Contents Intro.

The talk starts with a brief historical background of high-performance computing (HPC), machine learning (ML), and big data (BD) analytics. Today, HPC is essential for modeling and simulation; ML is being used for simulation and data analytics; and BD is vital for acquiring and analyzing data from many different sources. To satisfy tomorrow’s computational needs, the convergence of HPC, ML, and BD will be beneficial, if not mandatory. The talk presents three projects developed by the speaker and his team—the first project shows how data and thread regrouping may enhance HPC performance; the second project illustrates a ML-based imaging technique using HPC that can guide real-time surgical procedures; and the third project demonstrates how geospatial BD analytics using HPC and ML can help regional economic success. The talk ends with a discussion on computational challenges where Nara Institute of Science and Technology and Wichita State University can contribute together for common good.

Details

Publication year

2019

Form

電子化映像資料（1時間25分09秒）

Series title

情報科学領域・コロキアム ; 2019年度

Note

講演者所属: Wichita State University, Kansas, USA

講演日: 2020年1月14日

講演場所: エーアイ大講義室(L1)

Country of publication

Japan

Title language

English (eng)

Language of texts

English (eng)

Author information

Asaduzzaman, Abu