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oai:ipsj.ixsq.nii.ac.jp:00193608 2025-01-19T23:51:58Z 6164:6165:6640:9657

A Research on Big Data and AI Analysis Algorithm Optimization Using GPUs Van, Sang Tran 小林, 良輔 山口, 利恵 中田, 登志之 その他 With the significant increase of computer performance, in recent years, many complex human-like tasks have been resolved by computer software in reasonable time. These tasks include visual object recognition, speech to text interpretation, human face authentication, etc... However, computer performance is going to reach the limit as the CMOS transistor size near the limit. On the other hand, the amount of data which need to be processed is incredibly growing up under Internet of Thing, Industrialization 4.0, social network era, which leads to the demand of higher scalability on current Big Data, AI analysis algorithms. Our research investigated on finding scaling solution for Big Data, AI analysis problems. The whole development is composed of 2 phases: acceleration by GPU and distributed computing application. This research focuses on the former topic. A real-world dataset was used in this research to achieve more real-life optimization and model evaluation result. With the significant increase of computer performance, in recent years, many complex human-like tasks have been resolved by computer software in reasonable time. These tasks include visual object recognition, speech to text interpretation, human face authentication, etc... However, computer performance is going to reach the limit as the CMOS transistor size near the limit. On the other hand, the amount of data which need to be processed is incredibly growing up under Internet of Thing, Industrialization 4.0, social network era, which leads to the demand of higher scalability on current Big Data, AI analysis algorithms. Our research investigated on finding scaling solution for Big Data, AI analysis problems. The whole development is composed of 2 phases: acceleration by GPU and distributed computing application. This research focuses on the former topic. A real-world dataset was used in this research to achieve more real-life optimization and model evaluation result. 情報処理学会 2018-06-27 eng conference paper https://ipsj.ixsq.nii.ac.jp/records/193608 マルチメディア，分散協調とモバイルシンポジウム2018論文集 2018 1212 1219 https://ipsj.ixsq.nii.ac.jp/record/193608/files/IPSJ-DICOMO2018181.pdf application/pdf 906.0 kB 2020-06-27