Teaching High Productivity and High Performance in an Introductory Parallel Programming Course - Kumar, Vivek (2021 IEEE 28th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW), 2021)
Multicore processors are ubiquitous. Several prior research has emphasized the need for high productivity parallel programming models that require minimal changes to the sequential program and can still deliver high performance using runtimes based approaches on various architectures. In this paper, we present the structure and experience of teaching the Foundations of Parallel Programming course (FPP) at IIIT Delhi using a task-based parallel programming model, Habanero C/C++ Library (HClib). FPP covers a wide breadth of topics in parallel programming but emphasizes both high productivity and high performance. It is being offered at IIIT Delhi in the spring semester for undergraduate and postgraduate students since 2017. We describe our novel approach where the students start the learning process using the traditional parallel programming models, discover the underlying limitations, and build runtime solutions to achieve high performance.