Scientific Computing

The Scientific Computing Group (SCG) works on diverse scientific applications in a wide variety of fields including

• Astrophysics,
• Atmospheric and ocean modeling,
• Material sciences,
• Nanosciences, and
• Data mining and data-intensive computing.

We also tackle generic problems in scientific computing, including

• Numerical linear algebra, such as dense and sparse linear/eigen system solvers;
• Mathematical libraries and templates; and
• Parallel programming environments and software tools.

SCG's ultimate goal is to advance scientific computing by developing and enhancing applications in key disciplines, as well as developing tools and libraries for addressing general problems in computational science.

Group Leader: Esmond Ng

» Visit the SCG site.