Tsinghua University deploys Numerical Algorithms Group Numeric Library
October 28, 2010

Tsinghua University deploys Numerical Algorithms Group Numeric Library

Internationally acclaimed Tsinghua University, reportedly chosen by the majority of China's top ranking college applicants and whose prestigious graduates include both the current President and Vice President of China, has signed a cooperate agreement for a campus-wide license with Numerical Algorithms Group (NAG), a not-for-profit organization that collaborates with world-leading researchers and practitioners in academia and industry, and offers what are arguably the most rigorously tested and documented numeric algorithms in the world.
Tsinghua University's licensing agreement includes the NAG Library, which can be used from many environments including C, C++, Fortran, MATLAB, Excel, and parallel or multicore platforms, and the NAG Fortran compiler.
"We are very pleased to introduce NAG products into Tsinghua and believe that this cooperation will effectively improve Tsinghua's research environment," said Edward Chou, NAG's general manager for Greater China.
Chou continues, "Tsinghua University's top tier researchers and students should be equipped with first-class R&D tools. NAG's mathematical and statistical algorithms-- in terms of the scope of functionalities, accuracy, and performance, are the most superior numeric computing software one can find worldwide. In past years, because of budget shortfalls, scientists in China had to develop the required algorithms by themselves-requiring many man-hours for development and making re-porting of routines to new platforms difficult. But with the rapid economic growth and increased demand in China, it is no longer necessary or deemed economical for researchers at Tsinghua to develop these mathematical and statistical algorithms by themselves."
Ted Liu, NAG's technical director in Greater China added, "Scientists should focus on their own expertise to develop the best products rather than develop several unprofessional, low accuracy, poor performance algorithms".