CN. Computational Science (nothing in core)

CN1. Numerical analysis

  Floating-point arithmetic
  Error, stability, convergence
  Taylor's series
  Iterative solutions for finding roots (Newton's Method)
  Curve fitting; function approximation
  Numerical differentiation and integration (Simpson's Rule)
  Explicit and implicit methods
  Differential equations (Euler's Method)
  Linear algebra
  Finite differences

CN2. Scientific visualization

  Concepts
  Tools
  Examples

CN3. Architecture for scientific computing

  Vector architecture and pipelining
  MIMD machines
  Distributed systems and the network-of-workstations (NOW) approach
  Networks
  Timing, measurement, terminology (MFLOPS, and so forth)
  Benchmarks and elementary performance measurement

CN4. Programming for parallel architectures

  Review of parallel programming techniques
  Parallel algorithms for scientific computation
  Effects of array element and loop ordering
  Example languages

CN5. Applications

  Simulation
  Molecular dynamics
  Fluid dynamics
  Celestial mechanics
  Optimization (linear programming, integer programming, dynamic programming)
  Structural analysis
  Geology
  Computerized tomography
  Military and defense applications