Sources of parallelism. Characterization and performance of parallel algorithms. Parallel programming models. Practical case studies of parallel programs in the scientific, industrial, and business worlds.
Currently, parallel systems have become standard computational systems, and are currently from laptops and desktops (dual or quad) to teams in large supercomputing centers (Top 500 Supercomputing). When required problem solving computationally expensive or very demanding in memory, it is necessary to use the parallel application. This course introduces the concepts and fundamentals of parallel computing and presents the main parallel architectures and programming tools used to achieve high performance.