Ural Federal University

ASC22 Student Supercomputer Challenge Preliminary: Large AI Language Model and AI in Scientific Research

Retrieved on: 
Monday, January 17, 2022

More than 300 teams around the world compete on challenging tasks like the large AI Language Model Yuan 1.0 and the 2020 Gordon Bell Prize-winning application DeePMD-kit.

Key Points: 
  • More than 300 teams around the world compete on challenging tasks like the large AI Language Model Yuan 1.0 and the 2020 Gordon Bell Prize-winning application DeePMD-kit.
  • In the preliminary round of ASC22, all teams are required to tackle two very advanced tasks: Yuan1.0 - large AI language model, and an excellent combination of AI with advanced scientific application - DeePMD-kit.
  • Training such a large AI model requires massive computing tasks of parallel computing, presenting a real-life test to the student teams for their skills in supercomputing application optimization.
  • The ASC Student Supercomputer Challenge is sponsored and organized by Asia Supercomputer Community and supported by Asian, European, and American experts and institutions.

Ural Federal University and Elsevier Collaborate to Support Research Excellence

Retrieved on: 
Thursday, October 17, 2019

The system will help Ural Federal University's management with the research process at an institutional, departmental and individual level.

Key Points: 
  • The system will help Ural Federal University's management with the research process at an institutional, departmental and individual level.
  • "The development of scientific research with the involvement of reputable international partners is one of the key priorities of our university," points Viktor Koksharov, Rector of Ural Federal University.
  • Throughout the project, Ural Federal University staff will work very closely with their Elsevier partners by providing valuable feedback on these tools and their functionality.
  • Since 2013 Ural Federal University has been a participant of the Russian Academic Excellence Project 5-100.

Ural Federal University and Elsevier Collaborate to Support Research Excellence

Retrieved on: 
Thursday, October 17, 2019

The system will help Ural Federal University's management with the research process at an institutional, departmental and individual level.

Key Points: 
  • The system will help Ural Federal University's management with the research process at an institutional, departmental and individual level.
  • "The development of scientific research with the involvement of reputable international partners is one of the key priorities of our university," points Viktor Koksharov, Rector of Ural Federal University.
  • Throughout the project, Ural Federal University staff will work very closely with their Elsevier partners by providing valuable feedback on these tools and their functionality.
  • Since 2013 Ural Federal University has been a participant of the Russian Academic Excellence Project 5-100.