Welcome to MATH 8650: Advanced Data Structures (Fall 2015)

This course is designed to introduce students to advanced data structures and algorithms from computer science. The goal is to provide a solid foundation for sophisticated software development, research in computational mathematics, and other computational problems.

We will be using the Python programming language for weekly exercises and larger group projects.

1. This site: http://www.math.clemson.edu/~heister/math8650-fall2015/
2. Blackboard: http://bb.clemson.edu (grades, materials, etc.)
3. No required textbox. Reading material will be supplied.
4. Syllabus

1. About CPUs, memory speeds, caches, and optimization:
   • CPUs over time:
     • http://www.gotw.ca/publications/concurrency-ddj.htm
     • https://en.wikipedia.org/wiki/Moore%27s_law
   • latency numbers: https://gist.github.com/hellerbarde/2843375
   • complexity spreadsheet: https://goo.gl/CA9gIi
   • caches: https://en.wikipedia.org/wiki/CPU_cache
   • memory hierarchy: https://en.wikipedia.org/wiki/Memory_hierarchy
   • std vector vs std list (and caches): http://baptiste-wicht.com/posts/2012/12/cpp-benchmark-vector-list-deque.html
   • Premature optimization: http://c2.com/cgi/wiki?PrematureOptimization

• deadline: Dec 1, before class
• groups of two to three
• deliverables: code, ~2 page written report, 15 minute presentation
• Grading:
  1. Code: documented, object oriented, well structured, automated tests
  2. Presentation: adequate introduction to topic, show results
  3. Report: problem summary, solution, difficulties encountered, literature
• Projects: can pick your own, should deal with:
  • complexity, performance
  • data structures
• Suggested projects:
  1. Board game with AI, minimax strategy, game trees (quarto, checkers, nim, tic-tac-toe, connect5, 4 in a row in 3d, endgame chess)
  2. Solvers/generators for Mathematical puzzles (conway, sudoku, Str8ts, Kakuro, …)
  3. Path finding: A* vs Dijkstra
  4. Red-black trees, self-balancing trees
  5. Efficient delaunay mesh triangulation
  6. Weighted Quick-union with path compression (performance comparisons)
  7. Graph partioning/coloring (minimum k-cut, Kernighan–Lin algorithm?)

See http://www.registrar.clemson.edu/pdf/academicCalendar2015.pdf and http://www.registrar.clemson.edu/html/examSched.htm for important dates.