Introduction to Numerical Analysis 2
数値解析序論２

Lecture notes (レクチャーノート)

Part a

• Lecture a1: Fortran review
  • Solutions for Lecture a1
• Lecture a2: Basic algorithms, Gaussian elimination
• Lecture a3: Arrays in Fortran
  • Solutions for Lecture a3
• Lecture a4: Linear system with triangular matrix; Report 1
• Lecture a5: 2D arrays
• Lecture a6: Gaussian elimination
  • Solutions for Lecture a6
• Lecture a7: Gaussian elimination performance
• Lecture a8: LU decomposition; Report 2

Part b

• Lecture b1: Functions in Fortran
  • Solutions for Lecture b1
• Lecture b2: The conjugate gradient method
• Lecture b3: Preconditioned conjugate gradient method
• Lecture b4: Report 1 (preconditioned CG)
• Lecture b5: Sparse matrices
• Lecture b6: Storage of sparse matrices
• Lecture b7: Sparse matrix for the 2D Laplacian
• Lecture b8: Report 2

Reference

• Fortran cheatsheet
• Fortran quirks

Class information

• Evaluation 評価方法: based on reports (probably 2 large reports each quarter and some small ones). You need at least 60% points to get C. Please submit the reports through the LMS portal.

  Academic integrity: Submit only your own code or the code that I provide. Do not share the solutions with other students! If I notice copying, I automatically give 0 points and might take other steps.

• Self study: about 3 hours/week is expected

• Contact:

  • email npozar@se.kanazawa-u.ac.jp
  • office #228 (自然科学５号館)