Oxford Talk Series on Computing
Oxford Talk Series on Computing
This page is the main page for the talk series organised by Jacob Wilkins (Research Software Engineering Associate in High Performance Computing). These talks are usually fortnightly and cover a wide variety of topics. In general each talk is 20 minutes, with 10 minutes time for discussion. Full hour slots will be available on request. If you are interested in giving a talk and need some inspiration, see the list of possible talk ideas below. If you wish to sign up to give a talk, please send me an email at jacob.wilkins@oerc.ox.ac.uk.
| Date | Time | Speaker | Talk Topic | Talk Title | Speaker | Talk Topic | Talk Title | Room |
|---|---|---|---|---|---|---|---|---|
| 5/12/2019 | 12:30 | Jacob Wilkins | Compilation | From Code To Computer | Ian Bush | Parallelism and the Future | Tony Hoare Room, Robert Hooke Building | |
| 27/2/2020 | 13:00 | Stef Salvini | Numerical Accuracy | To Error is Computer | Min Chen | Visualisation | Visualisation | Lecture Theatre B, 7 Keble Rd. |
| 12/3/2020 | 13:00 | David De Roure | Algorithms | Algorithms and Music | Yassamine Mather | Effective Supercomputing | Lecture Theatre B, 7 Keble Rd. | |
| 21/5/2020* | ||||||||
| 4/6/2020* |
Dates labelled with an asterisk (*) are unconfirmed and subject to change
Possible talk ideas (in no particular order)
- Complexity analysis (big-O, how-to)
- Algorithm design (breaking down a problem, thinking differently to pure maths)
- Version control (introduction to git, useful tricks, maybe more advanced and if time mercurial)
- Regular Expressions (What, how, why and intro to how-to in various languages [Python, C, C++])
- Programming paradigms (OOP, Functional, Imperative, List), maybe specific intros to different ones, e.g. Haskell or Lisp for a session
- Intro to various used (not necessarily mainstream) languages (R, Perl, OpenCL)
- Compilers (What they are, what they do, how they do, why this can be good/bad)
- Dangers of floating points and other numerical arithmetic
- Jenkins, gitlab runner and testing platforms (Why, how to)
- Docker, Singularity and containers
- esting and test suites (Design, considerations, completeness)
- Build systems (Intro to make, cmake)
- Intros to specific algorithm classes (Pros/Cons of: encryption, sorts, compression, matrix ops, random numbers)
- Different development approaches (Agile, SAFE, TDD, etc.)
- Parallel paradigms (Why GPU, OMP, MPI, etc. How they differ, different problems)
- Esolangs and code golf (Learning languages for fun and why this can be beneficial)
- Profilers and debuggers (GDB, DDD, Intel Profiler, GPU profilers?)
- Experimental data and file handling and metadata
- Code human-interface design (how to make a friendly UI)
- Computer security
- Continuous Integration/Continuous Deployment services.
- Overview of available services, or focus on a particular service.
- Modern C++ features and practices