UCD School of Mathematics and Statistics Undergraduate Summer School in High-Performance Computing and Data Visualization

*** This is an old event. The materials on this page are left here for archival purposes only. ***

I shall be running a UCD-Mathematical Sciences summer school on high-performance computing and data visualization in summer 2013. I am aiming the programme at penultimate-year undergraduate students, although students in other years may be admitted in exceptional circumstances. All students (UCD and non-UCD) from numerate disciplines are invited! The application deadline is now passed - watch this page for lecture notes and other course materials.

Course details

  • Dates: 27 May -31 May 2013
  • Fee: None
  • Venue: UCD School of Mathematics and Statistics, Computer lab TBC

Scope of summer school: With increasing computational power available even on desktop level, opportunities for simulating large-scale physical, biological and social systems are ubiquitous. Moreover, as the scale and scope of simulations increase, the challenge of handling ever-larger data sets becomes immense. This challenge is amplified by the phenomenon of "big data" - the generation of more and more data as the internet permeates our lives, and the possibility of a "data wall", should the rate of data generation outstrip our capacity to interpret this information. The object of this module is to study high-performance computing at elementary level (along with standard data I/O) operations, and to interpret the resulting large data files in an automated fashion using batch-processing techniques that can be implemented in Matlab.

Learning Outcomes: On completion of the module, students should

  1. Be able to write elementary programs in Fortran, including subroutines, and compiler linking
  2. Be able to handle data I/O in Fortran
  3. Be able to implement multi-threading in Fortran
  4. Be familiar with the theory of multi-threading, the pitfalls in its implementation, and its limitations with respect to computer architecture
  5. Be able to automate data post-processing from Fortran simulations in Matlab, including Matlab I/O, visualization (e.g. 3D isosurfaces, contour plotting, animations), and statistical post-processing
  6. Be familiar with the pitfalls associated with data-processing of weakly-structured files

Prerequisites: Students must have taken ACM 20030 or its non-UCD equivalent and have a working knowledge of Matlab. No prior knowledge of Fortran of the Linux operating system is assumed, although some knowledge of these areas would be helpful.

Assessment: No assessment takes place in the summer school. Students who complete the school satisfactorily will receive a certificate of attendance.