High performance scientific computing in C++

Modern C++, with its support for procedural, objected oriented, generic and functional programming styles, offers many powerful abstraction mechanisms to express complexity at a high level while remaining very efficient. It is therefore the language of choice for many scientific projects. However, achieving high performance on contemporary computer hardware, with many levels of parallelism, requires understanding C++ code from a more performance centric viewpoint. In this course, the participants will learn how to write C++ programs which better utilize typical HPC hardware resources of the present day. The course is geared towards scientists and engineers, who are already familiar with C++17 (at the very least C++14), and wish to develop maintainable and fast applications. They will learn techniques to better utilize CPU caches, instruction pipelines, SIMD functionality and multi-threading. Shared memory parallel programming on multiple CPU cores will be introduced using parallel STL of C++17 and Intel (R) Threading Building Blocks. The participants will also learn basic GPGPU programming in C++ using NVidia CUDA and Thrust