首页|New Machine Learning Study Findings Have Been Reported by Investigators at Natio nal University of Defense Technology (A Survey of Machine Learning for Network-o n-chips)
New Machine Learning Study Findings Have Been Reported by Investigators at Natio nal University of Defense Technology (A Survey of Machine Learning for Network-o n-chips)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Machine Learning. According to news reporting originating from Hunan, People's Republic of China, by NewsRx correspondents, research stated, "The popularity of Machine Learning (ML) has extended to numerous disciplines, including the domain of Net work-onchips (NoCs), leading to a consequential impact. Recent works have explo red ML models' appli-cability for NoCs design, optimization, and performance eva luation." Funders for this research include National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC), Excellent Youth F oundation of Hunan Province. Our news editors obtained a quote from the research from the National University of Defense Technology, "ML-based NoCs design has demonstrated superior performa nce to heuristic methods employed by human experts in NoCs design. This has faci litated a tight collaboration between ML and NoCs research, offering novel persp ectives and optimization strategies to advance NoCs design. In this paper, we pr esent a comprehensive survey into implementing ML techniques for NoCs. Initially , we provide an overview of ML-based research for NoCs in two aspects: (i) the a doption of ML for performance modeling and prediction and (ii) ML-based for NoCs design, including individual components (such as routing algorithm, arbitration , traffic control, etc.). Subsequently, we summarize the challenges and difficul ties in designing NoCs for applying ML techniques and discuss the preliminary so lutions to these issues. Finally, we prospect the perspective on future research directions for expanding the application of ML techniques to diverse scenarios of NoCs, exploring the adoption of ML techniques for NoCs design automation."
HunanPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNational University of Defens e Technology