Tuesday, 13 November 2018 at 00:00
This course is in English.
Registration will open about three months before the course/school starts.
The tipical approach to the art of programming from the point of view of a scientist only rarely permits to reach good results in terms of computational performances. The basic knowledge about how a computer machine really works permits even to a naif programmer to better write his own code and eventually to optimize properly any kind of scientific program. This knowledge is way more important in the field of High-Performance Computing where the correct exploitation of the modern architecures is crucial to the achievement of scientific results.
This code is addressed to C and Fortran programmers that, even without notions of computer science, have necessities to learn tricks and techniques to quickly debug and optimize codes without restarting from scratch. Aim of this course is to guide the user to analyze and improve performances of his software, by introducing techniques and tools used in the HPC world. Software and hardware profilers will be presented and it will be showed how to find bottlenecks and how to fix them. Typical techniques of optimization (cache reuse, unrolling, inlining, vectorization) will be presented the use of mathematical libraries will be discussed. Furthermore, the use of compiler flags on different architectures and compilers will be introduced.
By the end of the course the student will be able to:
- manage efficiently the computer memory
- use tools to profile programs and measure their performance
- understand and use efficiently compilers and compiler options
- optimize programs
- understand and incorporate scientific libraries in their programs
- design a debugging strategy based on dedicated tools and other techniques
Researchers and programmers interested to a quick and efficient debugging and to a knowledge of fundamental concepts of optimization. This course is particularly suitable for people approaching for the first time to issues of computer programming in the framework of scientific calculations.
Knowledge of Fortran or C/C++. Elementary notions of Linux/Unix.