Welcome

Welcome to Scientific Computing, Comp-605

Logistics

• Office hours: announced on the course Canvas page or by appointment.

Note

Who am I?

• Assistant Professor in the Department of Mathematics & Statistics and the Computational Science Research Center

• Previously:

  • Research Software Engineer for 3+ years at Caltech, in the CliMA group

  • Postdoctoral Research Associate at CU Boulder, in Jed Brown’s PhyPID group

  • PhD in Applied Math from NJIT

  • some industry experience with CAD/CAM system development and at Pixar in the Research group

Resources

• SIAM Membership is free for students (30% discount on SIAM books)

• US-Research Software Engineer association free professional association membership with lots of resources

• Women in HPC professional society free professional association membership with lots of resources

• Books and additional resources

  • Hager and Wellein (2010), Introduction to High Performance Computing for Scientists and Engineers

  • Rauber and Rünger (2010), Parallel Programming for Multicore and Cluster Systems, Springer, ISBN 9783642048173

  • van de Geijn, Myers, Parikh (2019): LAFF on Programming for High Performance (free online)

  • Eijkhout, Chow, van de Geijn (2017), Introduction to High-Performance Scientific Computing (free PDF)

  • Grama, Gupta, Karypis, Kumar (2003), Introduction to Parallel Computing

  • Greenbaum and Chartier (2012), Numerical Methods Design, Analysis, and Computer Implementation of Algorithms – an excellent, comprehensive book.

  • Boyd and Vandenberghe (2018), Introduction to Applied Linear Algebra – practical introduction to linear algebra for computer scientists; free PDF

  • Trefethen and Bau (1997), Numerical Linear Algebra – fantastic, but limited to numerical linear algebra and covers more advanced topics.

  • Scopatz and Huff (2015), Effective Computation in Physics – Python language, data science workflow, and computation.