Abstract
Prevalent hardware trends towards parallel architectures and algorithms create a growing demand for graduate students familiar with the programming of concurrent software. However, learning parallel programming is challenging due to complex communication and memory access patterns as well as the avoidance of common pitfalls such as dead-locks and race conditions. Hence, the learning process has to be supported by adequate software solutions in order to enable future computer scientists and engineers to write robust and efficient code. This paper discusses a selection of well-known parallel algorithms based on C++11 threads, OpenMP, MPI, and CUDA that can be interactively embedded in an HPC or parallel computing lecture using a unified framework for the automated evaluation of source code—namely the “System for AUtomated Code Evaluation” (SAUCE). SAUCE is free software licensed under AGPL-3.0 and can be downloaded at https://github.com/moschlar/SAUCE free of charge.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
