University of Tsukuba | Grad. Scho. Syst. and Info. Eng. | Dept. Comp. Sci. | List of Courses
Tetsuya Sakurai, Hiroto Tadano, Akira Imakura
E-Mail sakurai [AT], tadano [AT], imakura [AT]
Office hours SB1022 Fri. 10:00-11:00
Cource# 01CH103, 02RA215
Area Information Mathematics and Modeling
Course style Lecture
Term FallAB
Period Fri3,4
Room# SB1001
Keywords Computational science, large-scale linear algebra computations
Prerequisites Basic knowledge of linear algebra and programming
relation degree program competence Knowledge Utilization Skills,International Skills,Research Skills,Expert Knowledge
Outline Lectures on algorithms and modeling that emerge in scientific computing, focusing particularly on large-scale linear computation.
Course plan
  1. Learning to model physical phenomena, with example applications (Weeks 1 and 2)
    Partial differential equations, discretization, boundary conditions
  2. Numerical Methods and Computational Tools
  3. Mastering fundamentals relating to matrix operations (Weeks 3 and 4)
    Matrix norms, BLAS, LAPACK, sparse matrices
  4. Understanding iterative solution techniques for linear equations (Weeks 5 and 6)
    Krylov subspace methods, preconditioning
  5. Understanding eigenvalue solution methods (Weeks 7 and 8)
    Dense matrix solution techniques, sparse matrix solution methods
  6. Understanding parallelization of numerical computing methods (Weeks 9 and 10)
    Vector operations, matrix ordering, region segmentation
References T. Sakurai, An Introduction to Numerical Methods with MATLAB and Scilab, University of Tokyo Press., Tokyo (2003) (in Japanese)
Evaluation Grades are assessed using three reports (33.3 points each) as follows:
A+ (90 - 100)
A (80 - 90)
B (70 - 80)
C (60 - 70)
D (- 60)
Misc. 奇数年度開講。