the program’s source code has been made publicly available on GitHub. This open-source initiative allows researchers worldwide to access, modify, and build upon the work, fostering a collaborative environment that accelerates scientific progress. The program has been rigorously tested using datasets from Japan’s<\/span> Hi-net seismic network and research groups led by Professor Yao Huajian at USTC, demonstrating its robustness and versatility across different data scales.<\/p>\n

\n

\"Practical<\/a>
Practical Applications and Future Implications<\/span><\/p>\n<\/div>\n

Practical Applications and Future Implications<\/b><\/p>\n

The practical applications of this technology are already being realized. The accelerated stacking algorithms have been successfully deployed in various experiments, including imaging of mining areas, fault zones, and regional geological structures. These applications highlight the potential of the technology to contribute to fields such as resource exploration, environmental monitoring, and disaster prevention.<\/p>\n

Looking ahead, this research sets a new standard for seismic data processing and underscores the potential of AI and GPU-accelerated computing in solving complex scientific problems. As China<\/span> continues to invest in cutting-edge technologies, the global scientific community can expect more groundbreaking innovations that push the boundaries of what is possible.<\/p>\n

A Global Perspective on China’s<\/span> Technological Advancements<\/b><\/p>\n

China’s<\/span> rapid technological advancements have not gone unnoticed on the global stage. According to a report by the Australian Strategic Policy Institute, China<\/span> now leads in 57 out of 64 key technology areas, ranging from quantum computing to advanced materials. This progress is driven by substantial investments in research and development, with China’s<\/span> R&D expenditure exceeding 2.64% of its GDP in 2023, surpassing the EU average.<\/p>\n

Moreover, China’s<\/span> commitment to international cooperation is evident through agreements such as the recently extended U.S.-China Science and Technology Cooperation Agreement.<\/span>\u00a0<\/p>\n

<\/div>","protected":false},"excerpt":{"rendered":"

<\/p>\n

BEIJING<\/span><\/span>, Feb. 18, 2025<\/span><\/span> \/PRNewswire\/ — A news report from sinolub:<\/p>\n

In the era of rapid digitalization and intelligent development, China’s<\/span> technology is rising on the global stage at an unprecedented speed. From artificial intelligence to high-performance computing, and from basic research to practical applications, China<\/span> has not only launched national-level products like Deepseek but also achieved remarkable accomplishments in numerous specialized fields. Recently, a paper titled “High-performance CPU-GPU Heterogeneous Computing Method for 9-Component Ambient Noise Cross-correlation” once again highlighted China’s<\/span> strength in the application of high-performance computing and artificial intelligence.<\/p>\n

A Breakthrough in Seismic Data Processing<\/b><\/p>\n

The paper, published in Earthquake Research Advances, introduces a novel approach to seismic data processing using\u00a0CUDA-accelerated computing. This method leverages the power of NVIDIA GPUs to significantly enhance the efficiency of calculating nine-component noise cross-correlation functions (NCFs) from ambient seismic noise data. By integrating advanced stacking techniques such as time-frequency domain phase-weighted stacking (tf-PWS), the research not only accelerates the computational process but also improves the signal-to-noise ratio (SNR) of the data.<\/p>\n

This breakthrough is particularly significant given the critical role of seismic data in understanding and mitigating natural disasters. The ability to process large-scale seismic datasets quickly and accurately can lead to more precise imaging of the Earth’s subsurface, enhancing our understanding of geological structures and potentially saving lives through better disaster preparedness.<\/p>\n

The Journey of Innovation<\/b><\/p>\n

The development of this high-performance computing framework is a testament to the collaborative efforts of Chinese researchers. Initially commissioned by Dr. Wang Weitao from the Institute of Geophysics, China Earthquake Administration, the project was spearheaded by a team from the University of Science and Technology of China<\/span> (USTC), led by Professors Sun Guangzhong and Wu Chao<\/span>. Their work laid the foundation for the single-component version of the code, which was later expanded and optimized by doctoral candidate Wang Jingxi.<\/p>\n

Wang’s contributions include the implementation of advanced preprocessing methods, batch processing, multi-GPU adaptation, and the extension to nine-component data. These enhancements have not only improved the computational efficiency but also broadened the applicability of the framework to various seismic data processing tasks.<\/p>\n

Open Source and Global Collaboration<\/b><\/p>\n

In a move that underscores China’s<\/span> commitment to global scientific collaboration, the program’s source code has been made publicly available on GitHub. This open-source initiative allows researchers worldwide to access, modify, and build upon the work, fostering a collaborative environment that accelerates scientific progress. The program has been rigorously tested using datasets from Japan’s<\/span> Hi-net seismic network and research groups led by Professor Yao Huajian at USTC, demonstrating its robustness and versatility across different data scales.<\/p>\n

\n

\"Practical<\/a>
Practical Applications and Future Implications<\/span><\/p>\n<\/div>\n

Practical Applications and Future Implications<\/b><\/p>\n

The practical applications of this technology are already being realized. The accelerated stacking algorithms have been successfully deployed in various experiments, including imaging of mining areas, fault zones, and regional geological structures. These applications highlight the potential of the technology to contribute to fields such as resource exploration, environmental monitoring, and disaster prevention.<\/p>\n

Looking ahead, this research sets a new standard for seismic data processing and underscores the potential of AI and GPU-accelerated computing in solving complex scientific problems. As China<\/span> continues to invest in cutting-edge technologies, the global scientific community can expect more groundbreaking innovations that push the boundaries of what is possible.<\/p>\n

A Global Perspective on China’s<\/span> Technological Advancements<\/b><\/p>\n

China’s<\/span> rapid technological advancements have not gone unnoticed on the global stage. According to a report by the Australian Strategic Policy Institute, China<\/span> now leads in 57 out of 64 key technology areas, ranging from quantum computing to advanced materials. This progress is driven by substantial investments in research and development, with China’s<\/span> R&D expenditure exceeding 2.64% of its GDP in 2023, surpassing the EU average.<\/p>\n

Moreover, China’s<\/span> commitment to international cooperation is evident through agreements such as the recently extended U.S.-China Science and Technology Cooperation Agreement.<\/span>\u00a0<\/p>\n

<\/div>\n

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