Difference between revisions of "Isc3313 schedule"

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3. January 10 2014 Introduction to C++<br>
 
3. January 10 2014 Introduction to C++<br>
 
4. January 13/15 2014 Algorithm development (Monte Carlo Integration)<br>
 
4. January 13/15 2014 Algorithm development (Monte Carlo Integration)<br>
5.  January 15 2014 Program testing and documentation<br>
+
5.  January 15/17 2014 Program testing and documentation<br>
 
6. Visualization and analysis of results<br>
 
6. Visualization and analysis of results<br>
  

Revision as of 05:48, 17 January 2014

( Overview | Syllabus | Schedule | Lectures | Assignments | Project | Misc)

I. January 6, 2014 Components of Scientific Computing

II. A simple example - Using a Monte Carlo approach to approximate problems
1. January 8 2014 UNIX basics
2. January 10 2014 Netbeans IDE: an integrated development environment for C++ programming
3. January 10 2014 Introduction to C++
4. January 13/15 2014 Algorithm development (Monte Carlo Integration)
5. January 15/17 2014 Program testing and documentation
6. Visualization and analysis of results

III. Solving a non-linear equations
1. Description of problem and some simple algorithms
2. Iterative methods, required accuracy of result
3. Implementation of the Bisection method
4. Program testing and documentation

IV.Object oriented programming concepts in detail
using the non-linear equation problem and implementing more methods
1. Encapsulation
2. Inheritance
3. Polymorphism
4. Abstract classes and datatypes

V. Operations on vectors and matrices
1. Development of general functionality that is usable in many places
2. Vector and Matrix operations
3. Vector norms
4. Concurrency and parallel processing of such calculations using C++

VI. Polynomial interpolation of data
1. Description of problems and (biological) applications
2. Algorithms: Lagrangian interpolation in detail
3. Implementation to fit a set of data
4. Piecewise interpolation
5. Implementation and visualization of of piecewise interpolation

VII.Solving ordinary differential equations systems
1.Description of problem: Lotka-Volterra Predator-Prey system
2.Algorithms
3.How to use functions from other libraries
4.How to assess correctness of program
5.Visualization of results

VIII. Markov chain Monte Carlo Integration
1.Description of method
2.Example application
3.Implementation
4.Testing and visualization of results

IX.Capstone project